Into the Impossible With Brian Keating - Cal Newport: Want to Be More Productive? Do LESS (#399)

Episode Date: March 5, 2024

Join my mailing list https://briankeating.com/list to win a real 4 billion year old meteorite! All .edu emails in the USA 🇺🇸 will WIN! What if I told you that you could be more productive… by doing less? Sounds crazy, but as per today’s extraordinary guest, it’s true! Meet Cal Newport, associate professor of computer science at Georgetown University and bestselling author of Deep Work, Digital Minimalism, and other books that offer a refreshing departure from the hustle culture that pervades modern society. Instead of advocating for endless multitasking and shallow engagement, Newport champions the art of deep work – the ability to focus intensely on cognitively demanding tasks, producing results that are not only profound but also deeply satisfying.  Today, he presents his newest book, Slow Productivity: The Lost Art of Accomplishment Without Burnout.  Join us as we explore the potential beyond the constant hustle and bustle of modern life and discover what you can accomplish by doing not more but fewer things! Key Takeaways: 00:00:00 Intro 00:04:50 Judging a book by its cover 00:07:48 The meandering path of productivity  00:13:54 The importance of time blocking 00:17:47 Working on fewer things  00:26:48 Controlling time and scheduling 00:31:02 Quality over quantity  00:45:31 Cal’s thoughts on writing books  00:53:37 Galileo’s scientific legacy and engaging with new ideas 01:12:44 What’s your five-year plan?  01:22:06 The potentials and dangers of AI  01:33:45 The value of technology in education  01:54:14 Outro — Additional resources: 📝 Get one month of Snipd Premium for free with this link: https://get.snipd.com/Cx7S/brianSnipd Snipd lets you take Smart Notes 🧠 with AI 💡 — it’s my favorite podcast player 😀 ! 📢 Ownership of your health starts with AG1. Try AG1 and get a FREE 1-year supply of Vitamin D3K2 and 5 FREE AG1 Travel Packs with your first purchase 👉 https://drinkag1.com/impossible ➡️ Connect with Cal Newport: 💻 Website: https://calnewport.com/ 📚 Get Slow Productivity by Cal Newport: https://calnewport.com/slow/ ➡️ Follow me on your fav platforms: ✖️ Twitter: https://twitter.com/DrBrianKeating  🔔 YouTube: https://www.youtube.com/DrBrianKeating?sub_confirmation=1  📝 Join my mailing list: https://briankeating.com/list  ✍️ Check out my blog: https://briankeating.com/cosmic-musings/  🎙️ Follow my podcast: https://briankeating.com/podcast Into the Impossible with Brian Keating is a podcast dedicated to all those who want to explore the universe within and beyond the known. Make sure to subscribe so you never miss an episode! Learn more about your ad choices. Visit megaphone.fm/adchoices

Today, we're featuring an extraordinary guest whose insights have transformed the way we approach work, technology, and life itself. Meet Cal Newport, an associate professor of computer science at Georgetown University, and a best-selling author of many books, including Deep Work, Digital Minimalism, and other books that offer a refreshing departure from the hustle culture that pervades modern society. Instead of advocating for endless multitasking and shallow engagement, Cal champions the art of, of deep work, the ability to focus intensely on cognitively demanding tasks, producing results that are not only profound but also deeply satisfying. Today he's here to present his newest book, Slow Productivity, The Lost Art of Accomplishment Without Burnout.

Join us and unlock the potential that lies behind the constant pings, dings, rings, hustle, and bustle of modern knowledge-working life. discover what you can accomplish as a student, a professor, any kind of knowledge work that you do whatsoever, not by doing more, but actually, paradoxically, by doing fewer things. Cal is just a phenomenal individual, a great intellect. He's kind of the professor's professor. He writes books on the art of being professor and academic, how to be a straight-A student. You'll hear about that in the episode. And it really made me wish that he existed and wasn't 10 or more years younger than me, more handsome, wealthy, no, no, I don't mind any of that. He's a wonderful individual and just a

great, great person, just full of good cheer, never seen him down, never seen him depressed, indefatigable, as they say. And as for another professor, you'll hear we talked a lot of shop in this episode. It's been fun, especially given everything that's going on in college campuses, including my own the last few months since October 7th and everything that's happened at Harvard, Penn, MIT and the kind of campus craziness with the anti-woke forces rallying against DEI bureaucrats. It's been a challenge. And to talk to another professor, to talk shop, you know, as they say, when amateur painters

get together, they talk about style and composition and the milieu and the zeitgeist of the time at which the art was created. And when real artists get together, as opposed to art historians, they talk about where to get cheap turpentine. So it's fun to kind of geek out, nerd out, faculty to faculty, friend to friend going through the academic hunger games, as we describe them. He's really got a phenomenal perspective. And he's such a generous individual. We talked a lot about personal advice, professional advice, and it's not just useful to egghead professors like me in the Ivy Tower. It's also a useful knowledge for anyone, no matter what your level of education. How to appreciate

what we have, how to take a rest, take a break, take a Sabbath, a digital, Sabbath, how to do more with less, and hopefully he'll help me with my ongoing X addiction. I'm addicted to X, not triple X, but to X. I do stay on there way more than I should, except on the Sabbath. That is my digital and physical Sabbath. You'll hear about that. Hear about a shout out to a upcoming guest by the time you hear this, although I just recorded it with him. Sam Harris was my guest. We have a little shout out to him in this conversation, and you'll really enjoy my conversation with Sam, which just clocked in at three and a half hours.

So my longest ever conversation on the Into the Impossible podcast. That's coming soon. I do hope you're enjoying these. It's hard on audio-only formats to get feedback to know who's out there, who's not out there, and are you enjoying this or if you're enjoying this? So it really helps to share this. And please do subscribe to Cal's channel, The Deep Life, on YouTube, and on audio, and leave a review for him.

Tell him you found out about him on the Brian Kee-Dee. Into the Impossible. And while you're out, leave a review, a rating of the Into the Impossible podcast. It's the only

visible metric as we gamify what we do. And so without further ado, Cal Newport, an astounding individual. And I recommend following this up

with episodes that we've done in the past with other academicians like Avi Lobb and others talking about that. And Ryan Holiday

also, you dig back in the back catalog of fun interview I did with our mutual friend Ryan Holliday about the stoic life, not just the deep life. And so I hope you'll enjoy it.

It means a lot to mean that you guys are out there and listening to this project, the Into the Impossible project. So here we go. Into the Impossible. Enjoy. Any sufficiently advanced technology is indistinguishable from magic. Open the pod bay doors, Hal. First thing I always do, Cal. I don't know if you've noticed this,

but whenever I have a brilliant author on such as you, I take the opportunity to do what you're not supposed to do, which is illegal to do in some counties, which is to judge a book by its cover. And for that, that will entail the following. It will entail the title, the subtitle, and this mesmerizing, deep sort of scene on the cover. I want you to walk the audience through all of that. And the only role is you can't say my publisher made me do it. So, Cal, take it away, help us judge this wonderful book by its cover. Are we sure we don't see your mountain house on the cover? Is that I'm trying to be,

trying to see here, this is a picture of where you are right now, right? I don't think that would, yeah, one of my twins would jump off of that. So no, that is not my house. No.

Yeah, so we have the title, slow productivity. We have the subtitled, the lost start of accomplishment without burnout. And we have like a very atypical cover for me, because it's full bleed graphics. So if you're listening instead of watching,

full bleed graphics of a, house up on a cliff top, you have a fall foliage woods with a path going through the woods, presumably maybe up towards that, that mountaintop house. So I pushed for all of that. That, that this was my strategy. You can tell me if this is a smart strategy or not, but I pushed for all of this. The book is about this idea of rethinking what we mean by productivity. And the lost art piece of the subtitle, the lost art of accomplishment without burnout, is that instead of coming up with new ideas, I look back at what I call traditional knowledge workers. So I said people like scientists from times past, playwrights from times past, poets and writers, people who work with their brain

for a living, but in times past they have full autonomy to do it. They're not in a cubicle somewhere. What did they do? Can we isolate those principles? And then can we adopt them to modern work where we have computers and email and bosses? So it's rediscovering a lost art. So the stories in the book try to capture that vibe. I wanted the cover to capture a vibe too. I wanted the cover to give you a visceral intuition of slow productivity. So you see that path through the woods at a quiet house up on the mountaintop. It immediately puts into a mindset of I am walking and thinking and working on something really cool and I'm not stressed out and there's no cellular so my slack doesn't work here. I want to convey all of that in a picture. So you're in the right mindset to rediscovering

different ways of creating valuable things with your mind. A typical Cald-Newport cover would typically be solid color, huge font, just like slow productivity, and maybe, you know how they do now in business books, like one picture in the middle. There's a, there's a turtle or something, you know, just like one picture in the middle, just like, this is what we're doing. And I said, now we're going to try something different. So we'll see. Hey, did it work for you? Like, what did you think? Do you like it? I enjoyed it. It was very sort of becolic. It made me, it put me into a state of relaxation, trying to figure out where it is. There's a meandering path, which is kind of suggestive of the slow nature of the, of the enhancement of productivity. I see this as two words.

Slow productivity. So you can't have slow without, you can't be productive, perhaps, without being slow. And there's this famous saying, you know, in the military, the Navy SEALs, which you look more qualified to be a part of than me. But, you know, slow is smooth, you know, slow is smooth. smooth as fast, something like that. But I want to kind of harken to this. This actual made me think originally of the Fourth Commandment, which in the, which is in the Hebrew Bible, it is, it goes like this. It goes six days shall thou labor and do all thy work. But the seventh day, Cal is a Sabbath for the Lord. In that, you shall do no work, not your son, your daughter, your maid servant, your maid man, whatever, your cattle, so the animals got a Sabbath. I take this

to mean the following. A lot of people say, oh, on Shabbat, so I'm Jewish and I take advantage of this law and I rest on the Sabbath. I don't do work. Some say I don't do work the rest of the week, but that's not the point. On the Sabbath, it is thought that you can't enjoy the fruits of your labor on the Sabbath unless you labor. In other words, Hebrew has this weird structure, which English doesn't. So the word mitzvahs translate as good deed, but it doesn't mean that. It means commandment. And so there's actually a command form. So this is written in a commandment. And therefore, you must work.

It says literally in the Hebrew, it says you must work six days. And then the seventh is a Sabbath. How do you resonate with that? If you enjoy the, you know, if productivity is sort of a goal, obviously it has to be considered a goal, is there not a sort of a concomitant obligation to, you know, work hard, fast? In other words, can you enjoy the slowness of it without actually having some intensity? along the way. Well, I think it's an interesting analogy that I actually just wrote about. So the week before we're talking, you know, I wrote an essay about Heschel's book, the Sabbath, which he, this is from the 50, 1951, which is not long after he was rescued from Nazi Germany to make it back to America.

And I wrestle with this exact question because that's his interpretation as well, right? So partially what he's saying is, yeah, you look at, you look in Genesis, right, and you see God worked for six days. And he also rested. He did both. And both were holy. Though Heschel points out the first time you actually see something as holy, Kodosha or Kudusha, the first time you see something ascribed as holy in the beginning of the Torah is the seventh day of rest. So it's like seeing the rest itself. There's something holy and like taking that, taking that rest. This I think actually gets to the central tension that's happening right now in our cultural discussion on productivity. You've probably picked this up. A lot of your list

years have as well that starting around 2019, 2020, there's been an anti-productivity movement that's picked up a lot of steam, especially online, but also in books, that comes out of a good place. I think it comes out of the same place my book came out of, which was a sense of burnout is more than it was. My work is exhausting me more than it was. Something seems out of whack with the way we're working, especially in knowledge work, I want to focus on, focus on that. So this anti-productivity movement arose. But part of the issue with a lot of the discourse and anti-productivity is it forgot those first six days. So it began to say, okay, why are we exhausted by work? Well, work itself is just an exploitative construct. And the solution to the sense that something is out of whack, which again,

I think is right, something is out of whack. The solution is just the demonize work. Or to, to say any desire to want to accomplish something, this is just your bourgeois mind has been reprogrammed by the imperatives of capitalism. And so do nothing is the right response. I don't think this was getting at it. And I think the ancient Jews did get this. They did figure it out. It's like, no, you need both.

God looked at what he created. He said, this is great. He also rested. You need to figure out how do you have a life that is able to balance those two things. So I think that's where we're out of whack. Maybe we were at a period we were too far on the first six days. Let's just go. Let's go.

Let's just more work. Let's get it done. And now we've shifted too far the other way. Oh, maybe work is all a construct. And let's just do nothing. But no, we need to rediscover what was written down 4,000, 6,000 years ago is no, we have to figure out both. And not in like a simplistic balance way. I mean, to me, slow productivity is my attempt to actually have a sophisticated ethic of doing work that you're proud of that's important, that's meaningful.

not having work conquer all of your life. You know, and that doesn't mean a 50-50 balance. It's not trite. How do you do both things? How can you be there for your kids, but also produce stuff that, you know, your kids are going to be proud of once you're gone? That's like, it's challenging, right? I mean, how do you create the earth that also rest on the seventh day? I think it's like a really big question.

That's what I'm trying to tackle. Hey, out there, sorry for this little break. I know you're sick of all the ads and interruptions, but such is life. I don't make the algorithm. I just am beholden to it. So, but I hope you're finding this interview enjoyable. Cal is a delight and kind of the professor's professor, the person he wish you had as an undergraduate, brilliant brainiac, but he knows how to say no.

And I hope you won't say no to this tiny request, which is just to subscribe or follow and like the video wherever you're watching it or subscribe and follow to the audio channel that you're listening to this on. And for extra credit, this professor will give you a bonus point if you leave a small asterism, a tiny constellation, five stars, hopefully. But if not, let me know why not. That really means a lot to me. So you know, the drill all set. Let's get back to the episode, shall we? Yeah. And I think it's very evocative of the many benefits of this thoroughness and slowness and attention, which is sort of a root, root cause of a lot of happiness and gratitude.

You know, you really can't be a happy person if you're an ingrate. And also, you know, the notion that even things like land needs rest. You know, if a bunch of dirt needs rest, and then again, in the Torah every seven years, you have to give the land arrest, you have to free your slaves every seven years. If they don't want to go, you have to hammer and nail through their ear because they're supposed to do it. But you make a clear case that the purpose of slowness and kind of this pace is not so that you'd be better productive.

In other words, it may be correlated with more productivity, but can you speak to the fact that you're not really writing this as a way of like, Well, if you do the vipassana, you know, for 20 minutes a day, that takes away from productivity. But you're going to be so much more productive because, you know, talk about how this structure should be applied by knowledgeware. And you're speaking to, you know, probably 90,000 PhDs and postdocs and faculty around at least, you know, in my half of the audience. And then I'm sure an equal number in yours. So tell me, what can we apply as not thinking of it as, you know, this cost benefit analysis? that we have to run, but actually it's intrinsically valuable for its own sake.

Well, I mean, I think that trap in thinking is so fundamental that I call myself out on it in the book itself. You know, there's these three principles that go on and one of them do fewer things. And I'm making the argument about why that's important. And I'm trying to make the argument about how can you do this, especially if you have a boss. And I do pull out the economic argument, you know, hey, by the way, overloading your schedule doesn't make you more productive. You just lose a bigger fraction of your time to admin overhead. Then I have what I call an interludes. So each of my principles have an interlude where I step back and kind of check myself. And I have this interlude where I'm basically saying this isn't really about an economic argument. Like yes, yes, if you're

less overloaded, you might produce more. But that's not really what this is about. This is about a life than some sense is more sanctified and meaningful, right? Not being completely overloaded by your work is a better life distinct from productivity type arguments. So there's this tension. I think that's like a dialectic in the book. Like on the one hand, there's this argument that like the way we're working now, it doesn't work really well. And what I'm arguing here is not a typical zero sum labor politics type negotiation where you say, look, we're going to we're going to get more things and it's bad for the employer. It's not a zero sum auto worker union. Like we're just going back and forth. Like you want to pay us less. We want more. Actually, the way we're working is so bad that

that these other ways are going to be better for everybody. But at the same time, the tension polling does, but this is not just about maximizing production because the slowness itself is going to make your life more meaningful. My whole motivation for writing the book is, you know, I have three young boys who just need as much time for me as possible right now. They're all elementary school age. So it's also, I want to give them as much time as possible.

So it's not about production. It's about how do I keep working like a reasonable contained box. So I think you're hitting at this sort of core, push and pull in the book. The way we're working stupid, but fixing it is not just about, well, how can we get more out of it? Fixing it is how do we make this work better? We do better work, but also we have much more control over it. It's a more subtle path to navigate, but man, it's worth it. Man, we need to figure that out, especially your audience. I mean, us academics, postdocs, PhDs, we have a ton of freedom, but that also gives us a ton of rope to hang ourselves

with. It's a weird, it's an interesting case study studying our world. There's a lot you control, but it's very, very hard to control. Just having the control is not enough. You've got to know what you're trying to do. I also have three boys. And the interlude that I really locked on to in the middle part of the book is called, what about overwhelmed parents? And as I copiously highlighted this section, because working on fewer things you say can paradoxically produce more value in the long term. Overload generates an untenable quantity of non-productive overrength. overhead. I love this quote. Overload generates overhead or unproductive overhead. When we're balancing all these things and you have to have it all. And I actually, I don't know when I first reached out to you and it was like, you know, a platonic asking you to the prom, you know, if you'd come on the podcast, I had no idea that you were aware of my podcast.

And you said, well, there's only three of us, you know, meaning there's only three real professors that do podcast. Now there's four, Sean Carroll at he's at Johns Hopkins. Not so far from you. So he's a real professor now. He wasn't for a long time, but now he is a good friend. And then there's Huberman, you know, who I have actually been invited by Andy on the podcast, and he was a professor here at UC San Diego. And I'm very thankful to him for the invitation. I understand you're going on very soon, or maybe you already did. But the pace of communications has made me optimistic and sanguine for communicating with alien life forms and proximate centurray because Andy and I exchange a text message every six to eight weeks. But anyway, we're overwhelmed parents.

So both of those other guys, Andy and Sean Carroll, they're childless. Andrew's, I'm trying to make a match, make a shit look for Andrew. We'll see if that ever happens. Sean's married, has no kids. How do you handle these different careers that you have, different aspects, different mountains in the David Brooks lexicon? How do you handle these, you know, professoriate writer, writing for the New York, writing the articles.

Is it Atlantic or New Yorker? New Yorker. I get this. New Yorker. New Yorker. How are you handling this? And what would you give to the 12.5% of my audience that's female? You might have a higher fraction that YouTube tells me I've got a good, a good solid eighth of my audience is female. But how the hell do they do it?

Because, you know, I can barely keep it together. And I didn't, you know, push these children out of my body. How do you handle it? How do you juggle these multiple things? And what advice of any, like, is there a differentiation between advice you give to women, advice you give to men, perhaps? I think there is because especially when you're leaning into the culture that exists now, which I call pseudo productivity in the book, which is the idea that we'll just use activity

as to proxy for useful effort. So the more you're doing, the better. This is, by the way, roughly, it's my claim in the first part of the book. This was the compromise we came up with when knowledge work emerged as a major sector. is like, we can't measure productivity like an auto factory. We can't measure productivity like a farm field and count bushels per acre. So we'll just use activity as a proxy for useful effort. This can be incredibly inequitable because now your measure of usefulness comes down to

how much activity are you able to basically tolerate. And so now when you add in, oh, by the way, I'm doing something else useful like raising children that I birth, you now have less time for just, overall activity, then the person with no kids. And now, so that person, if you're going to judge them, is like, well, that's a more productive person because they're active more.

They work later. They answer emails more. You're now selecting for one group over the other for reasons that have nothing to do with actual ability. So it is a hard problem. Slow productivity, I think, helps with all of this. What I do, and let me just preface this by saying, I wrote this book for myself.

So I'm evolving based on the ideas of the book. 2012 was so good they can't ignore you, which was about how do you find work you love. Yeah, I was about to go on the academic job market. So I was like, I should probably understand how do people end up loving their work because I'm about to commit to a career for the rest of my life. Assistant professor, I write deep work because I'm figuring out how do I get tenure, right? I need a published paper. Like, how do I do good work?

Then digital minimalism comes out after that because like I'm looking around me and everyone's like, why aren't you on social media? And then they're all suddenly everyone's all stressed out and it's like, okay, what's going on here with that. And then a world without email, I'm tenured and there's email is coming in and like, okay, what's going on? Why do we communicate so terribly with so much overwhelmed? So I always just write what I care about. But a couple things that matter for me is fixed scheduled productivity. Here's my working hours. I don't want to go past those. All right, I have to make it fit. And this might lead to drastic changes in the what I say yes to or

what I don't say yes to. It might lead me to have to be super sequential about things. I'll write a book now, but not do these other things. Then I'll do these other things when I'm not writing the book. It might make me have to be much more careful about my time during those hours. But I've been very careful about that. When I brought podcasting into my life, I said, it gets a half day. My show gets a half day a week. That's it. And if I want to do something new with the show, I can do whatever I want, so long as I can fit into a half day each week. And so if I want to innovate, I better hire someone to take on what I'm already doing so we could have more time to do something else, it's not allowed to leave a half day a week. And part of what made podcasting

possible was more recently in my academic career, I've been pushing my writing and my academic work closer together. I've become heavily involved in these digital ethics initiatives at Georgetown. So now suddenly my writing for the New Yorker, for example, which is on technology and culture, fits with my academic program. It's taking slots in my time that I might have pre- 10-year have spent writing computer science papers. So that opened up time that allowed me to fit podcasting carefully into my fixed schedule, which is all to say, I just, I work backwards from the time I want to spend, and I'm very careful. I really think a lot about how much do I want to work. So slow productivity as a book is me actually trying to get a formal philosophy around this

intuition in some sense. And, you know, when I thought about, you know, the core tenants of the book to take example of. So recently, there's been a huge amount of fuss over this, the Applevision Pro. We're talking in early February. A book comes out. This interview will come out on March 5th, the day of the book release. And there's all these people interested in it. And my older brother, who's, you know, he's a technophile.

It just loves everything tech. He's like, oh, you've got to get one. And then not even Netflix or YouTube are on it. So you have this great opportunity, Brian. And you can make the like a cosmology app and, and, you know, Neil deGrasse Tyson, you know, blank out of it. And I said, I'm about to interview Cal Newport. And if I tell him, I just took on like another, another thing.

He will, you know, send his hit squad after me, right? He'll, he'll digitally, you know, scold me. So the process of saying no and how you do that. Early on you made this point, you know, early on your career, you need to say yes to a lot of things. maybe not, you know, as many as people think. But then later on, you need to kind of say no, almost as much as possible in order to do that. Is that what people talk about?

They talk about time blocking, time boxing. You know, it's not the shunning and a shoeing of tools. It's using them forcefully. So you give a kind of example of your schedule and how you do it. Can you walk, you know, academics that are listening? Let's just nerd out. Let's niche down to blow up, Cal here. Let's just talk about academics, graduate students, undergraduates, postdocs.

And you also did write a book, How to Be a Straight A Student, right? That's a wonderful. So I actually say, I use a tool called Readwise and Readwise surfaces books that I've read and highlighted. And it'll also surface similar books that I've read. So I read, you know, deep work and all your other, but then it'll bring up like, how to be a straight A student. And at first I was like, I don't need this. You know, like, I got my, you know, 100% on my IQ test. I don't need this anymore. So, but then I start reading it. And I'm like, well, you know, my, kids, my nephews, nieces, they can all use this. So what are some of the tools for undergraduates? Let's just take each cohort that you and I have been undergraduate, you know, let's do the whole academic hunger games, you know, all these zero-sum games. Undergraduate, graduate student,

what is the one tool in slow productivity that might apply to each one of those cohorts up through postdoc, assistant professor, and then tenure, and then they can't fire us, right? We're so bad they can't fire us, right? I'll cover the whole range. Yes. And I did write. So I started writing student books just so people know the timeline. I wrote my first book, How to Win at College, and I was still an undergraduate. And then how to become a straight-day student came out my first year at grad school. And then I wrote one more a few years after that. And then it was my fourth book, actually, when I was a postdoc. It was my first hardcover idea book. Because I decided back in college, I'm going to do two things. I can do computer science and write books. And I don't want to do anything else. And that have been very, very focused on just doing those two things. All right. So what's the, I think you're writing a book now with your left hand. I'm almost, yeah, I'm almost done. Okay. Okay. So let's get let's simplify. I'm going to give two, let's give two ideas for the entire student to, uh, useless 10 year professor, uh, life cycle. Um, I'm going to say control your projects, control your time. Control your time.

Early on, this is going to be very, very important more so than control your projects. If you're an undergraduate, you don't have projects. You have assignments. You don't control them. Okay. So that's not relevant yet, but control your time will be relevant throughout this whole life cycle. And the idea here is you decide what you're going to do with your time. You decide when you're going to do the things you have to do. The opposite of this is allowing the things you have to do decide for you what you're going to be doing. Oh my God, this is due tomorrow. All right, let me, you know, typical undergraduate thing. Stay up real late and try to write this. Or oh my God, I have three exams in two days and how am I ever going to get this, how am I ever going to get this work done? That's letting your your work control, your

schedule as opposed to the other way around. And so, I mean, I really advocate if you're an undergraduate and a grad student, first of all, the courses you know you have. Like, I have to take these courses. So it's very regular. There are these times on these days of the week. I know what the work is for these courses. Like my theoretical physics class has weekly problem sets. Like I know how long that takes when they're due. Put aside the time for working on these things, same days, same places, same times on your calendar. I go to this library, these three sessions. The third session is with my group to help where I'm stuck. This is when I do the work. I know I'm going to have to do this work each week. Let me decide when I'm going to do it. Now you can level that up to non-regular things in your student life. All right. I have a syllabus. Right. Okay, Professor Keating, when's my midterm? Ah, I see. It's coming up in April. How much study am I going to have to do? What's that going to involve? Great. Let me go back three weeks from that deadline. I'm going to start putting it on my calendar to study sessions. So take control. There's effort. you know you have to do, control where it goes. That alone really changes your experience,

especially as a student. And it turns it away from this weird, panicky, reactive thing to something where you'll be like I was as an undergraduate, where I had to pretend to be studying during finals period because my friends were going to, you know, throw me out the third story window of Dartmouth Hall. Like, why aren't you studying? It's because I already put a slight time for this. I just execute. I have my calendar. Let's rock and roll. I don't let my instincts and panic get me going. As you head towards research phase of grad school, postdoc into professorship, projects now matter too. So you still want to control your time, but projects matter. You want to select well. You don't want to select too many. Really good projects. This is a paper I should be working on.

And I'm saying no to the other stuff that's not this. I'm not going to be super popular among the people running the various social committees. I'm not going to organize this or that. I'm trying to work on the projects that matter, really high quality selections, not too many projects on my plate at the same time. So careful project selection, control over time. I think that's a theme that goes through almost all of my advice for execution. And it's like at the core of how I get by as well. So like those two things. I mean, I'll say, I don't like always admitting this because postdocs get mad at me. You can tell me, Brian, if you think this is crazy. When I was a postdoc and I was preparing to be a professor, I artificially took two and a half hours out of my day.

middle of the day and said no working because I knew I would have roughly two and a half more hours per day of responsibilities as a professor and I wanted to start practicing for that. So I was like, I want to practice as a postdoc where I don't have much to do, making sure my research can, I can get it done efficiently. So I took this big chunk of time in the middle of the day. I was at MIT at the time. I'd bring my dog to campus. In the middle of the day, we'd go for a long run on the Charles and then I would have lunch and then I would walk back across the Longfellow Bridge. We were up and Beacon Hill back to the, back to the campus, just so I could practice being more efficient. I didn't want my work to fill my whole postdoc.

I was an easy job. Professor is going to be harder. So I took artificial time out of my schedule just so I could get used to like making progress on research without having the luxury of I can work on this. It's peak pollination season and my business is scaling fast. To keep the nectar flowing, I need a phone plan with top priority data speeds. That's why I chose GoogleFi wireless. My connections stay strong even when the hive is buzzing.

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out of a car on their birthday. So, yeah, one of the things is, yeah, having this kind of imposed artificial scarcity or whatever reminds me of, you know, another kind of probably apocryphal rabbinic tale where this guy goes to his rabbi. He's like, I'm going crazy. I've got all these kids. You know, my mother-in-law is living with us in the Stettel and, you know, Poland in 1822. I can't take it anymore.

And the rabbi says, okay, get a dog. What are he talking about it? All right. He gets a dog, comes back to the rabbit. It's even worse, Rabbi, what the hell are you doing to me? You're ruining my life. Okay, I have one more piece of advice. Get some chickens.

Okay, okay, this is enough. This is, I'll do it only because you say that I should. Get some chickens. It's horrible. Life is awful. He says, what are you going to do next? Say, get a goat? Yep, get a goat.

He's about to blow his brains out and kill the rabbi. And the rabbi says, now get rid of the goat, the chickens and the dog, and see how good you feel. See how great you had it. So I think, you know, when I look at, you know, kind of these techniques and tools and tricks, I always feel like there's a tendency to get into that hacking, you know, stand. Like when we are, you know, trying to confront things because there's ambiguity. We don't know what a graduate school is going to be like. I think if I ask my undergraduates, what do you think graduate school is going to be like?

They're like really just a bit, just harder homework problems, you know. And it's totally of a different character. And so too with being a postdoc, except there's. basically infinite, you know, kind of flexibility. Post-Tac, I would say it was the best time in my life because I was able to, you know, get funding just magically appeared. I had graduate students at Caltech and had just the most wonderful time coming up with ideas. And luckily I had a wonderful advisor. It was very supportive of me. And then switching to to being an assistant professor, you're like, it's totally like every phase is completely shielded by an event horizon of ignorance

that you only, you actually, it's worse because you think you know what your professors do when you're an undergraduate and you have no idea what they're really doing. And so, you know, for all these different faith, and nobody taught me how to be a professor, how to be, how to teach. And so, you know, I've had to learn on the job. But what do you make of academia right now? I kind of joked about the Hunger Games, but I'm sort of serious. Like, I always say science is an infinite game. You cannot win science, right? But it's comprised of a hell of a lot of finite games. undergraduate, graduate school, postdoc, assistant professor, tenure, funding, all these different things, papers, referees. So it has all these finite games embedded with an infinite game. Again,

maximizing ambiguity because we're not used to situations like that. But when I think about being a professor, I almost feel like we're doing a disservice in academia because there's so many postdocs. I make it now, I know you love baseball, I love baseball too. I make the analogy, like getting a postdoc is is probably almost as hard as like triple a ball is you know like those guys are awesome like in terms of but it's as easy as getting on like a you know high school baseball team or you know the junior high like it's very easy to get postdocs for most people not fellowships those are extremely hard but to get a postdoc somewhere trivial i mean i had two you know but but but the point is um then you go from that which is um you know as you know is also you know a hard thing

to get into and AAA, and then you go into the major leagues. It's impossible. Like, we had 400 applications for one job yet last year. I'm sure it's the same as Georgetown. What do you think we're doing? Is this, are we setting people up for this false expectation? I'll just add one more tidbit. And our colleagues in medicine, you know, you and I are in that, or in the biological sciences, the first NIH grant, they get average age is 42. And by then you might have to be tenured or you might have to look for another job. So how do you advise? you know, your postdocs or students, how do you handle the inevitable rejection that they're likely to face? This is something that culture writ large doesn't understand about academia. So I'm sure you have this same

frustration after all of this intense competitiveness, right, to get here. And I think Major League Baseball is not a bad analogy, right? And you finally get there and then you hear other people talk about it like, oh, oh, you decided to teach. Yeah, I thought I thought about teaching, but like I had, after undergrad but I went another way. And you're like, do you realize the hunger game blood sport that we just survived? Do you realize that we got drafted by the Yankees and like put up a 300 bad in average and like made it on the 40 bad roster? It was so impossible. What do you mean you thought about teaching? And so that's it's a common frustration. I think baseball is a good analogy too, right? Because you have a huge numbers of minor league systems. You have other

professional leagues. You have the Japanese leagues. It's like people. They, know it's almost impossible, but they want to be near the show. And even if they can't make the show, they're sort of around it. That kind of is how academia is running now. So I guess the question is only, are we being transparent about it? I think it depends where you're coming from. Now, I don't know about your experience, but my experience in grad school is the whole thing was preparing you for the realities and what it would take to get through the academic pipeline. Like my, the sea sale, the computer science, artificial intelligence laboratory at MIT, their whole thing is how do you be a very successful professor?

To the point where when you're in that program, and again, this is something that's very different than the culture writ large. The idea of going to work for Google or Facebook is just considered like the biggest disappointment and failure. They're like, those are places that hire thousands of people. That's not fun.

You need the position. That's what you do when you fail. And we're going to teach you how to, we're going to teach you how to succeed. How do you publish at the right? Right, right. How do you publish really good papers? This is something I talk about. People think that's just a translation of brain power to results. No, no, no, no, you have to be around a culture of how do you actually harness your brain power and push through to a science paper. How do you push through to a top computer science paper? You have to be around people doing it. You know, Nobel Prize winning biologists produce Nobel Prize winning biologists because you're around, oh, I see what it takes. Like, this is different. It's like kids of professional athletes. They train at a level that like the, like, the average kid doesn't realize that's what it takes because their parents know. So I'm of two minds of it. I mean, I don't think it's bad that it's so competitive because what you get is that

competitiveness keeps people like you and I interested in the game. It keeps me from not just going and taking the paycheck at Google or whatever. That I think does help competitiveness. I mean, U.S. universities produce really cool ideas. And so it keeps people in the game. But I do worry, I think you're right. Does everyone know how competitive this is? Does everyone know, know, because I always get questions from this from students, like, I'm thinking about teaching. And I'm like, look, you have to be at a good school now as an undergraduate. You have to crush it, right? You have to be like, I'm one of the best students in my major. Then you have to go to a top grad school, because you can only go downhill, right? You can't go from a B grad school to an A school. You go from

an A grad school to a B school. It all goes downhill. You got to get into a top then grad program. And you got to really kill it in that really good grad program as well. And then you have to like postdoc with someone who's doing the type of work that people want, but they can't hire that guy because he already has a job, so they'll hire you to replicate what that person is doing. And then, and only then maybe, if you can beat out the other 300 people, you can get a spot. I'm always giving this lecture to students who are just casually thinking, should I go to law school or maybe I should teach. So we do need transparency.

But I don't know. What do you think, Brian? I mean, I think like it being as sciences, at least, math and sciences, being as competitive as it is, is probably the reason why. We are so cutting. I mean, we really produce a lot of the top new thinking in these elite institutions. Hey there. It's me again.

And I have an amazing offer for you very quickly, especially to my educational students, especially to those of you with a dot edu email address, you can win your very own, honest to goodness, four billion-year-old piece of space schmutz. Going to Brian Keating.com slash edu for education. And if you're in the U.S., I'll send you one of these bad boys. that flew all the way in and impacted some 15,000 years ago. And I'll send you information about where to see meteor showers. You'll enjoy it.

And if you don't have the opportunity or you don't have a .edu email address anymore, and never did, that's fine too. We love you all. Go to bryankating.com slash list, and you can sign up too. And there's a chance that you will be one of the lucky folks that I choose every month to send a meteorite to as well. So I hope you enjoyed it. Yeah, I mean, I always wanted to live the life of the mind.

I'd never thought I could get paid to do it to be a professional astronomer. or it was like, are you going to pay me to be an ice cream taster? Or, you know, here in SeaWorld, at SeaWorld San Diego, we're going to come back very close to there because San Diego plays a very prominent role in this book, as we'll get to. That's leaving a hidden jewel for the future. Cal got it. But you guys haven't gotten it yet because you haven't read the book because it's coming

today when you listen to it. Prepare to grown everyone, by the way. Yes, that's good. Well, we're two dads, so we got to do it, right? It's our dad jokes. It's a day rigour. I once took one of my sons to Sea World Field. trip and I got there 15 minutes early, good dad, and we were just sitting around and I always carry

a small telescope in my car because I'm an astronomer nerd and I want to be prepared for the total solar eclipse that was unpredictable. That would be very scary if that happened. So I have this telescope with me, a little tiny pocket thing and I look and I see the roller coasters going, you know, the mantas like killer, you know, triple loop to loops or whatever. And I look and there's a guy on it and he's in the front row and I zoom in on the telescope and I look at him and he's just like, this, Cal. He's going on like 9 G's. Yeah, uninterested. He's just, he's either got like, you know, ice water flowing through his veins or he's so jaded because he's done it so many times. Every day he does it. And it's like, you know, if you had to taste ice cream every day,

yeah, probably you'd get, you get tired of it. But I always thought this job was literally the best. I call it the hardest three hour a week job in the world. But of course, we know it's much more than that. And there's many more skills that aren't taught to us, never learn in a class. room, never learned from a mentor, all these kind of soft skills about networking. I find, I don't know if you agree with this, maybe let me know, but being a salesman. I mean, we sort of have to sell our ideas. And it sounds transactional and it sounds venal, but it's true. We have to be persuasive in our field to get the invitations, to get the speaking opportunities to present papers for our students to get our students the job unless you have a Nobel Prize. It's very challenging thing to do. And I think we never teach those skills. We also never learn the skills like we have to take these. annual sexual harassment training courses, right? I always tell them. I already know how to sexually harass people. I don't need the training. No, prevention. Okay, prevention. I got you. I got it. Or cybersecurity and all these things. And I just got so sick of it. And I'm thinking like, well, nobody really tells you as a professor, what do you do when, you know, your student comes to you

and she broke up with her boyfriend or he broke up with his boyfriend or girl? Like, how do you handle that because you almost become like a father figure. My PhD advisor, Peter Timby, past guest on the podcast, he came to my wedding. I helped babysit his kid. These are relationships that we have in academia that are far more durable. And they're also, I spend more time at work than I do with my kids. I mean, they're in school. So how do you, you know, teach those kind of very soft skills? I don't know if there's a guidebook or way to do it. Like I said, they just put me in front of 200, you know, physics, you know, majors and teach class. They never said, here's how you teach.

I wonder, does Georgetown have any other things? Or at Dartmouth where you were, by the way, do you know what the connection is between UCSD and Dartmouth, Cal? USCD, no, tell me. Okay. So at UCSD, we have the Geisel Library. Oh, there we go. In honor of theater Geisel, Dr. Seuss, who was a denizen of La Jolla before he passed away.

And his estate donated this money. And you guys at Dartmouth have the Dr. Seuss medical. schools. I love that. I talked to Marcella Gleiser last week, and I dropped that on them. But did you ever encounter at, you know, Dartmouth is such a spectacular school or at Georgetown, another top learning educational environment? Are there opportunities for at any level to learn salesmanship, but to learn teaching, persuasion, all the soft skills that us hard scientists need to know? There's resources if you want them. But what they really do, and this is not isolating any university. I think this is just like most universities. It's this weird sink or swim culture,

and maybe there's a logic to it where it's, okay, here's a classroom, here's an office. We'll check back in in five years. If you're doing really good at the classroom, and more importantly, if you've made a difference in your field, which by the way, we're going to assess, another thing not really well understood by people who asked like, why didn't your books, didn't that help you get tenure? I'm not going to mention my books in my tenure case, because we're going to get confidential letters from top scholars in your field and said, how good is their work? How good is their research? My chair told me, well, we won't actively punish you for writing a book. But we're not going to give you anything for doing. Any credit money, tabadical, nothing. Nothing. Yeah. And it doesn't help.

People don't understand why. Because I think they think about companies. Like, well, like the company is deciding whether to promote you and you have the, no, no, no. It's a hard edged, leading scholars in your field, knowing their writing in full confidentiality, pouring over your CVs. like I read this paper. This wasn't very good. This is actually good. Doing comparisons by we would not tenure him in our school, but he would be tenured at this school. Here's four other people of roughly his age who I think are comparable. Here's three who are better. It's a whole crazy system. But they say we'll check back in in five years. And if it all went well, like congratulations, you get tenure and you can end up being like a great force of pedagogy at

a university. And if it doesn't go well, well, we don't talk about it. You just sort of kind of quietly, quietly leave. So it is a weird It is a weird sinker swing. It's a guild. It's a cartel. It's all these things that they don't really teach about. And one of them is, as, you know, there's a famous quote from Isidore Arabi who won the Nobel Prize. Basically invented a precursor for nuclear magnetic resonance or MRI and among his many accomplishments.

But he said, they pay you to make money to do research. But if you're a gentleman, you also teach. And some of the most renowned teachers, you know, on kind of the public scale communicators, Feynman, great example, another MIT grad. Wonderful in sort of the abstract, like the Feynman lectures, classic. He has some productivity tips too. Maybe we'll get into those. But really, I've met many people who took classes with him.

He was one of the worst in-person teachers that they ever had. And actually, what would happen was all the freshmen would get, drop the course. And then it was populated by postdocs and faculty that would come to Caltech to hear as lectures. Yeah, the academic environment, it really is sink or swim. And I think you're right. And although the tenure rate is quite high, I mean, we invest a lot up front, you know, see if this person's worth hiring. And then we assume that they're going to do well. I actually don't know many people, maybe one person who didn't get tenure. Yeah, and I assume it's similar elsewhere. But yeah, this notion that you kind of learn on the job, but it's very high pressure.

Like they invest a lot of money in a startup. You know, our salaries were hired for life. effectively. It's almost like anything else. One of my colleagues said, you know, I'd rather get married to somebody than tenure them because at least you can get divorced. The thing for me, when I look at your career, which is, which is really remarkable, I wouldn't have thought. If you just told me, here's a, here are all these different character types. You know, here's a very, you know, a computer scientist who is very mathematical. And it's not, it's more in the theoretical computer science. I want to get into some of your work, but also has the writing abilities. Are you sort of self-taught in that regard? Is it just your autodidactic nature,

polymathematical nature? How did you come to be not just so eloquent and so, and such a wonderful engaging writer? I mean, your bestseller, multiple bestsells. What were some of your guides, mentors, inspirations, other authors? What can you, what can you give to the audience to let them have a little insight in how these completely, as C.P. Snow said, two cultures have come together in one melange of Cal Newport. How did that come to you? They both emerged in childhood. So, you know, I was a very precocious reader. And so I could write pretty well for my age. So at a young age at my elementary school, I had this benefit of being pulled into this gifted and talented reading program, not math, but the gifted

and talented reading program where we just wrote. All we did was just write long stories, mainly short stories. All we did was write. So I always could write. I read precociously. I could always write. And then I got really into computers. So, you know, as a child, I could, I was writing a lot. I was in these sort of advanced programs for writing. And I was really good with computers, right? That just came naturally to me. My mom, when I was, the first phase of my life was a computer programmer. So I knew what it meant the program of computer. And then I just learned a bunch of languages. And all that came, that came naturally to me. So I was doing computer. computers and I was doing writing. And then eventually computer science. There was an AP course I took early on. And then I grew up near Princeton and they had an agreement with my high school that said, hey, if you have a student that's sort of out of things to take, they can come here tuition free and take courses. So I took some Princeton computer science in high school. And so when I went off the college, I said, okay, what am I going to do? I said, I'm going to do computer science because I'm good at that. But I said, writing's too hard, so I'm not going to write enough of that.

And I rode crew instead. I was like, I'm going to do sports and it's fun. And I like the camaraderie. I was an athlete in doing computer science developed a congenital heart condition that took me off to crew team. You can't row with having to take beta blockers that reduce your heart rate. Like you can't, you know, you're just a 20% worse rower. And that's after that year, after my freshman year, I said, what am I going to do with all this time? And I said, oh, God, all right, I guess I'm going to go back to writing. And so I'm at Dartmouth and really doing well in computer science, you know, because I was a really naturally good computer science student. And I got more and more into writing. I was a calmness for the paper. Then I started writing for the humor

magazine. And then I became the editor-in-chief of the humor magazine. And then once I stepped down from that role, I said, why don't I write a book? So by the time I left Dartmouth to head off the MIT, I'd already finished the book. And I was about to start like a more serious computer science training. And so all of that was in place by the time I left college. And I was like, oh, these are the two things I'm going to do. I'm going to write and I'm going to do computer science. And it seemed clear to me. I wanted to do those two things, not one versus the other. And that was it.

And then I was off to the races. And it's all I've done for 20 years. I want to do computer science and I want to write. You know, I mean, that's it. That's what I don't want to start businesses. I don't want to do apps for the Apple Vision Pro like your friend suggested. This is what I want to do. So I came out of the gates with a vision of I want to be a ten-year faculty doing

theoretical computer science. I want to be a best-selling writer, write an idea books. Like, that's what I wanted to do. And it, you know, it took 10 or 15 years until I really got to that goal. But it just, from as long as I can remember, those were the two things I was doing. And it sounds like your parents probably played a not insignificant role and nurturing that. And you grew up, as you said, near it not so far from Princeton. That's kind of another nice advantage.

All right. So we let's dispense with the pleasantries. Okay. I want to get into the Aratum in this book, Cal, because James Altucher told me once, if you want to impress, this is podcaster's advice. So this is really talking shop now. He said, oftentimes you want your guest to know that you really engage with his or her book. And there's ideas.

So one that you could show how many highlights you've made in their book. I like it. I like it. The other way you can go through and you can read the acknowledgments because when you get the Kindle sample copy, you know, and most people just read that, it doesn't have the acknowledgments. The only way to read the acknowledgments is actually have gone through the book. But the best way is to point out. an error, a typo or something in the book. And there aren't typos in the book per se,

but there's a huge awful missed opportunity, Cal. And I want to bring that up to you in hopes that I will someday get a tiny little citation in the book in its 12th edition. Okay. So I'm going to show it right here. I'm going to read it, but I don't know if you remember this here. Okay, so you're talking about Fermat's last theorem. Oh, okay. Let's get technical. All right, I like it. Okay, Cal. So you're talking about, how Andy Wiles, who was at Princeton, and I met once when I was at Brown, proved this 400-year-long conjecture because of the tools that, you know, he applied the slow productivity tools presaging what's going to happen. But that's not the relevant thing. Cal, how could you?

How could you put that as a footnote instead of putting it in the margin? How could you put the equation from allegedly said, and you would know this better than me, but he allegedly said he has found this conjecture, but the margin is not big enough to include it. So, Cal, please consider that a recommendation, humble, not so humble for me. Hey, I would have done it if I could. I didn't have the ability to put things. Also, you and three other people would have got that reference. So that's just, my whole publishers, but half of their job is reminding me that like most people aren't academic nerds and that like normal people, half the way I talk, normal people don't talk that way and don't write that way. My New Yorker editors are constantly, especially when

I write about AI, are constantly saying people don't know what that is. People don't know what that is. Stuff that like you or I would be like, of course they know what it is. The latest one was the word vector. They're like, people don't know what a vector is. I mean they don't know what a vector is. I mean, it's an order sequence of numbers that could be interpreted as a series of orthogonal coordinates in a multidimensional space. What do you mean? Of course it is a one form. Come on. It transforms it complementary to a one form. You want me to get covariant here? in a more serious kind of one thing that I love is you you're so widely read so it's one thing to be a good writer not all good writers or you know readers but you bring up one of my favorite books

on the road by jack carouac and i had always believed this mythology that he was you know probably in a speedball induced you know haze driving across the country and that he penned it on a single sheet of you know a roll of paper and he did it in three weeks and you point that that's a total myth and And actually, it's very high quality. It's very well done. And it was written over two years. So that's not so surprising. You also mentioned Galileo.

I don't have my finger puppets here. But I have all these finger puppets from the Unemployed Philosopher's Guild, which really, they really, you guys really should sponsor the end to the Impossible podcast. Because I've got many different ones, ranging from Galileo to Einstein. And even one of my, one of my former guest, past guest on the podcast, has a finger puppet. And you may have encountered him at M. MIT, Noam Chomsky. He has been a guest.

He has a finger puppet. So when we get together, I'll give you one of those finger puppets. Maybe we'll get a Cal Newport finger puppet. Anyway, Galileo, as everybody knows on this podcast, has been the biggest hero scientifically for me. He's also an incredible author, rich prose, just delightful visionary metaphors, talking about things that one just beautiful essay at the end of the dialogue, which I had the honor of making the first ever audio book, 22 hours of stunning audio dialogue between me,

Carlo Rovelli, who's a renowned physicist, my friend Lucio Piccerillo, and also Frank Wilczak from MIT did the forward by Albert Einstein. He writes in such delightful prose about how he used these tools and these arguments, not to be the last word, so to speak, but to open a portal, as he said, such that generations from now with minds more perspicacious than mine will be able to peer further into them than I in my fallible ability have been able to do. Of course, he was being, he had a huge ego. But you point out that, you know, he, Galileo had the work on the pendulum and the timing of the pendulum. Remember back then, there were no clocks. The first clock wasn't invented really until the 17, 1800. So you could only be

slow. He could only have, but he had first started thinking about these things. Allegedly, as a child in church, he was bored during a sermon. And he put his resting his hands like this. And he saw there was a lantern swinging pendulously, not far away. And he counted that, no matter how big the amplitude was, the period was still the same. He didn't write that up for 20 years. Yeah. And you mentioned that. You mentioned Kepler's work, very similar stuff. Copernicus. So Copernicus has the church. tragic. He should have been a little faster, Cal, because he got the revolution, the most famous book where he comes up with the heliocentric model. He got that the day he died.

So it was like, it's not clear if he ever saw it in print in 1543. But there's one episode, which I think could have been very damaging. And I want to segue, this has happened to Galileo. And it's a very long meandering question. I'm breaking all the laws of podcasting. But Galileo, starting in 1610, actually in January 10th, 1610 observed for the first time in human history the moons of Jupiter. And he realized instantaneously this was a falsification, not a proof of heliocentrism, but it was a falsification of geocentrism. Because these stars, he called them, he named them after his funding agency, which is very clever, the Medici stars. He called them Medici star. Now, ironically, we call them the Galilean moons. So the Medici, the fours,

funding agencies lost to history. And he realized he was looking at a miniature solar system, he called it on edge. It's just brilliant. I would have said, well, there's a couple stars there. Tomorrow they were, but they kept following the planet and 80 pages of Sedarius Nunchius, the starry messenger is filled with these tables and plow. And so he tracked it for literally for 80 days. He made sketches of the moon. He made sketches of Saturn, which he incorrectly thought was a single planet with two giant moons for the rings. And he realized that if he could do this, he didn't invent the telescope. He improved it by a factor of 10 or so by getting better quality glass, stopping the aperture, which is a very counterintuitive. Why would I make the aperture

smaller? But that get rid of chromatic and sphere collaboration, incredible, just brilliant. He understood the math of it, how the optics were working. And then he rushed at the publication in March, March 13th of 1610. So he did actually write this book in three weeks or three to four weeks. And if he hadn't done it, it wasn't clear that he wouldn't have been scooped. Actually, there was a British astronomer the same day that he observed Galileo's moons. He also observed them. And he's lost to history because he was, he took this low productivity route.

So Kerouac, you're right? Total apocryphal. But in certain circumstances, do we not, especially in academia, My field, C&B, was Cosmic Microw Background, famous quote from Robert Dickie, also Princeton and MIT. He heard about Penzius and Wilson discovering it and said to my PhD advisor's advisor, boys, we've been scooped. How do you not let that anxiety, I'm what's called the scoop anxiety, that these other teams, if I don't, you know, if I paint the Sistine Chapel, no one else is going to do it. But if I don't measure the Higgs boson or gravitational waves from inflation, someone else is going to do it because I'm not the smartest person in the world. How do you defeat that anxiety that leads to rushed productivity?

It's true, especially in astronomy. It seems like simultaneous discovery is the rule. The big exception, I heard someone say this once. I forgot who said this. Maybe it was Neil deGrasse Tyson, maybe not. But they said the one exception in astronomy where there was just someone that no one was there. and no one was even in the universe of there was general relativity. Special relativity, people were there.

You know, okay, Einstein needed to publish that. No one was in the universe of general relativity. No one was dealing with non-uclidea geometry to try to measure space time and understanding these different. That's like the one exception of like, he could have taken as much time as he wanted because people were not going to get general relativity. It wasn't in the air. But let's zoom back out in Galileo. Right. So the reason why I talk about him and Brocket and Kepler and I talk about Newton and Marie Curie and some of these other figures from various time periods is their careers in general feel so much different than modern science careers that they had a lot going on that was unrelated to science. Galileo was he's poetic because he wrote poetry and was really good at the lute like instrumental music and he had all these interests that he sort of, they took their.

their time in some sense, right? Like, oh, I had this observation about the pendulum. He gets back to it at some point. Newton starts to build these ideas about the inverse square law. It takes 20 years before he really pulls it. So they take their time. And then when the time is right, yeah, they do then they publish. But it's like a few things, right? So yeah, Newton had to speed up because the Leibniz to publish to Principia. Galileo did have to publish quickly because he realized, okay, this telescope is getting around. I mean, he, I talked about it in the book. I don't know how much this I put in, but there was a guy with the telescope and he missed him. He's like, oh, I got to meet this guy. I've heard about this thing and he missed him and he spent months trying to track down.

Like, I need to get one of these things. What's going on here? And he eventually just built his own. So that was like in the air. So yeah, they do rush when they get that momentous discovery. But think about these great scientists. Most of them have like one or two great discoveries. And it's very different. I think the fast productivity approach is constantly be working and publishing, maybe in there, one of the things will be great, where the old method was wait for the great a little more. Expose yourself to things, follow threads, maybe you kind of let this one life fallow, you come back. They were measuring their productivity on the scale of lifetimes, not on seasons or careers. And partially is because they had this philosophical approach, especially these

Renaissance astronomers. They had a philosophical approach influenced by Aristotle, among others, that the process of being a thinker and contemplating the world, natural philosophy in general, was very worthy. So they found worth and just I'm contemplating and engaging and seeing evidence of God and the world and his beauty. And their whole life was meaningful. They were less focused on, you know, the Medici's were not saying,

Hey, Galileo, what's your, your H index is plateauing, right? It was just a different, it was a different feel. They published less, but the stuff they published was great. And they had pretty varied lives, way much more so than a stressed out, you know, assistant professor in the USCD, astronomy department, trying to hit their publication count and get their NSF grant. It just is a different pace. That's why I like those scientists stories. In terms of connection to computer science, outside of work, do you, I always say to my students, like, you should be working, you know, as a commandment. I'm not playing God, but you should really be obsessed with this.

Like, you should only go into grad school. I say this about book writing, too. I've only written four, three books now. I'm starting my fourth. So I'm halfway there, Cal to the Cal Newport level. But the point is, I tell them, A, don't go to grad school unless you can not go to grad school. And, you know, don't write a book unless you are the only person who can really write this book. Like, people, oh, you should write a book.

And it's like saying, oh, you should open a Chinese restaurant in, you know, in San Francisco. like no just because you're a good cook or you know it's it's not enough so what does that resonate with you a and b if it does what sort of extra like as a as an avocation you know do you have computer science interest do you play around with these chat bots as i do um what kind of computer science do you read turing's original books or how do you how do you approach it as a hobby in addition to being a vocation well i do have turing's dissertation on myself So yes, I guess to that. I have a whole riff on Turin.

I love Turin. I love him as a theoretician. And I think he gets, this is my 10 second version, though, because I was talking to Sam, and Sam had this interesting thought experiment. He's like, if you went back in time to kill, it's kind of a dark thought experiment, but if you killed one person from history with the goal of slowing down the development of the computer as much as possible, he was like, I wonder who would you go back and kill? And he's like, would it be Alan Turing?

And I think this is a popular, Turing gets too much credit for the development of the digital computer and not enough credit for his theoretical contributions, which most people don't understand. That's an aside, but you can already,

I'm kind of answering your question just by telling you that. Yes, I'm interested in all this. With this in mind, like an important shift I made is that when I was at college, being a computer science guy in high school and in junior high meant basically

I could program in 90, it was programming, right? I could program. lots of stuff and that's kind of what it was. I could program in a dozen languages. It was like programming. I'm in college doing, you know, you do research. Another thing I always tell undergraduates,

you want to be a professor one day. You better be doing and publishing work as an undergrad. Like you got to get started. So I was doing this. And it was systems work. It was with a wireless networking group, not theory. Systems work, right? I was never seen as a math guy.

I only went up to like AB calculus in high school. I was like, I'm not great at math with the like CTI talent search where you take the SATs early and that you can go to those camps. I was only invited for the creative writing one, not for the math one. And so I was never a math guy. Like there are some intimations like I got the highest grade and discrete math in college. And they were like, how did you get that? Because we had these Russians that studied this in high school. I had some intimations.

I might have some skill there. But anyways, I didn't want to be a systems person. I didn't think I could find an advocation as a computer scientist building systems and programming. it didn't sing, right? It didn't make my heart sing. I was like, if I want to just build things, I might as well to start a company. But growing up, I had always, because this came to my dad, we had always idolized Feynman. We had idolized von Neumann, the Manhattan Project. This, this idea of people at the Institute for Advanced Study, you know, we lived near there at Princeton, just staring

at blackboards and solving equations. This was something that I always had a deep feeling towards. And it's like, that feels like an advocate, like an avocation, math and theory. Like that just feels the distillation of the human cognitive experience. The problem was, I was not a theoretician. I was doing systems research. So I'd get in the grad school and the way it works at MIT is basically professors who might be interested in you working for their research group invite you to come interview with them.

And they're all systems professors. Like, yeah, come, you know, you're a systems guy. there was one theory professor and she was like, I need a systems guy who knows about wireless networks because we're writing these theory papers about wireless stuff. We need someone to build simulations and stuff.

And I was like, this is my way in. And so I tricked my way into that group. Like, yeah, I'll do that for you. And then almost immediately started writing theory papers. And so, like, I tricked my way into being a theoretician because I knew that's something I was, I touring, Feynman. Like, I really admired the astrophysicist

of the war period. I really admired. or the applied mathematicians that came out. I just wanted to do that. And it was really cool. And at MIT, the theory group where I trained, it was just all whiteboards.

Just like whiteboards, they were freestanding whiteboards, and people just stood there. It was like everything I wanted. So, advocacy matters. Like having that sense of, this is so cool what we're doing,

was really necessary. I think in academia, I'm sure you had the same way in astronomy. If you don't have that, it can become really cynical, you know, and really people, really burn out. But people love theory. And I loved it. And I never looked back. And I'm really glad. I mean,

I was completely mentally outclassed. Right. Because the people who were real theoreticians were moving stuff with their, you know, they could look at a fork and move it across the table with their brain. I mean, you want to feel dumb. Hang out at the theory group at MIT. I mean, I was out class, but I was just so happy to be there. I was like, this is so awesome. Look at, look at this. Like, there's Eric DeMaine. He became a professor at 19. And he's there like staring at a whiteboard for four hours. Like, this is the coolest thing. When I was a postdoc at Caltech, I would have undergraduates, you know, that would be assisting in the lab. You know, we're cooling down something over the weekend and it needed liquid nitrogen poured in and vacuum

checked at, you know, 2 am. on a Saturday or whatever. And I'd say, you know, it's too bad I have to come back and do it. And they're like, oh, I'll do it. I'm like, aren't you, you know, going out with your buddies, you know, on Saturday nights? No, I just have some programming. I have to catch up on. So I'll be up at two in the morning. It's just incredible. These people, yeah, the horsepower. of the average undergraduate, you know, puts many of my faculty colleagues, I'm sure to shame. So, yeah, when we're looking at, you know, kind of this, this very abstract notion and the passion that comes with it, I think, you know, a lot of people are, it's hard in the beginning. It's easier to do quantity than quality. And you make this, this notion very clear

throughout the book, focus on quality. But you also mention, have diverse interest, you know, kind of become a cinephile or, you know, whatever, take up crocheting or who knows, but, but you need to have interest outside of it. Why is that important? Why do you feel that, you know, having completely orthogonal, um, interest in pursuits that that will benefit, forget about students for maybe a second, but, but in terms of the average person, knowledge worker, that that's going to benefit them? I mean, isn't it enough to be a parent and and a knowledge worker and, you know, working in the, in the underground sugar caves on the Zoom Apocalypse lips is, isn't that enough?

Now we need to assign another hobby. So what is that advice based upon? Well, where the cinephile advice comes up, for example, is in the principle about quality, obsessing over the quality of what you do, which turns out to be the glue you need for the other two ideas to work. So the other two ideas are do fewer things, work at a natural pace. If you don't also obsess over the quality of what you're doing, that doesn't work. Right.

If it's just I want to do less stuff and not work, not work all the time, but you're not marrying that with I want to do what I do best even better. You can just grow a sort of resentment towards your work. So in that chapter, I'm looking at, okay, how do we become better at things? Because when you become better, like a couple things happen. One, slowness becomes necessary. You're like, as I get better and better at this thing and really care about it, I now see all this other junk is getting in the way. Like, how do I clear this out? So it's like Andy Wiles, it's a Fermat Last Theorem example.

I talked about how he so carefully cleaned up his schedule once he realized that he had a shot at the Tanayakashamorich conjecture and from there being able to actually establish as a corollary Fermat's theorem and how he very carefully began removing things from his life and how he took existing work and trickled it out so that people want to think he stopped publishing. Because when you have something you're trying to do really well, it demands. man's slowness. And then at the same time, as you get better at something, you get more ability to go slow. Andy Wiles does not worry anymore. At Princeton, I guess he got hired away, but at Princeton, he didn't worry about needing to impress people after he solved that theorem. So it also gives you autonomy. So anyways, how do you do things really well? One contrarian idea is appreciate something that's really high quality that's not your field. That's why I had to become a in a file in the book because I'm really into movies.

I became more recently more into movies. And I found that really helped me become more ambitious in my writing. It's hard when you're studying the best people in your field because there's a lot of other complicated emotions to come with that, right? It's too close to home. But if you study something adjacent, I'm inspired. Look at these directors. They have this artistic vision.

I should have more vision. I should take more creative chances. It's a jolt of, it's a jolt of inspiration and refinement of your taste. when you can just study high quality output in a field that's not your own. And it's not, oh, my God, that guy's better than me. And why don't I da-da-da-da. And so I write about it.

Studying movies has increased my ambition as a writer in a way that, like, I have a hard time reading other writers in my genre. It's just too close to home. I'm exhausted by it. So there's a reason to do. Your summer starts now with Memorial Day deals at the Home Depot. It's time to fire up summer cookouts

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You talk in the book about the virtue of having a five-year plan. I always say to my students, you could tell me your five-year plan, but I'm not going to believe it. You know, if I go back to that age group and maybe it gets more solidified, you know, right now my five-year plan is probably much more predictable and legitimate. But why is that a key core? Is it because of this, you know, kind of focusing and narrowing, you know, zooming in the telescope on what you hope to accomplish and therefore you can do it more productively?

And then a subsequent question is what's on your five-year plan? Yeah, well, I mean, this comes from the work at a number, natural pace principle. Because one of the big ideas here is take longer. Along with that, it zoom out the scale at which you assess your productivity. So that goes back to our discussion of the great Renaissance scientist. Very productive people in a sense if we look back and say they change our understanding of the universe. Zoom into a particular Tuesday in Galileo's life. And you're like, you're playing the loot. Like how unproductive you are, right? You don't worry as much about every day has to somehow like maintain some maximum. This is this factory mindset of like

we need to make sure we have 100% output through our shifts every day. That becomes less relevant when you're saying, yeah, what do I want to do in the next five years? Like I want to write a really good book, you know, and maybe have like a couple of papers that really hit home. And as long as you feel like you're making progress on that, on that scale, you don't really worry so much that on Tuesday, it's a sunny day. And you're like, yeah, I'm, I'm going to go hike in the woods. So when you expand your scale at which you measure productivity, it's why the opening story in the book, for example, to use a non-academic example, was John McPhee. And I opened on a story of John McPhee in the 60s working on a New Yorker piece. And he spent an entire week laying on a

table in his backyard, just trying to figure out, like, how am I going to get into this piece? And by the way, now that I've been a New Yorker writer for the last five years, I totally get it. It's impossible to start New Yorker articles. It's really hard. So I understand. I understand. But my argument was, is like, if you were hanging out in Princeton at his house in that week, you would say this guy is lazy. Like, certainly not a productive person. He's laying on a table. But I said you zoom back out. He's one of the most productive influential writers of his generation and the generations that followed, many of whom from those generations he actually trained.

And so when you scale out your definition of productivity, the day to day becomes less of this factory mindset of, oh, my God, why was I not working at three today? need to be doing things. That's pseudo productivity thinking. So that's why I say I have a five-year plan. Now, here's the hard part. You've got to make progress on that plan, right? And a lot of people are like, I don't trust myself. All I trust myself to do is the sort of whip the buggy whip every day and just try to be as busy as possible. And like to that, my answer is you got to learn how to do it. This is the skill. You have to learn how to make progress on big projects over a long period of time that's going to have ups and downs and intensity, how to keep coming back to it, how to know what matters and pursue what matters. Yeah, that's hard. But don't just give up on it. I don't, I don't

accept when people say, I just don't trust myself. I would just procrastinate. I was like, no, it's just hard. You don't want to do it. But I'm telling you, this is what it is. This is what it is to be slowly productive, to produce great stuff and leave a legacy without burning out is you have to be comfortable. I'm working on something over the next few years. This week, I'm doing nothing on it. And yet I believe that I'm not going to abandon it because I can do it. It's important. And I have discipline and I'm going to come back to it and I review it every week and it's kind of the crux of the matter to some degree is let's not let ourselves off the hook and say I can't do anything unless it's right in front of me and trust ourselves more trust ourselves to actually produce

some bigger timescales. So I promised the audience early on I planted the seed the foreshadowing of the cliffhanger that I'd come back to San Diego and we discussed Jewel who appears in the book, also in the context of quality over, over quantity. And I wonder if you could, you know, kind of delve into that. It wasn't, it wasn't immediately obvious to me, although after I read it, it was very interesting. She's, she's interesting in fact, because she turns down a million dollar, you know, contract or she's living in a, in a car outside of a taqueria, you know, down here on the beach. What about her story is pertinent or relatable to members of the audience? again, you know, mostly academics, a lot of academics, but not all. So yeah, what, what was it

about Jules' story that was so, so, so pertinent for you? Yeah, well, she also showed up in the obsess over quality chapter. And I love her story. Her memoir is fantastic, by the way. Also, the Joe Rogan interview she did is just mind-blowing. It's like the most interesting three hours. You got to listen to that and read the book. But yeah, the headline that I then deconstructed was this idea that she was homeless. and turned down a million dollar record deal. So I was like, all right, let's work back from that and see what's going on. So she was living out of her car, began playing at the interchange coffee house in San Diego, and was really good.

And she was good because she spent her entire childhood performing. Her family was a performing troupe. And she just, she spent her entire childhood performing all over Alaska. She's from Alaska, which is why I assume as soon as she could, she moved to sunny San Diego. But she was a yodler, among other things. So she had really interesting vocal control as well. Interesting story. Interesting story.

But anyway, she's living out of her car, starts doing these epic performances at the San Diego coffee house, and it gains attention. And it's this exponential growth thing. There's two people, then there's four people, and then there's eight people. And then soon, like, the record executives come, and like, okay, we want to give you a million dollars.

And she says no. But the reason why she said no is she realized, and she actually got a book out of the library, it was called something like, how the record industry works. And she realized, wait a second, this million dollars, it's like with books, it's an advance against royalties. It's an advance.

Yeah. And so someone say, yeah, but you got to keep your advance, right? Even if you don't make it back, you know, you get to keep it. So why not just take the money? But she thought about it. And she said, well, here's the thing. If I take that million dollar advance, for them to not see me as a disappointment, I'm going to have a hit record like right away.

And if I don't, they're going to cut their losses. And yeah, I'll have the million dollars, but that'll be it. And I want a long career as a musician. So she turned it down and instead very cleverly, remember this is someone who's, you know, living out of their car, no college education, very cleverly says, oh, no, I don't want the money. But how about we make my back in bigger? And they're like, okay, fine, whatever. This is like a small deal. So she had a bigger back.

And by the way, she ended up earning well over $200 million to her career to date. So this worked out pretty well. So the car she sleeps in now is a Bentley. It's a nicer car. That's what she did. Yeah, she sleeps in a nicer car. Yeah. So anyway, she did that because what she realized is I need more time to get better.

And they're not going to care. If they didn't pay any money, they are going to give me the time it takes to experiment and figure out how do I really do this well. And she really did need that time. So she recorded her first album out on Neil Young's ranch and with the stray Gators. But she was nervous. And she'd never played with a band before. and it showed, and the album wasn't doing well, but she just kept touring,

and she was doing a lot of college shows, and was trying to get her sound better, and she got more confidence, and no tour bus, no tour manager, she wanted to be as cheap as possible. The record label just ignored her, like, whatever. She's not costing us any money. It's not like a big deal.

And it was like a couple years later, she finally found her groove, re-recorded, you were meant for me, this time with Flea, actually, from the Red Hot Chili Peppers, who she knew from the San Diego, and some other. and there was a more confident version

and she was better at it. And it took often. And it was, okay, now she's found what she was going to do. And she had this cool quote about it. It was a quote from her grandmother. Hardwood grows slowly. And so she's like, I'm going to have to take my time

systematically getting better and experimenting and figuring out what works and what doesn't, doubling down on what's important, moving away from the things that's not helping me. And it took her years, but then when it came together because she was really, really good,

that record just exploded. It was selling like a million copies a month for a while or something crazy like that, right? I mean, she made a fortune. So that first phase of her career, I thought was really cool. And then the second phase, which I really also appreciate,

is that pretty soon after she became really big, did a couple tours and said, I don't want to, this is stressful. Like, I don't want to tour. I have plenty of money. I like music. I'm done with touring. And she just stopped and said,

I'm just going to release albums. I have enough money. So she took her time getting good. She took the slow route to getting good. And then once she was good, she used that for leverage to say, I'm going to control what I want my life to be like. And no, I don't want to be Taylor Swift. I don't want to be constantly touring the country,

just like the always like chasing the next highest number. She's like, I have plenty of money. I like music. I'm going to go to my boyfriend as a ranch in Texas. Let's just go chill there. You know, let's write some songs. And so it's this great example of the slow pursuit of quality and then the confident application of skill once you have it to take control over what your life is like.

Taylor Swift recently was the victim of a deep fake. And I figured, you know, who better to talk to about this than Taylor Swift. No, to talk to you about kind of the AI apocalypse and get your notions of it. You write mainly about graph theory. We're going to get into, you know, whether or not the, it is true that a K message can be broadcast in order. or N plus K to the three power, if that's really true, if it's K to the two-thirds part. We're getting to that. I know the audience is likely to be interested in that, as is Jewel and Taylor Swift.

But we'll save that, again, more foreshadow. Talk about AI. I keep saying to people that I am an AI optimist. I think going out on a limb, just like my bold Super Bowl prediction, I think it would almost only be a positive thing. I think it's already been incredibly positive. I think, you know, there's an old adage in Silicon Valley, you know, pessimists get to sound smart, but optimists make all the money. And we hear a lot about this from everybody from,

you know, Sunder Pichai to to Sam Altman, to Elon Musk and Stephen Wolfram and others. But I like to point out the following factoid. Albert Einstein, renowned for slow productivity in a lot of ways. He, you know, he really didn't write a paper in depth after 1917. That was, you know, really as well received as any of, you know, within a factor of a logarithm of those citations for say. The EPR one was, was a big paper, but he was put his first author, you know, to kind of sizzle cells the stake, right? So Einstein said the following. He said the happiest thought of my life was that an observer in free fall would experience no gravitational field. Now, why the hell am I bringing that up other than to quote my second favorite physicist,

you know, who wrote the forward to Galileo's book of the dialogue? as I said in the English translation. I say this for two reasons. One, I want to get your kind of input, your take on whether or not it's possible for a computer to experience a visceral sensation like freefall. And as you know, your former colleague at MIT, Norm Chomsky, thinks a lot of computation and actually thought is limited because of its lack of embodiment. Language, generative grammar, I'm talking to you, I'm using my hands.

just because I'm a New York Jew, it's because natural nonverbal communications component. Anyway, so A, can a computer experience or visualize a thought experiment, a Godanken experiment, of free fall? And B, to what extent could it have, like Einstein, a happiest thought, to cement and reify that notion of, wow, I'm onto something, which would later become the Einstein equivalence principle. That's why I'm an AI optimist. I don't think either one of those things is possible, but you're a million times more educated on this subject. What do you feel about AI? Is it really likely to provide net benefit?

Is it something we should be scared about? How are you using it? If you would. Yeah, it's something I've thought a lot about. I did a big article last year for the New Yorker, just trying to explain how a large language model works in terms that a New Yorker reader could understand. And then after that, I did a lot of speaking on that,

a few Senate briefings, for example, and a bunch of other types of talks. And I've kind of been in the thick of it. I'm actually in the middle of another really big piece right now while we're talking. So who knows, maybe that'll be out when it comes out. So I have a few thoughts on AI. I think it's super important.

And I'll preface it by saying, here's the hard thing about AI discourse right now is there's two separate camps that unrelated to the optimist pessimist estimate camp. I mean, it maps to it, but it's not by default. There's the, I call it the algorithmic online discourse. And by algorithmic online discourse, I mean, you get a lot of this on YouTube, you get a lot of this in some of the podcast spheres where there's just a benefit to boldness in what you're saying. And a lot of, there's an overlap in this world to the crypto hype as well.

So there's a whole online ecosystem of my YouTube video gets more views, the more I'm saying, this is crazy, what's happening. Oh, my God, because that's a very compelling storyline. And it's a very cynical world because it's algorithm driven. I want a recommendation algorithm to recommend it. On the other side, you have the computer science community. It's a much more complicated take because it's very complicated technology. It's much more nuanced take on what's happening over there, not nearly as hyped as that one. In the middle, you have journalists and podcasters.

And I think what's happening is it's this weird tug-a-war between those worlds, and they don't really know how to deal with it. And so I do think there's a lot of confusion in the coverage because there's not some clear thing. But I think the the hype world is colliding with the computer science world and they're colliding with each other. And people in the middle are like, I don't know where to think about this. And am I just a pessimist or am I going to, you know, like, Rogan has just adopted more of a mindset of like, I just like this is going to change everything. And it's because he likes that. He kind of likes the extreme of, you know, this is, yes, it's more powerful than you think and it's going to be this big thing. Everyone's being pulled in between, right?

So it's a complicated story. So what do I think that's going on? Here's what I think is important. Large language models, which is what powers the chat GPT variants, and what powers Claude and the other major chat type agents right now. Those are a very specific architecture. Those are not by themselves ever going to give you something like a machine that can think or feel or have consciousness or plan.

or do anything, it's something that we would imagine, like a flexible human style cognition. Architecturally, it's impossible. It understands language. It produces language. And we can get into sort of how it does it. So I'm pessimistic on this idea that, hey, we're just going to buy GPT7, realize we accidentally created Howl 9,000. Impossible. The architecture makes it impossible.

By the way, you know that that is the origin of the word podcast? Oh, from the Pod Bay doors? Yep. Yeah. Yeah, so Steve Jobs, the engineer who came up at the iPod pitched it to Steve Jobs, he had the notion that we should call it the iPod. And then from that came the word podcast. And that's why in my other studio, I have opened the pod bay doors behind me in a beautiful neon sign. Anyway, that's just an aside.

I love, but that's a good. I had this analogy. It'll probably get cut. But in the article I'm working on now, Hal 9,000 did not open the pod bay doors because it knew what Dave was trying. to do and was like, okay, this is not the mission objective and I'm going to prevent, I'm going to try to like kill a human. Chat TPT will open the pod bay doors for you. Why?

Because it's a static feed forward architecture that can't simulate the future. It can't look ahead and look for consequences for novel situations. It can only move matrices of numbers forward through a collection of transformers and neural networks in the end coming out with a distribution of probabilities on token selection. There's no interactivity. There's no malleable memory. there's nothing, no ability to actually interrogate a situation and evaluate possibilities. It's why large language models hallucinate because they don't have a notion of self-evaluation.

They have a notion of this, yeah, this token is a, I predict this token to be a rational extension of the input I was given. That's what they can do. It's a small Lawrence distance from another one in 20 to 9,000 dimensional space. Yes. And it turns out, like not to sell it short, is that when you expand the approach, parameter space to a trillion or beyond like we do with GPT4, it turns out you can have really complicated logics built into these mappings from internal representations of understanding to tokens. That mapping, like if we're going to be kind of like mathematical about, they're still static

mappings, but they can have intense logics in them, right? So you can have a ton of heuristics about what makes a good and bad chess play baked into a mapping that maps an internal representation of a chess board to a token that describes a new chess move. And so GPT4 then when it outputs a chess move when you describe a chess board for it, will probably output like a pretty reasonable move, not because like deep blue it's like playing out different scenarios. It can't do that. It's non-interactive and static.

But its mapping function can actually have, you know, a thousand different things that's looking at that got, that it abstracted emergently from its training. So it's pretty amazing what can happen. But it is all still static. So there's no interactive cognition or malleable state in a feed-forward network model. However, that doesn't mean, oh, we don't have to worry about it. Like how 9,000 is not coming because what is happening, we do know how to build systems that look ahead and plan and evaluate different possibilities.

We know how to build systems that can do that and keep in mind the psychology of other humans that are involved in the system that they're making plans for. This came out of game playing bots. And now there's a move for these two worlds to come together. That's going to be the future. If you want to keep an eye on anything, keep an eye on OpenAI's Q-Star Initiative, which is secret, but almost certainly it's trying to bring

the planning style reasoning engines that were innovated in game-playing bots, superhuman strength game-playing bots, into a world with language models. It's going to be this world of ensembles of models. That's where you could potentially end up with what you're talking about there. But you need ensembles of models.

Language models are so incredible at what they do that I think we've mistakenly assumed that they can therefore do everything. But Jan Lacoon, you know, the AI pioneer now at Meta, in December had a tweet that said, oh, auto-regressive large language models are a dead end. That's not a couple of years from now we're not going to be talking much about them. So the engineers who are working on this are like, yeah, this language models are great. And there's a lot of commercialization still to be done. like how do we hook this up to Microsoft Word and Excel and like make useful commercial products out of it.

But the researchers know the real excitement is other types of models that handle other types of cognition and figuring out how to connect them all together. If you're an up and coming AI doctoral student right now, you don't care about language models. You're probably, you're like a Noam Brown, someone I've been writing about recently who really, he wrote, he helped create the first bot to win at multiplayer Texas Holden Poker. he's the guy, by the way, that Open AI hired away for QSTAR. That's what you're doing. Like, what's the next type of model? So the way I summarize it is the road to an unsettling AI. Like, that's my definition is like, I'm unsettled by it.

I'd be unsettled turning it off. The road to that is longer than people think right now. They think it's going to be GPT six or seven. We're just going to discover. Yeah, right. Yeah, permanently. The singularity is near. Now it's nearer.

soon it's near it yeah four years from now so it's not that it's not open AI is like three iterations of GPT away from it but it's also not a blocked road I just think it's a longer curvier road than we expected so we have kind of more time in some sense on the other hand we are driving at a pretty steady clip so you know it's weird with AI stuff man it's like people blow certain things out of proportion because the algorithmic hype engine but there are these like longer term if you look at the research like okay we do need to think about it, both these things are going on at the same. So I don't mean to preach about a, I love the topic. I think it's fascinating. Yeah. No, well, yeah, if you'll come back on the

James Alltoucher schmooze with Brian Keating, I would definitely want to dig into that. James is also a chess master as well, which I know you are fascinating with as well. And it's natural for brandy act computer scientists to think about that. I actually came up saying with Sean Carroll, Chris and the Keating test, which is I took my Alexa and now I've set off, you know, 90,000 Alexas are in the world. I took it my Alexa. I changed the name of it to Hal. But then I said I made it plug into an Amazon smart plug. So it's power supply goes through an Amazon smart plug and it knows that. And so every now and then I'll ask it, you know, Hal, turn off the plug, turn off the smart plug. And the day that he doesn't do it, or it doesn't do it, then I am going to be aware

that the Keating test has been failed, and we are now into this new epoch. But in seriousness, I wonder how much we can do with pure, you know, either language or in other words, is there an opportunity to bring hardware, you know, it doesn't give the right answer. So can a computer feel pain? You know, and it brings up all these ethical issues that I know you've confronted at Georgetown as well. Maybe just speculate one or two minutes. If we got to this level of, you know, how like, you know, how 2000, 3,000, whatever, before our grandkids are full professors, you know, in the relatively near turn, what responsibilities would we have if a computer could feel pain, if we could do that? Do we have an ethical responsibility to, to behave in a way that,

you know, would comport with, you know, Jeremy Bentham or, you know, can they suffer? What level do we have as an obligation as their godlike programmers. And obviously this connects with a past guest on the show, Nick Bostrom, notions of the singularity and a simulation theory. Tell me, Cal, do we have an ethical obligation like a pet or, you know, a graduate student? What do we owe these creatures if, indeed, they will have some sort of coupling to the world beyond what they do now? I don't think we're ready to grapple with that yet. I mean, that's the, this is the answer coming out of the, Georgetown Center for Digital Ethics, of which I'm a founding member. If I can't get it from you, Cal, who the hell am I going to go to?

We don't, I don't think we don't have an answer yet because I don't think we understand enough what that's going to mean. I tend to be from the school of thought that thinks there's a, it could be a huge amount of complex obstacles to getting something like recognizable consciousness in a machine. and so few economic incentives to go towards those obstacles versus like what's happening now, which is like, let's make these language models bigger so that we can plug them into products and it's useful interface. I think that we'll call us the Newport principle, right? I think there's going to be an event horizon actually where the complexity curve goes up. We start to get some intimations of unsettling this and we sort of move to this direction. Why are we going this direction?

maybe that's going to be optimistic. But I do not believe that this is a quick jump development. I do not believe, just the one thing I do believe is we're not going to get from, we had chat GPT and we did another upgrade and oh my God, I realize this thing is alive. I think that road is like evolution, biological evolution. It's a longer road than I think we fear. I could be wrong about that, but that's the Newport principle. The unsettliness is going to become an unseptuous.

a governor that's going to then push back on the directions naturally that we're researching. But I might be, people think I'm too optimistic about that. I'm an optimist. I get a lot of pleasure from playing with these things. I've commissioned them to read my kids bedtime stories at night, which, you know, my wife, you know, throw the phone away when I do that. But I'm like, well, what's the difference between a book, you know, which is somebody else's, you know, fixed thing where I can have my son or daughter's name in there and they can go on a

magical adventure and it'll be tailored to, you know, what their friend, Susie said at school today. I don't feel any guilt about it. She's, she's more of a Luddite than I am. But, yeah, I mean, for me, it's been an incredible benefit. I've done, you know, many, many, you know, things. I have yet to really agentify it, you know, and turn it into something that can connect to the physical, not giving it my credit card and, you know, telling it to book a flight for me, you know, somewhere, but, or teach a class or whatever. But I have done things and I'd love to talk to you. Maybe we'll do this if you'd be so gracious to come back when I have this podcast with James. I see our profession. Maybe we'll end with three more questions, too, will be quick answers,

but this one will be maybe the last kind of fleshed out thing. Our profession is approximately 950 years old. The first professors were in the first modern Western University. It was in the University of Bologna in 1080. So we're coming up very rapidly on the 1,000th millennial that. And back then, Cal, it was very, you know, I remember hearing on deep thoughts, not, not deep, a deep work, but you remember Jack Handy had on sound of deep thought. He said, one of his things was, the very first fly swatters, Cal, were just like a stick with a big pad at the end of it. That's all they were. They were so primitive back then. Flies, of course, they haven't changed at all. But our profession hasn't changed at all. It's some guy or gal with a piece of rock, you know, scratching on another piece of rock, a blackboard and standing up the sage on the stage. I don't know how we survive COVID. You know, the Zoom apocalypse, that was on steroids. I never got such bad teaching reviews. I never felt more disgruntled, hating my profession. Luckily, it was only, you know, for one quarter for, for me, the way it turned out with my sabbatical. But, but anyway, Cal, aren't we not kind of living on

fumes of that we are living on the earnings of the dividends that this thousand-year-old, unchained stultified sclerotic profession that we have this pleasure of occupying. Do you see it lasting? Because it seems so vulnerable to disruption, you know, in the Silicon Valley lexicon. And yet it survived COVID. And it survived October 7th. And it survived the plagiarism scandal. It's not going away. So what do you see as the opportunities? We make Newport University, which may exist actually. But anyway, Newport University, what would it have? What would you put as mandatory curriculum of Newport University?

And where would you see the professor at playing that role? Well, I'll tell you this. I usually turn that argument around, right? If anything, I think it's the sort of the height almost of prokialism and, you know, narrow focus on the moment to feel like this mode of instruction has survived a thousand years. Why do we think what's happening today somehow is going to be the thing that breaks it? I mean, with the university education, I've been to University of Bologna. It's been there since, you know, 1,000, as you said. We think Zoom's going to break it.

What about the codex? I think we forgot the widespread appearance of printed books came out after the invention of the university. Shouldn't that have been the biggest disruption possible? Wait a second. I don't literally have to be within hearing distance of a. a person to understand their knowledge. I mean, couldn't you imagine you're in the 14th century and you're talking about like the university? Like, wait a second, if we're going to have like portable, a distilled and clarified version of this wisdom, why would we have to hear someone say it?

Right. So if the university system survived the codex, it feels like it's going to survive Zoom. So I sometimes turn it around because I never get that argument of like, well, it's been around for so long. Certainly that means it has to be out of digital. date and it's going to change. It could mean the exact opposite. The obvious, you know, back then, Cal, they had this barbaric practice that the students could go on strike. And then the professors wouldn't get paid. So thank God. Thank God. We've had some progress. We've had some progress. Yeah. Though I will say, let me ask you a quick astronomy question, because this is, and this ties back to AI and the future of the university. This I'm really fascinated in, this idea of one thing that AI might

do to change, let's say, astronomy or my type of field is, you know, a language models can't do math, really, except for heuristics they had built in. But with planning modules that can explore and simulate possible things, they're probably going to get very good at simplifying equations. This is like our bane of our existence, right? If you're a cosmologist, you're a theoretical computer scientist, you have your intuition, and then you have to grapple with the damn algebra that try to establish it. And it's like so frustrated. This is what slowed down Einstein with general relativity. People say, oh, it's a myth. He was bad at math, because of course he was much better at math, but he was bad at math as compared to like the top mathematical thinker

physicist at the time. He was a very good mathematician vis-a-vis a normal person, but it's sort of like, yeah. Yeah. So like I'm, I'm very good at math compared to the average person, but in the theoretical computer science worlds, I'm not as quick as a lot of the people. I didn't grow up, you know, in specialized math universities. So like this could be fair. Einstein could have got general relativity five years earlier. If he didn't have to go and, and, you know, learn all these new like okay i got to learn these new maths it's so complicated and it's taking me years and i have to get help and gross has to help me and i'm trying to understand these new whatever if you had an agent you're like okay well like simplify this can you is this equal to this like

how do you show me that i think for people who do applied mathematics in these various fields this actually could unlock a lot of creativity so this might be one of the bigger the internet was the last big change right like when i started grad school one of my advisors most important resources was this giant wall full of mail sorters with five printed papers of the 50th most important papers in the field. And it was a huge competitive advantage for her group that you could just go and get a copy of the landmark papers and build off of it. By the time I left grad school, of course, it's all digitized. That was a huge deal. I think mathematics on AI is going to be the next big deal. It's going to allow people like you or me to actually follow through in our intuitions faster.

more creative papers, more elaborate results produced easier. But none of these I think are going to break the model. I don't know why this model works so well. But the human species seems to like having academics gather in buildings and tell you what they're doing, just like religion hasn't really innovated much either in the past 4,000 years. You know, we sort of like the, there's certain modes of ritual and liturgy that seems to work for unlocking whatever that experience is. So I think that we have cool innovations coming, but I'm not this. big believer of like, well, we're going to be the ones to break the whole model. Yeah, I mean,

I agree with it on the research side. But of course, you know, as Robbie said, you know, at one level, we have to be gentlemen and we have to teach. I do feel like, you know, seeing some stuff that we have been playing around with and, you know, in kind of VR and augmented stuff at UCSD and computer science and even in anthropology, they're getting into this with avatars. You know, I always say, like, what's the most boring? What's the trope about the most boring aspect of physics that you remember physics one or high school physics cal what's like the bane of all beginning physics students you know existences what would you say that is oh god i should remember my physics oh man is this going to be like equation but like have you ever heard of the inclined plane yeah sure remember the

inclined plane like everyone just freaking hates that but if i told you i call this teaching the controversy and then and aping the uh you know intelligent design which i'm not going to get it to but um so galileo came up with that in his final book, which is written when he was imprisoned in Archetetri, Italy, where I've had the opportunity to host a workshop on relativity when he was the father of relativity, Galilean relativity. And this notion of he had this brilliant idea. Not only did he come up with the time, the pendulum and everything that you talk about in the book, 20 years hence, but he also realized that the reason you couldn't measure it with the

crude hourglasses that they had is because gravity is kind of fast on a human time scale, but he could slow down gravity by having an inclined plane reduce the force vector, and that would effectively allow it to be commensurate with the best measurement. So anyway, my point is, why learn that from Brian Keating? Why not learn that from Galileo? Why not have him sit there and say, actually, yeah, I remember I was in this part and you're touring around. It's just we experienced the Maslow's hierarchy of needs and pedagogies.

Like physical environment and also, you know, what's primacy of learning, what you learn first, you learn best, and then recency, the thing you most recently learned. But making it visceral, you know, you put them in this environment. There's the Pope. And now you've got to learn about this incline plane because this paper had to be published in Leiden because it was banned throughout all of you. Just bring it so much more visceral to the student. And that's why I wasn't, I agree with you 100% about research.

It's only been beneficial. I can even use it for teaching in that. I can take my textbook or my notes and put it into notebook LM and make a virtual TA and one of my students has done that. But, you know, eventually I wonder about the static model of just the stage on the stage. But we'll leave it there for now because I do want to, I do want to respect your time. It's been almost two hours, a lot of fun. But I have to ask you, by law, I have to ask you two questions of the final four, fantastic four, the quintessential quad of questions that I ask all my guests, but I'm going to ask you only two of them. One, sort of advice to your

former self. And I use this as a way of introducing maybe some of the people. on your audience that may not know about it. My podcast is called Into the Impossible. It's a quote from Arthur C. Clark. I'm the associate director of the Arthur C. Clark Center for Human Imagination at UCSD. And one of many of the quips that he has, including one of my favorites, I drop it on my department chair when he asked me. He said, for every expert, there's an equal and opposite expert.

That's always fun to lay on your colleagues when they're a little too egotistical. But he also said the only way of learning the limits of the possible is to go beyond. them into the impossible. Cala, I want to turn that around in the form of advice to the 20-year-old version of Cal Newport. What advice would you give that 20-year-old, you have 30 seconds with him, to give him the courage to do it as you've done, to go into the impossible? I wrote this. When I was graduating graduate school, I wrote an article where I reflected on exactly this question. What do I wish I had told myself when I intergraduate school? So I have a record of what I was thinking about this, at least at that time.

And what I said in this piece is like, why in the world, when I first started at grad school, why did I not go up to a senior student who was on the academic job market and sweating that whole thing and said, what are you discovering matters? Like, what is it that like matters here that you wish you had done more? Like, why did I not talk to someone on their way out? Because we have this tendency to write our own stories instead of actually confronting what's reality. And I, so I didn't realize this.

In grad school, for example, what I got wrong and what I would have told. myself to correct it is I thought like in research and what mattered I wanted to do in ideas that were interesting to me I was inventing a lot of my own problems and then solving them and I was like I'm gonna market these I'm a writer whatever and then I realized by the time I graduated no no no you need to write things that matter to other people which means you need to see what other people are working on spend more time reading other people's papers and make progress on them those are the superstars and it was like a really easy thing

Not to do, but to understand. And I never asked. I never asked. And so then I had this bigger general point. No matter what field you're in, the temptation is to write the story of what you want to matter. Because usually that story is going to be kind of challenging, but not too challenging and kind of fun. But what you need to do is confront the reality of what actually matters, talking to the people who were there before. And so I went through this whole exercise.

I was like, man, I would have been much more of a star on the market if I had done that. I never even thought to ask. Like, hey, what really matters? You could have had a good career, Cal. I know. It's all been downhill since then. You could have had a good career. You know, they asked Einstein to be the president of Israel, the second president.

Can you imagine what kind of a career he could have had, Cal? People would have known his name. They would have known his name. Yeah. When your biggest blunder is that you predict something, which later on will win multiple Nobel prizes because your actual biggest blunder was calling your blunder a blunder, that's when you know you've got a pretty powerful legacy to on Western culture. Anyway, Cal, last question.

Been so generous with your incredibly valuable deep time. Cal, I'd like to ask another question prompted by Sir Arthur C. Clark. He said the following. This doesn't apply to you the first part. An elderly scientist, very distinguished scientist, that does apply to you, says something as possible. He or she is very likely to be right. But if he or she says,

it's likely to be impossible, they're very much more probably to be wrong. Cal, I want to use that as a springboard to ask you the following question. What, if anything, have you been wrong about, changed your mind about, or would like a mulligan about in the grand intellectual sweep of your life? Or maybe even in your personal life. I'd be curious about that too. Oh, I've had a bunch of these. I'll give you a concrete example early on. My first two books were for students. So we talked about how to become a straight-day student, how to win a college. And the whole tone of these books was my whole conceit was write student books like business books. That was my whole conceit is that student books are too fluffy and they're trying to be cool.

And they don't understand the student market. And you should write, just be serious. Here's how to get great. Here's how to study. So I write these books. These books come out. You know, I give talks. Like, yeah, all that matters is study skills.

Like I remember being at some panels about student stress and the growing student suicide epidemic and being like, we just need to teach kids how to manage their time. They're stressed because they're not managing their time well. Those books come out. I'm at MIT. I start a blog to sort of like promote the books. And because of that, I start meeting real students in the Boston area.

And I say, great, here's what I'm going to do. I'm going to bring a bunch of you over to MIT. I'm going to mentor you. I'm going to teach you these ideas about how to study. All of your problems will be solved. I'll write about it.

People like, this is brilliant. You're brilliant. This is when I began to learn. Oh, my God, there's all of these other psychological aspects of student life. These students are completely stressed out. I had no understanding that there was this millennial student stress epidemic that

was happening in the 2000s. Like I didn't know about it because I didn't experience it. It wasn't on my radar. Completely missed it in my work. And this was much deeper than just their study skills were wrong because I was running the problems. There's this one student who I mentored and I wrote about her on the blog under a pseudonym where she was really stressed out. And I was like, okay, let's look at your schedule. We're going to time block it. And we're time blocking her scheduled, she had double major, seven clubs. It just didn't fit. I was like, look, it doesn't fit on here. Like, we're out of hours. Like, you got to quit stuff, right? And I remember this was such a turning point for me because she couldn't. She's like, I can't stop, I can't quit anything.

There's this deeper psychological thing. She had gotten into MIT. This was her identity. Her family was so proud of her. She didn't know what it meant to be outstanding at this, when, in this type of institution. The only lever she knew how to pull was quantity because, and so she she ended up basically having to leave for medical. She burnt out and she had to leave and take time off. And it kind of was a disaster for the rest of her career. And it was this big turning point for me. Oh, I completely missed the psychological aspect of achievement.

That it's not just technique. And it turned me completely around. And the third book I wrote was all about success in academic areas without stress. The motto of my blog and newsletter became do less, do better, know why. I invented these ideas like the Zen valedictorian and the romantic scholar to give a model for thriving in a student environment without stressing out. Completely missed it. Because my experience was I was really good at this stuff.

I was very organized. It kind of came easy to me. I wasn't very stressed out. I was naturally not an anxious guy. What's the problem? Everyone else, let's just do this. Let's go.

Completely missed it. Cal Newport is currently the Provost Distinguished Associate Professor of Computer Science at Georgetown University. It's also their Center for Digital Ethics Leader. He's a best-selling author of seven books. Let's just say eight books now. Come on, this is going to just crush it. I truly enjoyed this book.

I got it. Hard copy, soft copy audio version as well. You'll enjoy them all. They're really beautifully bound and printed. And, you know, Cal, I'm just so grateful to you for all your work. But, you know, when I get a new student or I have a, you know, someone struggling and a lot of times what we do is meta and you know meta professorship it's advice fatherly motherly avuncular advice i can give them this book so the highest incommium i can give you

is that this has been a useful tool for us you know fellow professors working in the sugar caves and it will be of great value your whole uvra but especially this most recent book congratulations cow this is amazing talk to you well thank you and i really enjoyed it and yes i think us in the academic world, don't tell everyone else, are going to get a lot more out of this book because, come on, this is the world I know best. And so there's going to be a lot of winks in here where you're like, oh, yes, a professor wrote this. Yeah, he gets us. So I was really happy to come on your show so we could talk shop and get into the academic weeds. It's a weird world we're in that your audience is in, but it's a cool world. So I'm glad to spend some time here today. It is. Thank you so much,

Cal. Have a great day. Thank you. Ambition comes in all shapes and sizes. At First Citizens Bank, We roll with your goals because we're built for what you're building. Fit for your ambition for citizens back.