From First Principles - 5,000-Year-Old Bacteria, Solar Storms, Dogs, and Meta’s AI War (EP. 32)
Episode Date: March 20, 2026Hosted by Lester Nare and Krishna Choudhary, this is our first standalone rundown episode — a faster, looser format where we hit several stories we didn’t have room to turn into full deep dives. T...his week: bacteria revived from a Romanian ice cave after 5,000 years, a speculative but fascinating theory linking solar storms to earthquakes, new evidence that dogs and humans share genetic roots for personality traits, and the increasingly dramatic fight over the future of AI after Yann LeCun leaves Meta to build a new billion-dollar company focused on world models.SummaryAncient bacteria, modern resistance — a microbe revived from a 5,000-year-old Romanian ice cave resists modern antibiotics and may even contain compounds useful against present-day superbugs.Solar storms and earthquakes? — a Kyoto University theoretical paper suggests space weather could perturb electric fields in Earth’s crust enough to influence faults already near critical stress.Dogs and humans, genetically — a Cambridge / Morris Animal Foundation study finds shared gene pathways that map to personality-like traits in both golden retrievers and humans.The Meta AI split — Yann LeCun leaves Meta to pursue AI systems that model the physical world, arguing that simple scaling of LLMs may never reach real general intelligence.Support the showDonate: FFPod.com/donateFollow: @FFPod (X / Instagram / TikTok / Facebook)Show NotesStory 1 — Ancient bacteria in Romanian ice cave (Frontiers in Microbiology)Story 2 — Solar storms and earthquakes (Kyoto University / International Journal of Plasma Environmental Science and Technology)Story 4 — Dog and human personality genes (PNAS)Story 5 — Yann LeCun leaves Meta / world-model AI (Wired)
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Frozen for 5,000 years, this Ice Cave bacterium
resists modern antibiotics,
which sounds a little bit scary.
It's very speculative,
but even the fact that the sun could affect earthquakes
is a very interesting.
That is, Jan Lacoon, who has recently left Facebook or meta in early 2026, and has now raised a billion dollars to build AI that understands the physical world.
Hello, Internet.
This is your captain speaking.
Lester Nare, joined as always by my co-host and our resident PhD Krishna Chowdery.
We are in our first standalone rundown episode.
We're going to cover several stories.
just at a high level, have a fun conversation.
These are stories we didn't get to to do a deep dive this week,
but we still want to talk about it
and get you guys into your weekend with some fun, exciting talking points
with a special segment in the middle,
which is going to be a surprise for our resident PhD.
Today we're going to cover microbiology on bacteria
that was found in frozen caves 5,000 years ago,
solar storms and earthquakes and how they may be related.
some of the shared genetic roots between us and dogs,
and we will wrap up with an AI story
about how the battle for control at meta-a-I
has now led to the start of a new billion-dollar AI company
coming at a different angle than large language models,
as we know it.
We will be learning about the science,
not quite from the ground up,
but at least from the top of the surface,
because this is from first principles.
Our first story for the rundown today is out of the Institute of Biology in Bucharest of the Romanian Academy,
and it was in the frontiers in microbiology.
Frozen for 5,000 years, this ice cave bacterium resists modern antibiotics,
which sounds a little bit scary.
Yeah, dude, this one was pretty weird.
There is a cave in Romania.
It is called the Skari Soara Cave.
Okay.
It's got this giant glacier that's about the size of 40 Olympic swimming pools.
And that glacier began to form about 13,000 years ago.
And what you can do is you can drill cores into that ice and then extract those samples.
And there's bacteria that are preserved in that ice.
And bacteria are notorious for surviving being frozen for thousands of years.
So we can bring back to life bacteria that have been frozen for thousands of years.
This particular sample is from the 5,000-year-old layer of that glacier.
They took it out.
They revived it, and they tested it on modern antibiotics.
They tested 28, and this bacteria was resistant to 10.
Not great.
Yeah.
It's really quite strange on the face of it.
Okay.
Because modern antibiotics are by definition modern, right?
So we've developed these, you know, antibacterial medication such that it kills bacteria.
And these bacteria that are 5,000 years old still have a kind of defense to stuff that we made today.
This is in line with a lot of the antibacterial like resistance that we're faced with as humanity, right?
We've been using antibiotics for hundreds of years now.
The first real big one was penicillin by Alexander Fleming before World's.
War I. And because we've been going at it, bacteria has evolved to fight against these antibiotics, right?
They've figured out ways to get around it. And the fact that 10 of these 28 did not work on bacteria
that were 5,000 years old, suggests that these bacteria were already resistant in the first place,
right? Okay, fine, 18 worked. But still, the 10 is kind of weird. Yeah, yeah, yeah. It's it kind of
dovetails with the story we just talked about as it relates to bringing back samples from
space.
Yeah.
And the concern that arises because we don't know what will happen.
Yeah.
If there happens to be, again, that's a little bit, this is real world.
We know that it's there.
Yeah.
We've tested it.
And they're basically pre, they have pre-immunity.
Like, they were never our current antibiotic.
They were never exposed to the current antibiotics.
And yet they're still already immune.
Right. It's quite weird.
I don't think we should be too worried about these glacial glacial bacteria because these are called psychro-bacteria, which means they're cold-loving.
They're not going to survive in the 98-90-degree Fahrenheit environment of the body.
Of the body, right?
But it's still quite a nice, you know, little problem in molecular biology that, like, how could this even happen?
And when you look at how bacteria actually evolve, they evolve together.
Bacteria are incredibly dynamic with their genomes.
They swap genes from one to another all the time.
That's actually how we transform bacteria.
A lot of times, you know, in an undergrad lab, if you want to like make a bacteria glow in the dark or something with a GFP,
which is this fluorescent molecule, what you can do is put in a plasmid, which is a circular piece of DNA that has the GFP code.
you put that in and then you heat shock the bacteria.
There's something that we've talked about a lot
where you just take the bacteria and you put it in hot water.
And then the bacteria kind of freak out and they're like,
what are we doing?
They ingest all sorts of DNA from their environment
and they try to transcribe that and see if that'll work.
So bacteria are swapping DNA between themselves and the environment all the time
and perhaps through the swapping you get this kind of drug resistance.
What's really cool about this story is that it actually,
the existence of this reveals
how antibiotic resistance evolves
naturally. So that's one thing.
The other thing is that this ancient strain
also showed the inability
so this ancient
strain showed the ability to
inhibit the growth of other
modern superbugs. So kind of like in
penicillin, when Alexander Fleming
discovered penicillin, it was because it was a natural
antibiotic that he had seen there was
a mold that was growing in his petri dish
and around that mold there was no bacteria.
And he was like, the mold is creating something that is killing the bacteria.
Well, in this case, this ancient strain is able to create compounds that will kill modern
superbugs, right?
So it possesses some kind of enzymatic gene that can hold existing biochemical potential,
right?
Existing pharmaceutical potential.
And so it tells us that maybe, like, we need to look at these kinds of natural places
at isolated populations of bacteria
to figure out how to beat
modern day superbugs that are now
resistant to our antibacterial
compounds, antibiotic compounds, but maybe
these guys have something
that we can use to defeat them.
You know, it's like that Thor,
I can't defeat you, but she can't
thing.
But the she can thing is like these
like 5,000-year-old bacteria.
Right.
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What's, um, there is a, we can look to the past, uh, to help inform us about how to fight in the present and in the future in a way that was maybe somewhat unexpected in that these bacteria that are 5,000 years old contains sort of an active ingredient.
Yeah.
That is relevant to sort of a pharmacological, pharmaceutical, pharmaceutical application today.
And, and historically most antibiotics are developed from bacteria and fungi.
that live in the soil.
I see.
And like they produce natural compounds
because over there, down there, it's like
D-Day every day, right?
It's just World War all the time. Everyone is
trying to eat everyone. And in recent
times, those pathogens that we found from
existing soil bacteria no longer work.
Well, we can, you know,
go back in time. Yeah. I think it's
a pretty cool
story at the heart of it.
And for, it gives a new meaning
to the phrase natural immunity.
Yeah. And
if we can scale up the same process that allows you to freeze bacteria and reanimate them
5,000 years later, maybe Walt Disney has a chance because if I recall correctly, he's currently
cryo-frozen somewhere deep underneath Burbank's headquarters.
Yes.
That is rumor, of course.
We don't know anything about it.
Don't know that to be true.
But this is, again, new research paper out of the Institute of Biology and Bucharest of the Romanian
Academy. It was in frontiers
in microbiology.
Fun little microbiology
story to get us started
on our rundown. Number two
on our rundown today
is can solar storms trigger
earthquakes? Yes.
And scientists propose a
surprising link. This is, was actually
covered by Science Daily.
It was out of Kyoto University.
And
there's a huge solar storm
monitoring community
on a variety of social media channels
every time there is a
I guess a coronal mass ejection
or similar
there's this like ranking system
that's like the Richter scale
and everyone's like this one is
over 9,000
hunkered down prepper
but there's a potential link here
to actually like geological activity
yeah and that one I was pretty surprised
that there is even a theoretical argument
that you can make here
and this is mostly a theoretical argument
this is a theoretical paper
what they're doing is showing a surprising
theoretical connection between space weather
and earthquakes, geological activity on Earth.
Now, how does that even...
What is the mechanism there, right?
Is what I always wonder.
So here's the idea.
Faults on the Earth are poised at a kind of
critical spot where there's a lot of stress on them
and they're ready to snap, okay?
Because they've been pushed to their brink
and like the faults on the earth are these, you know, plates on the earth's surface that are
contiguous blocks of the earth's crust that are moving around because magma underneath is
like flowing in a liquid motion. And so, you know, you move around just like how ice on a
frozen lake sort of moves around based on currents underneath. So why would, why would that
be affected by solar activity is the idea? Well, solar activity is the idea. Well, solar activity is effectively a
bunch of charged particles coming at us. That's effectively what it is, right? There's a bunch of
electrons, let's say, that come at us, and those electrons are going to create a massive change
in the ionosphere. The ionosphere being the outside ions around the Earth's atmosphere that are
built by the magnetic field that sort of, you know, shield us from space weather. Now, that ionosphere
is going to get changed up a lot because of, you know, shield us from space weather. Now, that ionosphere is going to get
changed up a lot because there's going to be a huge influx of charged particles from the sun.
That's going to change the electric field on the earth. The earth's crust, on the other hand,
has all of these plates that are sort of at this critical point. And in between all these plates,
inside the earth's crust, there's a lot of water that is in a supercritical state because it's
under high pressure, it's under high stress. And that water has a bunch of ions. So the electric
field on the outside is going to move around the electric field inside these.
cracks in the earth's crust, and that could potentially create enough of a force to actually
snap and create high earthquakes, you know, high damage earthquakes.
The idea is that there is these fields that are all around us all the time and interacting
have impacts in the physical nature in which we see and we interact, the tangible things we can
touch and feel.
and at the scale of the sun
and the scale of these solar storms,
the amount of the change in fields
in the ionosphere can potentially have a subsequent impact
on plate tectonics and how they move,
which again, big enough solar storm means
it would not only trigger things like frying electronics
and all that other stuff,
but could actually physically impact the Earth.
The Earth itself.
Yeah, and there's like weak correlation
between solar activity and geological activity.
If you go to 2.5, there's a weak correlation that was out in scientific reports,
nature scientific reports in 2020.
Again, it's not that big, and this paper is not claiming,
this current paper out in 2026 is not claiming that, you know,
solar flares directly cause all quakes.
But the research provides this, like, kind of new mechanism to explain
maybe unusual ionospheric activity and that connection.
with major quakes because in
2024 there was the Nodo Peninsula quake
and that was
preceded by a really large solar storm
and so there's these coincident
sort of we don't have enough data
to like you know the Sigma isn't down
to five but
it's there and this is exploring
some of the mechanisms I think that's
I think that was like pretty cool
it's very speculative
but even even the fact that the sun could affect
earthquakes is a very interesting
That is. And I think the plot of a future upcoming Jerry Bruckheimer produced a disaster movie.
Jerry, if you want a scientific advisor, I think I know someone I can suggest.
I've done it before.
Great. So this is, again, out of Kyoto University, which is fine. I mean, not funny. It's interesting.
Obviously, Japan has had very dramatic earthquakes.
Yeah. If we think of Fukushima, et cetera.
Yeah. So they have a very concerted effort to try to figure it out.
and this was in the International Journal of Plasma Environmental Science and Technology.
Yes, yes, makes sense.
This is going to be fun.
All right, here we go.
And we're going to try this.
And if it doesn't work, you're not going to hear this on the final episode.
But we are going to start a new game show segment called Are You Smarter Than a Scientist?
Welcome, ladies and gentlemen, with our resident Ph.D.
Krishna Chowdery.
who will be our scientist of the day.
And we will have one question,
family feud style for you to answer.
And today's segment question,
are you smarter than a scientist,
is can you name the 10 most abundant elements
in the human body?
We have 10 on this list.
Okay.
All right.
Okay.
So I'm not sure when you mean abundant,
if you mean by number or by mass.
So let's test it out.
and start with hydrogen.
Okay.
So we have you on the board with hydrogen.
Okay.
So hydrogen is number three,
which means that you are going for by mass and not by number.
Maybe.
So let's go with oxygen.
That should be number one.
Is it number one?
Ladies and gentlemen and...
Yes.
Oxygen is number one.
70% of the body is H2O, so that tracks.
Okay.
Let's go with carbon.
Okay, carbon. Is carbon on the board?
Got the top three.
Okay, and then nitrogen. That should round up four.
Okay, so you think that nitrogen is going to be number four?
Is nitrogen number four? You are on a roll. We have our top four.
Okay, so we got our top four. All right.
That was the easy stuff. I expected you to get that.
Yeah, so now let's do, now I don't know if this is going to be number five, but I know it should be phosphorus because nucleic acids, ATP,
Okay. So phosphorus.
The phospholipids of our cell membrane.
Not number five, but still on the board at number six.
Number six. So there's something in between nitrogen and phosphorus.
The only thing I can think of is sulfur.
Okay.
Let's go with sulfur. Okay.
That's in proteins.
We may have sulfur on the board.
But it's going to be at the number eight spot.
Okay. What am I doing wrong?
Wow, what is number five?
Nitrogen.
So right now we have oxygen number one, carbon two, hydrogen three, nitrogen four, phosphorus six, and sulfur eight.
We are missing five, seven, nine, and ten.
No cheating.
All right.
Let's do, so sulfur is already in there.
Wow.
Oh, calcium for marbones.
We have number five on the board with calcium.
All right.
There we go.
All right.
Now let's do.
Reminder, you have three strikes.
Oh, I do have three strikes.
Okay.
I don't want to use any, though.
You know me.
Okay, so I think now we should get into ions.
So I'm going to go with, you know, the bread and butter of our nervous system and ions in general.
So let's go with sodium first.
That's why we like salt.
Sodium is on the.
board at number nine.
Okay.
We have two left, number seven and number 10.
Let's do potassium.
Is potassium on the board?
It is at number seven.
Okay, so we got sodium of potassium.
That's our N-A-K channels for the neuroscientists out there.
One left are number 10.
This might be a tough one.
This one's a tough one.
This might be a tough one.
Okay.
Okay. So, um...
Okay, we're going to be oxygen, carbon, hydrogen, nitrogen, calcium, phosphorus, potassium, sulfur, and sodium.
We are looking for the 10 most abundant elements in the human body.
If you at home have gotten this before Krishna, you may be smarter than a scientist.
Yeah, I don't know. Okay, I'm going to guess on this one.
Okay, you have to go with iron. Okay.
Because of our blood. Hemoglobin.
Iron. Is it on the board?
I hear this.
Okay.
Not on the board.
Strike number one.
Got two more strikes in the chamber.
We do not have phone a friend.
We do not have any escape routes.
We already got calcium.
I put you on the spot today.
I know.
This one's a hard one.
Let's go with zinc.
Zinc is heavy.
And I know that we need it.
Okay.
I just don't know for what.
I'm going to go with zinc.
Number 10.
So even if we don't need a lot.
Is it zinc?
No.
Oh my gosh.
It is not zinc.
All right.
One more strike left for the 10 most abundant elements in the human body.
All right.
So I'm thinking it's either iodine because I know we need iodine.
That's why we need iodized salt or magnesium.
I know a lot of people take supplements of magnesium.
but people also take iron supplements and that wasn't on it.
Let's go with magnesium.
Final answer?
Yeah, let's do it.
Final answer for the number 10 spot,
10 most abundance elements in the body.
Is it?
No.
All right, what is it?
It is not our number 10 spot.
If you're at home, plug in your guesses now.
For our number 10 spot, the answer was,
Chlor. How did I...
Oh my God. I even said salt.
Sodium chloride. Wow.
So that's ridiculous.
This was our first rendition of, are you smarter than a scientist?
If you got all 10, you may have one out on this week one.
So this was our first go-around doing this.
I think it was pretty...
But that's just...
That's just my personal opinion.
I now have also access to a soundboard, so this can get very outrageous very quickly.
I will be sure to hold it in as much as possible.
But it looks like for the most part, everything went smoothly on the board itself.
I think this could be super fun.
That would be really fun.
So again, let us know in the comments if you are intrigued by Are You Smarter Than Scientist
and would like to see us bring that segment into the rundown episode.
on a regular basis.
We are going to now go into our third story of the day,
which was the one about the link,
the shared genetic link between humans and dogs.
And this is about golden retriever genes
linked to anxiety, aggression, and intelligence in humans
out of the University of Cambridge
and the Morris Animal Foundation
in the proceedings of the National Academy of Sciences.
Yeah, this was a really cool one.
They studied 1,300 golden retrievers, and it turns out that not all golden retrievers have the same personality.
I mean, anyone who has multiple golden retrievers or has seen multiple golden retrievers knows this.
They're not like a one brand type dog.
There's dogs that are shy.
There are dogs that are, you know, a little timid.
There's dogs that are very, very social.
So there's enough genetic variation within golden retrievers where when these scientists studied 1,300.
golden retrievers, they could figure out genes that were related to certain traits.
Each of these 1,300 golden retrievers, the owners of those dogs got like a little questionnaire
about like, you know, personality traits for your dog.
And then they could correlate using the genetic data certain genes with certain traits.
And then when they went and looked at humans and those human traits, the same genes mapped
to the similar human traits.
That's the idea.
Interesting. So there's two kind of points of data. There's sort of a quantitative data, which is the genetic piece. And there's like a qualitative data point, which is the survey.
Exactly. And there was the survey, there was a reference point both for dogs and the personality traits on the qualitative side and humans. And when they looked at the genes that were being expressed that mapped to the personalities in dogs, based on the feedback from the owners.
What's interesting is that if you point to those same genes and humans, the same qualitative data matches up.
Yeah.
And you can map the genes together because even though obviously the golden retriever gene and the human gene are not going to be identical,
their dogs, we're humans.
But you can look at the sequence of nucleotized, the ATGC, ATGC, and you can find overlap where this gene is like,
there's only very few mutations, right?
So it's definitely the same gene.
And then from that, they can figure out these genes.
that are actually related.
There's one gene, for example, PTPN1.
This was linked to aggression towards other dogs in golden retrievers,
and it's associated with intelligence and depression in humans.
So not same same, but it's really kind of this meta-behavioral state or personality type
that these genes are controlling.
They were very careful about making that distinction,
that this is not like a one-to-one mapping,
but it's rather like a shared biological route for overarching personality.
It's more meant to be a framework versus like a purely like, for lack of a better,
I'm like diagnostic,
exactly, a discrete diagnostic tool.
Yeah.
And it helps create a scaffolding by which to kind of architect the structures.
And then you can swap out the variables within those structures as makes sense.
Yeah.
And it also like leads to like insights and training dogs.
for example, because certain dogs might just be a certain way because of the genetic makeup, right?
And it has nothing to do with like their history or like so on and so forth.
Here's a quote from one of the lead researchers.
If your golden retriever coweres behind the sofa every time the doorbell rings,
perhaps you might have a bit more empathy if you know they're genetically driven to feel sensitive and anxious.
Love that from this researcher from the university.
of Cambridge, Anna Morris Nuevo.
It's funny.
As a
someone who has three dogs,
who have very, very, very distinct
and different personalities,
it's an interesting just to think about.
And also, as we continue to sort of
in of right, because we've touched a lot of genetic stories,
especially in the last couple of weeks.
and just the breadth and depth of the increase in our understanding of like this fundamental like, you know, the instruction manual for how our bodies and all like living beings like create the stuff net, the factories.
Yeah.
Right.
And the IP that generates.
It's as we continue to learn more, it, it's not only the understanding piece, which is the first step.
But that understanding is also an already being a place.
because there's a whole variety of things we can now do
because we actually know the map.
Yep.
We actually have that baseline reference point.
And we always love a dog story.
Yes, always.
Whenever I see dog stories in science news,
I'm like, yep, we're going to cover it.
The Corgi story continues to be, I think,
our most popular dog story.
Yes.
And then the whale, the pods attacking.
That's our biggest animal.
It's actually our biggest story ever,
which I still can't.
It's still so surprising to me.
We're going to wrap up the rundown today.
Again, super casual Friday, almost summer Fridays.
Here it's 92 degrees in Los Angeles, California currently, which is...
That's an average March Friday, so...
We're finally over the rain, I think, apparently.
Which is great.
And our last story is, you know, interesting because it dovetails with a lot of the AI stories we've talked about.
And there's both a human personality.
side to the story and sort of like an actual science part to the story. And this is related to
Jan Lacoon, who has recently left Facebook or meta in early 2026 and has now raised a billion
dollars to build AI that understands the physical world. And this is related to, this was covered
by Wired. And there's a lot of background to this story. I'll kind of just quickly paint a picture
before we kind of get into the physical world AI piece,
you know, in terms of if you've listened to any of the frontier model CEOs
over the last 12 months.
So this is Sardemis Asabas at Google DeepMind,
who runs all of Google's AI products, Gemini,
everything that's integrated with Google Workspace.
You have Dario Amadeh at CEO of Anthropic,
who has the Claude and Claude Code and co-work.
They've been very much in the zeitgeist and in the mainstream because of their ongoing kerfuffle with the Pentagon over usage of Claude within military applications, specifically autonomous weapons and mass surveillance primarily focused on civilian, but you could argue generally.
And particularly with Davos, the Davos speeches that just happened.
All of them were there and talking about all the journals are like, where is this going?
and when are we going to get to, quote, AGI,
artificial general intelligence or ASI, artificial superintelligence,
and can simply scaling the current architectures,
meaning putting more compute and more data into it,
get us there.
Or do, are we missing a fundamental architecture or concept
that needs to be included in order to actually make that jump?
And Jan Lacoon has been very vocal about,
his perspective that the scaling laws are not going to get you to AGI.
Yeah, he's been very vocal about that.
And he's had some really nice little analogies about why he thinks that is.
Yes.
He equates it to, you know, the models of Ptolemy on the epicycles.
Yes.
And how, you know, before Copernicus, everyone was trying to fit the Earth as the center of
the universe.
And so they came up with orbits around Earth.
But obviously Mars does this weird retrograde motion.
it goes backwards. And so Ptolemy decided, okay, I'm going to put an epicycle, which is Mars has a
big circle around the earth, but then around that circle, there's a little circle that Mars goes around.
So every once in a while on that little circle, it's going to go back. But then as you get closer and
closer and the data gets harder and harder, you just start adding more and more epicycles.
And it turns out, because of something called Fourier transforms in mathematics, for infinitely,
the more epicycles you add, the closer and closer you'll get to the ground truth. And you'll
never discover Kepler's ellipses if you don't have a fundamental change, right? And Yanuklun is saying
that basically our scaling hypothesis, which is just make the parameters more and more,
we're just adding epicycles and bidding data. But the underlying parameter of Newtonian gravity
and the one over R squared dependence were missing that entirely. I like that little...
That's a great, you know, that's a great and out like reference point. Yeah. And just
Just to briefly kind of touch on, so, you know, people talk about chat, GPT and clon and all this.
And the fundamental architecture that is undergirding them is this idea of large language models.
And, you know, so the ideas you're optimizing language as an abstract or as a construct.
And both Demis Asabas and Jan Lacoon in the last six to 12 months have discussed the importance of world models, this idea that language.
language models are not actually having this fundamental understanding of the physics of reality,
which is what has maybe made it a little bit more difficult to get image generation and video
generation that out of the box feels real. What seems to have happened is these LLMs have
created this this like abstraction of what they, like what they understand physics to be.
Yeah. But it is not actually grounded to like the real.
fundamentals. And so this has now become the new hot topic is world models. I actually believe Google's
already introduced for public consumption a version of their world model. Oh, okay. Where you can go into
the interface and it's procedurally generating a 3D environment in real time as you move around it. And you
can choose the POV of like a cat or, you know, a bird flying through the air. Yeah. And so it's not like a
video game where all the levels have been explicitly coded by developers already. And then when you get
to the edge, you can't walk deeper into the forest because there's an invisible fence in the Pokemon
forest. It just continually will procedurally generate, generate on the fly as you move around.
So as far as I'm aware, that's the first world model kind of thing at scale that's launched. But
it seems like Jan agrees with this viewpoint and is trying to push forth.
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for this day.
And with his new company advanced machine intelligence,
they're trying to focus on this idea of building AI world models
to actually understand like physical 3D spaces,
which becomes much more valuable in applications like having any kind of humanoid robotics
do anything in a physical environment,
whether that's in a manufacturing context, in a residential context,
driving is maybe a little bit different because it's such a rules-based system.
Yeah.
Whereas having a humanoid robot at home where you want to be able to have it, fold your laundry,
do the dishes, pick up stuff off the floor.
It's like unstructured tasks.
Yeah.
And I think just in general, too, even for language, right, and like producing text that makes
sense or producing recommendations that make sense, having a world bottle is a huge deal, right?
It'll give you recommendations that actually makes.
sense because it understands how fundamental physics works and so on and so forth, right?
There's one other sort of interesting palace intrigue corporate drama.
Oh, all right.
Aspect to this story, which is meta ended up acquiring, so Mark Zuckerberg ended up acquiring
this sort of AI infrastructure company, scale AI, which was led by this 20-something, you know,
super genius Alexander Wang, not that Alexander Wang, a different one.
and, you know, with no E between the D and the R at the E.
Got it, which is interesting.
And they acquired,
Ameta acquired their scale AI for $14.3 billion.
Okay.
And the idea was it was,
they were building like a tagging and training kind of pipeline system
that was supposed to accelerate,
you know, Olama and all of META's AI work.
Now, he,
Alexander Wang was brought in and became META's like first chief of AI, right?
Okay.
Or head of AI, right?
And you already have the legend,
Jan Lacoon there. Right. And so... Yeah, and Jan Lacoon is not your head of AI. Right. And what seems to have been
from the outside looking in, part of the drama here is, you know, Yon is more on the researcher
kind of viewpoint. So you could probably categorize like Sam Altman and Mark Zuckerberg in the
scorched earth philosophy. Yeah. Just spend money, get to the scale fastest because whoever gets their
first wins. And then the Jan Lacoon and Demisizizabas are more on the
if we have the deepest research bench,
we will be the ones who win.
And research is the driver of product,
not product being the driver of research
or product being the driver of implementation.
And Dario at Anthropic is like
kind of somewhere in between those two.
So it seems to be the case that he was
sidelined because he wasn't moving quick enough
or Zuckerberg was worried about losing.
And one of the reasons that Mark Zuckerberg
is so motivated to not lose the AI battle
against everybody else and why he was one of the first movers to really do a huge amount of capital
expenditure to build out meta's infrastructure is when we were going through the transition from
desktop to mobile in the early 20 teens Facebook missed the opportunity to build the hardware
device for mobile and what ended up happening is they became victim to Apple and Android
as it related to getting distribution to their end customers.
So there was a famous battle between Facebook and Apple
where they were like,
if you want to keep stealing users data,
we're going to kick you out of the app store.
Okay.
And Zuckerberg never again,
he vowed never again to allow someone
to be able to control his distribution in that way.
That's why he went big on VR and Oculus
because he's like,
if that's the next medium,
no one's going to beat me.
That's why he went big on AI and all this
because if that's the next medium,
no one is going to beat me.
However, all Apple has to do
to kind of really kill a lot of these,
and this is kind of the bare case
for a lot of the foundational models,
if Apple finally decides to do something good
and do a local only,
relatively high-quality model
on device
that no longer needs you to have a chat GPT subscription
or any of these other things,
and they have billions of devices everywhere
and become the first AI of choice,
it is going to become very sticky
for some of these model providers.
So we'll see.
But Jan Lacoon is out at Meta.
He's starting his new thing.
I think he's going to need more than a billion dollars.
Yeah, he has a billion dollars already from the likes of Mark Cuban, Eric Schmidt.
Yep.
And it values that $3.5 billion already.
Already.
In like six months of starting.
And it's going to say, and this is just the valuations of these AI companies.
It's just outrageous.
But again, people are viewing it as, you know, end game technology.
So with that, we are going to wrap up.
up our rundown for this Friday.
Touched on a nice fun
microbiology story.
Although it's not that fun if it ends up killing us all.
Solar storms and earthquakes.
Maybe this was not so happy to any.
But we had our, Are You Smarter
Than a Scientist? We got 9 out of 10.
Shared to genetics between us and dogs.
And the battle for AI
continues as people throw
money everywhere.
We are going to ask again
for feedback. This is going to be the third
episode that comes out this week.
We're splitting it out so that they're shorter, more bite-sized, easier to consume and digest on your commute during your workout.
And it just becomes easier to share with friends if you want them to listen to a specific section.
So let us know if you do like that structure and that setup.
We will continue on accordingly.
I am your host.
Lester Nare, joined as always by my co-host and our resident PhD, who may be as smart as a scientist, Krishna Chowdary.
We will see you all next week.
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