Better Offline - How DeepSeek Showed That Silicon Valley Is Washed

Episode Date: February 3, 2025

In this episode, Ed Zitron explains how the emergence of a much-more-efficient generative AI model has become an existential threat to the future of OpenAI and Anthropic - and tells a dark story about the death of innovation in Silicon Valley. --- LINKS: https://www.tinyurl.com/betterofflinelinks Newsletter: https://www.wheresyoured.at/ Reddit: https://www.reddit.com/r/BetterOffline/  Discord: chat.wheresyoured.at Ed's Socials: https://twitter.com/edzitron https://www.instagram.com/edzitron https://bsky.app/profile/edzitron.com https://www.threads.net/@edzitronSee omnystudio.com/listener for privacy information.

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And as I've written about many, many, many, many times and argued on this very podcast just as often, the large language models run by companies like OpenAI, Anthropic, Google and meta, are unustainable and the transformer-based architecture they run on as peaked. They're running out of training data, and the actual capabilities of these models were peaking as far back as March 2024. Nevertheless, I'd assumed, incorrectly, by the way, that there would be no way to make them more efficient, because I had assumed, also incorrectly, that the hyperscalers, along with Open AI and Anthropic, would be constantly looking for ways to bring down the ruinous cost of their services. After all, OpenAI lost $5 billion last year, and that's after $3.7 billion in revenue, too, and Anthropic lost just under $3 billion in 2024.

And in the last episode, I told you a little bit about Deepseek, by the way, in this one we're going to get into, well, how fucked things might actually be. But what I didn't wager was that potentially nobody was actually trying to make these models more efficient. My mistake was, if you can believe this, being too generous to the AI companies, assuming that they didn't pursue efficiency because they couldn't, and not because they couldn't be bothered. But then, as I just hinted at, a little known Chinese company released a product that was broadly equivalent to open AI's latest reasoning models, but cost a fraction of the cost to train and run. And now the conventional understanding of how generative AI should work has been fundamentally upended.

You see, the pre-deep-seat status quo was one where several truths, and I say that in the loosest sense of the word, allowed the party to keep going. So the first one is that these models were incredibly expensive to train. GPT-40 cost $100 million in the middle of 2024, and future models, according Dario Amadeo-anthropic, might cost as much as $1 billion or more to train. And training future models, by the way, as a result of this, would necessitate spending billions of dollars on both data centers

and the GPUs necessary to keep training these bigger, huger models. Now, another thing was these models had to be large, because making them large, pumping them full of training data, and throwing masses of compute at them, would unlock new features, such as an AI that helps us accomplish much more than we ever could, without AI, which is a Sam Altman, quote. And in the words of Sam again, you'd be able to get a personal AI team full of virtual experts in different areas working together

to create almost anything we can imagine. I don't know, mate, you ever try creating a functional fucking business? Dipship. Anyway, here's another one. These models were incredibly expensive to run. It has to be this way. But it was all worth it because making these models powerful was way more important than making them efficient because once the price of silicon comes down,

and this is a refrain I've heard from multiple different people as a defense of the costs of generative AI, we would then have these powerful models that were cheaper somehow because of silicon. Now, you may think, Ed, that sounds like a, not a real argument, that just sounds like something someone said once. And it is, it is something someone said once. Anyone who knows anything about chips know how hard it is to make a new chip. And remember one of the CES episodes when I asked Max Churny about this, you should go back and listen to him. Anyway, another thing, another part of this, was that as a result of this, was that as a result of this, need to make bigger, hugeer, even bigger models, the most powerful ones, these big, beautiful

models, we love them, we look at the big, beautiful models. We would, of course, need to keep buying bigger, more powerful GPUs, which would continue the American excellence of burning a bunch of money on nothing. And by following this roadmap, everybody wins. The hypers get the justification they needed to create more sprawling data centers and spend massive amounts of money. And open AI and they're ill get to continue building powerful models, and also Nvidia continues to make money selling GPUs. Remember I've said in the past that things were kind of a death cult? This is what this is. It's a capitalist death call. It runs on plagiarism and hubris, and the assumption that being, that at some point all of this would turn into something meaningful. Now, I've argued for a while

that the latter part of the plan was insane, that there was no profitability for these large language models, as I believe there simply wasn't a way to make these models more efficient. In a way, I was right. The current models developed by both the hyperscalers, so Gem and I from Google, Lama from Meta and so on and so forth, and the multi-billion dollar startups, if you can even fucking call them that, Open AI and Anthropic, they're horribly inefficient.

And I've just made the mistake of assuming that they tried to make them more efficient, and they couldn't. But what we're witnessing right now isn't some sort of weird China situation. This isn't China being Chinese and doing scary Chinese things to us. No, what we're witnessing is the American tech industry's greatest act of hubris. It's a monument to the barely conscious stewards of so-called innovation, who are incapable of the k-fabe of the fake competition, where everybody makes the same products,

charges about the same amount of money, and mostly innovates in the same direction. Somehow nobody, not Google, not Microsoft, not OpenAI, not meta, not Amazon, not Oracle, thought to try, or was capable of creating something. something like Deepseek, which doesn't mean that Deepseek's team is particularly remarkable or found anything super new, but that for all the talent, trillions of dollars of market capitalization and supposed expertise in American tech oligarchs, not one bright spark thought to try things that Deepseek had tried, which appeared to be, what if we didn't use as much memory and what have we tried synthetic data? And because the cost of model development and inference was so

astronomical in the case of American models, they never assumed that anyone would try to usurp their position. This is especially bad, considering that China's focus on AI as a strategic part of its industrial priority was really no secret, even if the ways it supported domestic companies kind of is. In the same way that the automotive industry was blindsided by China's EV manufacturers, the same is happening with AI. Fat, happy and lazy and most of all oblivious, America's most powerful tech companies sack back and built bigger, messier models powered by sprawling data centers at billions of dollars of GPUs from invidia, a bacchanalia of spending that strains our energy grid and depletes our fucking water reserves. Without, it appears, much consideration of whether an alternative

was possible. I refuse to believe that none of these companies could have done what Deepseek has done, which means that they either chose not to, or they were so utterly myopic, so excited to burn so much money on so many parts of burning the earth, boiling lakes and stealing from people in pursuit of further growth that they didn't think to try. This isn't about China. It's so much fucking easier if we let it be about China. No, no, no, no.

It's about how the American tech industry is incurious, lazy, entitled, directionless, and irresponsible. Open AI and anthropic of the antithesis of Silicon Valley. Their incumbents, public companies wearing startup suits, unwilling to take on real challenges, more focused on optics and marketing than they are on solving actual fucking problems.

Even the problems that they, themselves created with their large language models. By making this about China, we ignore the root of the problem, that the American tech industry is no longer interested in making good software that actually helps people. DeepSeek shouldn't be scary to Silicon Valley, because that Silicon Valley should have come up with this first. It uses less memory, fewer resources, and uses several kind of quirky workarounds to adapt to the limited compute resources available, all things that you'd previously associate with Silicon Valley. Except now Silicon Valley, these only interests like the rest of the American tech industry is the rot economy.

It only cares about growing, growing at all costs, even if said costs were really things you could mitigate, or if the costs themselves were self-defeating. To be clear, if the alternative is that all of these companies simply did not come up with this idea, that in and of itself is a damning indictment of the valley. Was nobody thinking of this stuff? If they were, why didn't Sam Altman or Dario Amadeh or Satchinadell or anyone else put serious resources into efficiency? Was it because there was no reason to? Was it because there was, if we're honest, no real competition between any of these companies? Did anybody try anything other

than throwing as much compute and training data at the model as possible? It's all just so cynical and antithetical to innovation itself. Surely if any of this shit mattered, if generative AI truly was valid and viable in the eyes of these companies, they would have actively worked to do something like Deep Seekers done. Don't get me wrong. It appears DeepSeek employed all sorts of weird tricks to make this work, including taking advantage of distinct parts of both CPUs and GPUs to create something called a digital processing unit, essentially redefining how data is communicated within the servers running training and inference.

And just as a reminder, inference is the thing where when you type something in, it infers the meaning. Just could have specified that earlier. DeepSeek had to do things that a company with unrestrained access to capital and equipment wouldn't have to do, and it often used impractical and quirky methods to do so. Nevertheless, Open AI and Anthropic both have enough money and hiring power to have tried and succeeded in creating a model this efficient and capable of running on older GPUs. Except what they wanted, what they actually wanted was more goddamn growth and the chance to build even bigger data centers with even more compute that they would own.

Open AI is as much a lazy cumbersome incumbent as Google or Microsoft, and it's about as innovative too. The launch of its operator agent was a joke, a barely functional product that's allegedly meant to control your computer and take distinct actions like ordering stuff off of Instacart, you know, things you could do with your hands. But just to be clear, it doesn't work. You'll never guess who was really into it, though. His name is Casey Newton. He writes a blog called Platformer, and he's a man so gratingly credulous that it makes me want to fucking scream. And of course, he wrote the operator when he used it was a compelling day. demonstration that represented an extraordinary technological achievement also somehow was significantly slower, more frustrating and more expensive than simply doing any of these tasks yourself.

Casey, of course, not to worry, had some extra thoughts about Deepseek, that there were reasons to be worried, but that American AI labs were still in the lead, saying that DeepSeek was only optimizing technology that OpenAI and others had invented first, before saying that DeepSeek was only last week that OpenAI made available to ProPlan users a computer that can use itself. this statement is bordering on factually incorrect. It is fucking insane that Casey is still doing this. I do not what to... I don't know what to do with this guy. This guy, just like... That's a fucking lie. This, the computer can't use itself.

This shit can't... Just to explain what operator is, you're meant to type in something like, hey, order me some milk. Order me some milk off of Instacar. And when Casey tried this, it tried to find milk in Des Moines, Iowa. Just fucking insane.

Just... This is how these kinds of... companies have got big. It's people like Casey. It's people like Casey were just like anything they show. Like, God damn, that's the most impressive thing I've seen in my life. It's a fucking farce. But let's be frank. These companies aren't building shit. Open Air Anthropic are both limply throwing around the idea that agents are possible in an attempt to raise more money to burn. And after the launch of Deep Seek, I have to wonder what any investor thinks they're investing in, other than certain ones I'll get into in a bit. And to be clear, an agent is meant to be this

autonomous thing, which you say, hey, go and do this action, go and sell things for me and go and email people for me. They don't really work. There are some that kind of do that are really expensive, but large language models are not built for this kind of thing. But let's be honest, Deepseek, and as I said in the last episode, they've built a more efficient reasoning model, so like Open AIs 01. And you'd think, well, okay, couldn't Open AI simply add on Deepseek to its models? Not really. First of all, with the way these models work, you can't just like plug it in. It's just not how it works. They could train a new model using deep seek's techniques, but the optics of that aren't brilliant. It would be a concession. It'd be in a middle that open AI

slipped and needs to catch up. And not to its main rival, pretend rival, I mean anthropic, or to like another big tech firm, but to an outgrowth of a hedge fund in China, a company that few had heard of before December. And, like, really, not that many people had heard before January 25th. It's very embarrassing. And this, in turn, I think, will make any serious investor think twice about writing the company a blank check. They're going to have to dip into some very bothersome pockets.

And as I've said, ad nauseum, this is potentially fatal, as Open AI needs to continually raise money, more money than any startup has ever raised in the history of anything. and it really doesn't have a path to breaking even, even if they copy what Deepseek did, because we still right now, though Deepseek is 30 times cheaper than 01, we don't know if that's profitable. We don't know.

We haven't found out. And if OpenAI wants to do its own cheaper, more efficient model, it's likely to have to create it from scratch, like I said, and while it could do distillation to make it kind of more like Open AI using their own models, by the way, Deepseek taught itself using OpenAI's outputs, like I mentioned in the last episode, it's kind of what DeepSeek already did.

It already has been fed OpenAI bullshit. Even with OpenAI's much larger team and more powerful hardware, it's hard to see how creating a smaller, more efficient and almost as powerful version of 01 benefits them in any way, because said version has, well, already been beaten to market by Deepseek, and thanks to Deepseek, will almost certainly have a great deal of competition for a product that, to this day, lacks any killer apps anyway.

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So if you've ever supported me or you're just chasing down a dream, this is right where you need to be. Listen to the Clifford show on the IHeart Radio app, Apple Podcast, or wherever you get your podcast. And for more behind the scenes, follow at Clifford and at TikTok Podcast Network on TikTok. It's just, it's, it's very frustrating to me. It's very frustrating to me. It drives me a little insane. Reading all this stuff makes me feel crazy. I think you hear it in my voice.

You hear the sanity stripping away, but I'm here to podcast and don't worry. But seriously, though, anyone can build on top of what deep seeker's already built. Where is OpenAI moat exactly? And where's anthropics? What are the things that make these companies worth 60 billion or 150 billion or, my God, as we'll discuss, us in a bit $340 billion. What is the technology they own or the talent they have that justifies these valuations? Because it's kind of hard to argue that their models are particularly valuable anymore.

Celebrity? Celebritydom? Cult of personality? Ortman, Sam, he's an artful bullshitter and he's built a career out of being in the right places at the right times, having the right connections, and knowing exactly what to say, especially to credulous tech media ponses without the spine or inclination to push back on his more stupid claims. And already, Aortman has tried to shrug off Deep Seeks rise, admitting that while Deep Seeks R1 model is impressive,

particularly when it comes to its efficiency, open AI will obviously deliver much better models and also it's legit invigorating for OpenAI to have a new competitor. Yeah, mate, sure. I'll bet your love in this. Altman ended his tweet where that came from with, Look forward to bringing you all AGI and beyond,

something which I add has always been close on the horizon in Altman's world, but it's never really materialized and the timeline keeps moving and there's no actual proof they can do it. AGI is not fucking happening. And if it's possible in any way, it's not coming out of probabilistic models. I'm fucking sick of this. An open AI can't even lean on its relationship with Microsoft, which on Wednesday, January 29th, started offering deepseek's models through its own cloud services. Open AI hasn't got shit. Deepseek has commoditized the large language model, publishing both the source code and the guide to building your own. Whether or not someone chooses to pay deepseek is largely irrelevant. Someone else will take what

they have created and build their own, or people will start running their own deep seek instances, renting GPUs from one of the various cloud computing firms. They don't give a shit, they'll take the money. And while InVidio will always find other ways to make money, Jensen Huang is amazing at this. It's going to be a hard sell for any hyperscaler to justify spending billions more on GPUs to markets that now know that near-identical models can be built for a fraction of the cost with older hardware. Why do you need Blackwell, which is the latest Nvidia GPU? The narrative of this is the only way to build powerful models, it doesn't really hold water anymore. And the only other selling point is that what if China does something? Well, the Chinese did something. And they've now proven that

they can not only compete with American AI companies, but doing so is possible in an efficient way that can effectively crash the market. While there's been a recovery, this is still very worrying. I also want to address something real quick. A few people on Twitter have been suggesting that talking about Deepseek positively in any way is some sort of Chinese op.

If you believe this, you're a fucking moron. I really must be clear. Take your weird xenophobia and go eat your own shit. I don't fucking care anymore. Yes, there are problems with China. Yes, China does something to America. This is an open source thing.

This is an open source thing. This is an open source. thing and you can remove China from the equation because it's open source, someone else is going to use this. If your only defense is the sneaky Chinese are doing something, go to therapy and talk to the therapist about you being paranoid or racist because it's one of them. I should also be clear, concerns about China are very realistic. The Chinese government has tried to interfere with America. It's happened many times. Even if China is funding deep seeks models, the fact that they are open-sourced means that anyone can run them and anyone can build their own. They can look under the

hood. We don't have the training data, but that is it. You cannot win on a xenophobic argument here. You can have realistic concerns about another foreign power. I'm not saying not to. But what I am saying is that you have to look at this realistically, and you have to take this seriously, and dismissing this as Chinese magic, is stupid. It's very goddamn stupid. But like I said earlier, it also isn't clear if these models are actually going to be profitable. It's unclear who funds DeepSeek, like I just said, and whether its current pricing is actually sustainable. But they're likely going to be a damn site more profitable than anything OpenAI is currently selling. After all, OpenAI loses money on every single transaction, even their $200 a month chat GPT Pro subscription.

And if OpenAI cuts its prices to compete with DeepSeek, its losses are only going to deepen. And as I've said again and again, this is also deeply cynical because it's obvious that none of this was ever about the proliferation of generative AI or making sure that generative AI was accessible. Putting aside my very obvious personal beliefs for a second, it's fairly obvious why these companies, the big hypers, and OpenAI and Anthropic, wouldn't want to create something like Deepseek. Because creating an open source model that uses less resources means that Open AI Anthropic and their associate hyperscaler Findom clients, would lose their soft monopoly on large language models. Now what does that mean? I'll explain. Before DeepSeek, to make a competitive large language model, like GPT-40,

as in one that you can actually commercialize, required exceedingly large amounts of capital, and to make larger ones effectively required you to kiss the ring or the ass of Microsoft, Google, or Amazon. While it isn't clear what it costs the train OpenAI's O-1 reasoning model, we know that GPT-40 cost in excess of $100 million, and 01 as a more complex model would likely cost even more. We also know that OpenAI's training and inference costs in 2024 were around $7 billion,

meaning that either refining current models or building new ones is quite costly. The mythology of both OpenAI and Anthropic is that these large amounts of capital weren't just necessary, but the only way to do this. While these companies ostensibly compete, neither of them seem concerned about doing so as actual businesses that made products that were, say, cheaper and more efficient to run, you know, they made more money than they cost. Because in doing so, these companies would break the illusion that the only way to create powerful artificial intelligence was to hand billions of dollars to one of two companies and build

giant data centers to build even larger language models. This is AI's rot economy. Two lumbering companies claiming their startups, creating a narrative that the only way to build the future is to keep growing, to build more data centers, to build larger language models, to consume more training data with each infusion of capital, GPU purchase, and data center build out, creating an infrastructural moat that always leads back to one of a few tech hyperscalers. Open Aanthropic need the narrative to say buy more GPUs and build more data centers, because in doing so they create the conditions of that infrastructural monopoly,

because the terms, forget about building software that does stuff for a second, were implicitly that smaller players cannot enter the market because the market is defined as large language models that cost hundreds of millions of dollars and require access to more compute than any startup could ever reasonably access without the infrastructure that a public tech company delivers. Remember, neither anthropic nor OpenAI has ever marketed themselves based on the products they actually build. Large language models are in and of themselves fairly bland software products,

which is why we've yet to see any killer apps. This isn't a particularly exciting pitch to investors or the public. markets because there's no product innovation or business model to point to. And if they'd actually tried to productize it and turn it into a business, it's quite obvious at this point that there really isn't a multi-trillion dollar industry for generative AI. Look at Microsoft and their attempts to strong-arm co-pilot into Microsoft 365, both personally and commercially. Nobody said, wow, this is great when they demanded you use co-pilot in Word. Lots of people, however, asked, why am I being charged significantly more for a product that I don't want or care about?

Open AI only makes 27% of its revenue from selling access to its models, so allowing people to use their models to build products. Around a billion dollars of annual recurring revenue, by the way, with the rest of their money coming in about $2.7 billion last year, coming from subscriptions to chat GPT. If you ignore the hype, Open AI and Anthropic are actually deeply boring software businesses with unprofitable, unreliable products prone to hallucinations, and the new products, such as OpenAI Sora,

cost way too much money to both run and train to get the results, the, well, they suck. They're not good. Even OpenAI's push into the federal government with the release of chat GPTGov is unlikely to reverse its dismal fortunes. Seriously, think about it. I'm sure some of you are going to say, well, Trump will just give them money. These motherfuckers need way more money than Trump is going to give them. And why would Trump bet on a loser? Why would Trump be like, oh yeah, I'm going to give more money to this company that does the same thing? He doesn't understand any of this shit. And he probably just looks at Sam Orton and goes, nah, that's a kind of new money I don't like.

But to make this more than a deeply boring software business, Open AI Anthropic needed larger models. And they needed them to get larger, generally in perpetuity, and for the story to always be that there was only one way to build a future, and that the future cost hundreds of billions of dollars,

and that only the biggest geniuses who all happened to work in the same two or three places were capable of doing it. Post Deepseek, there really isn't a compelling argument for investing hundreds of billions of dollars of CAPEX in data centers, or buying new GPUs, or even pursuing large language models as they currently stand. It's possible, and DeepSeek through its research papers explained in detail how, to build models competitive with both of OpenAI's leading models, and that's assuming you don't simply build on top of the ones that Deepseek released. It also seriously calls into question what it is you're paying OpenAI for in its various

subscriptions, most of which, other than the $200 a month pro subscription, have hard limits on how much you can use their most advanced reasoning models. One thing we do know, though, is that OpenAI and Anthropic will now have to either drop the price of accessing their models, and potentially even the cost of their subscriptions, too. I'd argue that despite the significant price difference between 01 and Deepseek's R1 reasoning model, the real danger to both OpenAI and Anthropic is Deepseek V3, which competes with GPT4O, which is their general purpose model, by the way. And as I'm recording this episode, by the way, news broke the Alibaba, a bit of the

Bohemoth out of China in its own right has created its own model that outperforms Deepseek. I'm yet to fully dive into it, but if it's true, it's only going to pile on the price pressure. Though I kind of wonder what they could possibly do. Is it going to be cheaper? Because if it's more powerful, that's just like, doesn't really change shit. Anyway, though, Deepseek's narrative shift isn't just about commoditizing LLMs at large, but commoditizing the most expensive ones, run by two monopolists backed by three other monopolists. I mean, the magic's died.

There's no halo around Sam Altman or Dario Amade's head anymore, as their only real argument was we're the only ones that can do this, something that nobody should have believed in the first place. Up until this point, people believed that the reason these models were so expensive was because they had to be, and that we had to build more data centers and buy more silicon because that's just how things worked. They believe that reasoning models were the future,

even if members of the media didn't really seem to understand what reasoning models did or why they mattered, and that as a result, they had to be expensive, because Open AI and their ilk were just so fucking smart. Even if it wasn't obvious what reasoning meant or what it allowed you to do or what the products were, it's just very annoying. And now we're going to find out, by the way, because reasoning is now commoditized, along with large language models in general. Funny enough, the way that DeepSeek may have been trained using, at least in part, synthetic data,

also pushes against the paradigm that these companies even need to use other people's training data. though their argument, of course, will be that they need more training data, always. We also don't know the environmental effects, by the way, with Deepseek, because even if it's cheaper, these models still require those energy-guzzling GPUs to run, and they're running at full tilt. In any case, if I had to guess, the result will be that the markets are going to be far less tolerant of generative AI, and the idea that generative AI is the future. Another podcast from some SNL late-night comedy guy, not quite.

Unhumor me with Robert Smygel and friends. and hilarious guests from Jim Gaffigan to Bob Odenkirk to David Letterman help make you funnier. This week, my guest, SNL's Mikey Day and head writer Streeter Seidel help an a cappella band with their between songs banter.

There's the worst singer in the group. The worst? Yeah. Me. Is there anything to the idea that because you're from Harvard, you only got in because your parents made a huge donation. The group. The yarn birds, right?

That's the name. The Harvard Yard, but they're open. Do you have a name suggestion? We're open. Since you guys are middle-aged, one erection. Listen to humor me with Robert Smigel and Friends on the I-Heart Radio app, Apple Podcasts, or wherever you get your podcast. Humor me. I need some jokes to make me seem funny.

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Within probably 10 days, I'd put on 10 pounds. I was having trouble stopping the muscle growth. Listen to Superhuman on the IHard Radio app, Apple Podcasts, or wherever you get your podcasts. A win is a win. A win is a win. I don't care what you're saying. Yep, that's me.

Cliver Taylor the fourth. You might have seen the skits, the reactions, my journey from basketball to college football, or my career in sports media. Well, somewhere along the way, this platform became bigger than I ever imagined. And now I'm bringing all of that excitement to my brand new podcast, The Clifford Show. This is a place for raw, unfiltered conversations with some of your favorite athletes, creators, and voices that not only deserve to be heard, but celebrated. One week, I'll take you behind the scenes of the biggest moments in sports and entertainment, and the next we'll talk about life. mental health, purpose, and even music. The Clifford Show isn't just a podcast.

It's a space for honest conversations, stories that don't always get told, and for people who are chasing something bigger. So if you've ever supported me or you're just chasing down a dream, this is right where you need to be. Listen to the Clifford show on the IHeart Radio app, Apple Podcasts, or wherever you get your podcast. And for more behind the scenes, follow at Clifford and at TikTok Podcast Network on TikTok. Open AI and Anthropic no longer really have moats.

Unless, well, there is another idea. What if there was a huge fucking idiot with a lot of money? How about billionaire dipshit Masayoshi's son, the CEO of SoftBank, a multinational investment firm that's rumored to be investing anywhere from $15 to $25 billion in Open AI in a round that values the company at an astonishing $340 billion as part of a round of up to $40 billion. Now, you may think,

Damn, this is a sign that Open AI is going to make it, but I must remind you how bad SoftBank is it investing. They put $16 billion into famously awful real estate company WeWork and managed to lose, I think, $800 million on the DoorDash IPO and $1.8 billion on their investment in Uber. And in both cases did so because they were desperate to bandwagon on to supposedly shorefire bets, either just before they crashed or way after an investment made sense. According to the Wall Street Journal, SoftBank would lead this insane $40 billion round in the company and would, and I quote, help assemble investors for the rest of the round. In doing so, SoftBank would also become OpenAI's largest investor, replacing Microsoft and, yes, SoftBank was the largest investor in Wheatwork before it went tits up. It's also important to remember that OpenAI is pledged to put $18 to $19 billion to fund the Stargate Data Center project,

along with, you guessed it, SoftBank will be committing the same amount. This is on some level soft bank handing money to itself to invest in data centers to prop up an industry that's dying. Now, this is a developing story, but it's hard to imagine any serious contribution for many respectable investor at this point. My money is on a few VC firms desperately scraping at the bottom and the barrel. Quarter of a billion here, quarter of a billion there, maybe Nvidia chucks in some. And on the subject of barrels of stuff, I also expect money from the Kingdom of Saudi Arabia and its associated venture-off. You're going to see if maybe Andresen Horowitz gets involved. They don't think much. It's just very fucking silly, and I don't know how this works out. Open AI burns money,

and even if they somehow make more efficient models, the actual total addressable market of generative AI is actually pretty small. Microsoft said in their recent earnings they made $12 to $13 billion of ARR on AI. Just to be clear, that's not profit, and that's not a business unit. There's no AI business unit, which means that that is just spread across. delivering cloud compute for AI, copilot on Microsoft 365 products, which, by the way, no one likes, they're having trouble selling, and other associated co-pilot products they sell. I don't think, and like $12 to $13 billion across four quarters, that's not actually good at all. It's just very silly.

All of this is so silly, and when I think about it too hard to feel, a little crazy. Open AI makes $3.7 billion in revenue, and they do so, as I mentioned, primarily from chat GPT, subscriptions. Even if that somehow, and it won't, by the way, turns into $3.7 billion of profit, or even $10 billion of profit a year, that's less than the profits in a single quarter of any given hyperscaler. It would be respectable, sure, but a $340 billion valuation, I guess, makes sense if it was profit. It doesn't make sense if it's not profitable, though. It also isn't obvious how Open AI would actually provide any liquidity to investors, by which I mean allow them to sell their stock beyond selling shares of people that work at OpenAI, like people who work there who have

been given stock grants, selling that to another investor, a really dumb guy maybe. And as in this side, SoftBank bought $1.5 billion of stock from Open AI employees in the tender at the end of November 2024, just a note for you. They could also take the company public, but with the unit economics of this fucking company, which boiled down, by the way, too, our products lose billions of dollars and are extremely commoditized, I'm not really sure what the plan is here. The fundamental problems that OpenAI has are not solved by throwing more money at the problem. This hasn't worked before and it won't work this time.

They're burning cash. And in SoftBanks case, it isn't obvious what it is they're getting from Open AI. Is it the chance to continue an industry-wide con? The chance to participate in a capitalist death cult? I don't know. Maybe it's the chance to burn money at a faster rate than we work ever could dream of. Will this be the time that Microsoft, Amazon, and Google just drop Open AI? and Anthropic and make their own models based on DeepSeaks work.

What incentive is there for the hyperscalers to keep funding Open AI and Anthropic? They hold all the cards, the GPUs, the infrastructure, and in the case of Microsoft, non-revocable licenses that permit them unfettered use and access to OpenAI's tech, and there's little stopping the hyperscalers from building their own models and just dumping them entirely. In fact, Microsoft might actually be a little glad to see SoftBank become the biggest investor and pick up the tab for OpenAI's expenses. I can imagine Satchi Nadela texting Sam Orton being like, no, don't take their money, LOL. Don't do it.

Oh, I'd hate that. I'd hate it if this was someone else's problem. And the Stargate thing, by the way, is an attempt to, the up to 500 billion thing, it's just bollocks, whatever. It's an attempt to remove themselves from Microsoft. And Microsoft actually allowed OpenAI to alter their deal so that they could get cloud compute from others.

Now, at the time, people were like, yeah man uh this is a this is a good thing this shows open ai will be independent no it doesn't it just means that they're gonna be under masayoshi's son now the funniest dumbest man in investing i love masyoshi's son i think it's nice that we have an insane guy who isn't instantly murderous in our lives anyway anyway though as i've said before i believe we're at pkai and now that generative a i has been commoditized the only thing that open a i and anthropic have left other than a pile of cash, is their ability to innovate. And I don't think they're capable of doing so.

And because we sit in the ruins of Silicon Valley with our biggest startups all doing the same thing in the least efficient way possible, living at the beck and call of public companies with multi-trillion dollar market caps, everyone is trying to do the same thing in the same way based on the fantastical marketing nonsense of a succession of directionless rich guys

that all want to create America's next-top monopoly. It's time to wake up accept that there was never any kind of AI arms race, and that the only reason that hyperscale has built so many data centers and bought so many GPUs is because they're run by people that don't experience real problems and thus don't know what problems real people face. Generative AI does not solve any trillion dollar problems, nor does it create outcomes that are profitable for any particular business. DeepSeaks models are cheaper to run, but the real magic trick they pulled is that they showed how utterly replaceable a company like Open AI and by extension

any LLM company really is. There really isn't anything special about any of these companies. They have no moat. Their infrastructural advantages moot, and their hordes of talent are relatively irrelevant. What Deepseek has proven isn't just technological, it's philosophical. It shows that the scrappy spirit of Silicon Valley Builders is dead,

replaced by a series of different management consultants that lead teams of engineers to do things based on vibes. You may ask if all of this means generative AI suddenly gets more prevalent. After all, Satchin Adela of Microsoft quoted Yvonne's paradox, which posits that when resources are made more efficient, their use increases. Sadly, I hypothesize that something else happens. Right now, I do not believe that there are companies that are stymied by the pricing the OpenAI and their ill coffer, nor do I think there are many companies or use cases that don't exist because large language models are too expensive.

AI companies took up a third of all venture capital funding last year, and on top of that, it's fairly easy to try reasoning models like 01, and make a proof of concept without having to make an entire operational company. Shear OpenAI barely has one. I don't think anyone has been on the sidelines of generative AI due to costs. And remember, few seem to be able to come up with great use case for 01 or other reasoning models anyway. And DeepSeaks models, while cheaper, don't have any new functionality. As a result, I don't really see anything changing beyond the eventual collapse of the API market,

which is the way you plug these models into things for companies like Anthropic and OpenAI. large language models and reasoning models, they're niche. The only reason that ChatGPT became such a big deal is because the tech industry has no other growth ideas. And despite the entire industry and public markets screaming about it, I can't think of any mass market product that really matters. Even if DeepSeek doesn't land the fatal blow, it could set the foundations from another company

to drag open AI's carcass out behind the barn and hit it with a big stick. One way in which this entire farce could fall as if nasty Mark Zuckerberg decides he wants to simply destroy the entire market for LLMs. META has already formed four separate war rooms to break down how Deep Seek did it, and apparently, to quote the information, in pursuing Lama, which is their large language model, CEO Mark Zuckerberg wants to commoditize AI models so that the applications that use such models, including Metas, generate more money than the sales of the AI models themselves. That could hurt Meta's AI rivals, such as OpenAI and Anthropic, which wrong pace to generate billions of dollars in revenue from such sales. And lose billions. Fucking hell.

I love the information, but can you add the most important bit? But I could absolutely see Meta releasing its own version of DeepSeaks models. They've got the GPUs and Mark Zuckerberg can never be fired, meaning that if he simply decided to throw billions of dollars into specifically creating his own deep discounted ALMs to wipe out Open AI, he absolutely could. After all, a few weeks back, Mark Zuckerberg said that Meta would spend between $60 and $65 billion in capital expenditures in 2025, and this was before the Deep Seek situation. And I imagine the markets would love a more modest proposal that involves Meta offering a chat GPT beta simply to fuck over Sam Altman.

And that's the thing. Chat GPT is big because everybody's talking about AI, and chat GPT is the big brand in AI. It is not essential, and it's only being treated as such because the media and the markets ran away with a narrative that they barely understood. Deep Seek pierced that narrative, because believing said narrative also required you to believe that Sam Altman is a magician versus an extremely shitty CEO that burned a bunch of money.

And I don't believe that, even before Deep Seek, that Altman's peers really bought into the hype. Sure, you can argue that Deep Seek just built on top of software that already existed thanks to OpenAI. Thank you, Casey, by the way. But this begs a fairly obvious. question. Why didn't Open AI build on top of software, invented by Open AI? And here's another question. Why does it goddamn matter? In any case, the massive expense of running generative

models hasn't been the limiter on their deployment or their success. You can blame that on the fact that they, as a piece of technology, are neither artificial intelligence nor capable of providing the kind of meaningful outcomes that would make them the next smartphone or cloud computing. Honestly, it's all been a con. It's been a painfully obvious one. One I've been screaming about since February, since when I started this podcast, trying to explain that beneath the hype

was an industry that provided modest at best outcomes rather than any kind of next big thing. Without reasoning as its magical new creation, Open AI really doesn't have anything left. Agents aren't coming. Large language models aren't going to build them. AGI isn't coming either. There's no proof it's possible.

All of this is fucking flim-flam to cover up how mediocre and unreliable the fundament of the supposed AI revolution really was. All of this money, all of this energy and all of this talent was wasted, thanks to markets that don't actually do anything, markets that don't make for good companies just growth hogs, and a media industry that fails to hold the powerful to account. And it looks like everything got broken by some random outgrowth of a Chinese hedge fund. It's so ridiculous, it's so sickening.

I can't believe it. Well, I can totally believe it. I'm actually surprised they didn't come up with this idea myself. Just the idea that someone could do this cheaper. It makes me go insane. And what's more insane is that open AI is still going to be able to raise that round. But I think we're approaching the end of days. I'm not calling the end of the bubble yet.

I refuse to do that. I'm not going to do that. What I am going to say is it's deflating. And I am going to say I have no idea how they reinflate it. A bunch more money isn't going to change anything. These companies are washed. Sam Hortman's washed. He's the Mark Sanchez.

of the tech industry. And he's so sickening. All of them are so sickening. Imagine if this money had gone anywhere else. Imagine if it had gone into batteries. Imagine if it had gone into climate stuff. Imagine it have gone somewhere useful. Imagine if instead of spending billions on this dog shit,

they actually fix their problems. They actually fix the products that they've made worse. But the problem is that the rot economy is in control. That the growth at all costs mindset is all that you see in the tech industry. And Silicon Valley needs to repent. Silicon Valley needs to change its ways, because when the bubble bursts, and I really think it will, the destruction that follows will be horrifying,

and it will hit workers, it will hit tens of thousands of tech workers, and it will affect the markets. And after that, the markets are going to realize something. The tech industry doesn't have anything left. They don't have another growth market. They're out. They're all out. And I look forward to telling you how.

I look forward to talking about it when it happens. and I'm so grateful for you listening. Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Matt Rosowski. You can check out more of his music and audio projects at Mattisowski.com. M-A-T-T-O-S-O-S-K-I.com. You can email me at E-Z at Better Offline.com or visit Better Offline.com to find more podcast links and, of course, my newsletter.

I also really recommend you go to chat. Where's your ed dot at to visit the Discord and go to our slash better offline to check out R-R-R-R-W-Lead. Thank you so much for listening. Better Offline is a production of Cool Zone Media. For more from Cool Zone Media, visit our website, coolzonemedia.com, or check us out on the IHeartRadio app,

Apple Podcasts, or wherever you get your podcast. Another podcast from some SNL, late-night comedy guy, not quite. Unhumor me with Robert Smygel and friends. Me and hilarious guests from Bob Odenkirk to David Letterman help make you funnier. This week, my guest. Yes, SNL's Mikey Day and head writer Streeter Seidel

help an a cappella band with their between songs banter. Where does your group perform? We do some retirement homes. Those people are starving for banter. Listen to humor me with Robert Smigel and friends on the I-Heart Radio app, Apple Podcasts, or wherever you get your podcasts. A win is a win. A win is a win.

I don't care which I'm saying. Yep, that's me. Clifford Taylor the 4th. You might have seen the skits, my basketball and college football journey, or my career in sports media. Well, now I'm bringing all of that excitement to my brand new podcast, The Clifford Show. This is a place for raw, unfilled conversations

with athletes, creators, and voices that not only deserve to be heard, but celebrated. So let's get to it. Listen to The Clifford Show on the IHeart Radio app, Apple Podcast, or wherever you get your podcast. And for more behind the scenes, follow at Clifford and at TikTok Podcast Network on TikTok. I'm Michelle McPhee,

and I've been unraveling the strangest criminal alliance I've ever reported on, a Mormon polygamist and an Armenian businessman. Multi-million dollar house, Ferraris and Lamborghinis, private jets, a billion dollar fraud. But how long can this alliance last? Tell me what you know. Is somebody coming after me? Listen to Kingdom of Fraud on the IHart Radio app, Apple Podcasts, or wherever you get your podcasts. Life is full of hurdles. So how do you keep going? On Hurtle with Emily Abadi, We're talking with the most inspiring women in sports and wellness from professional athletes, coaches, and Olympic champions about the challenges that shape them and the mindset that keeps them moving forward. At our level, at this scale, being able to fail in front of the entire world.

Like, I can do anything. I can do anything. Listen to Hurtle with Emily Abadi on the Iheart radio app, Apple Podcasts, or wherever you get your podcasts. Presented by Capital One, founding partner of IHeart Women's Sports. This is an IHeart podcast. Guaranteed human