Hugely capable releases from OpenAI and Anthropic have done very little to quell the screams that the big ol' AI bubble have popped. Now a new Wall Street Journal story is saying that OpenAI's growth is slowing down and that failing to reach a billion users by the end of last year means that it's all over. Oh, it's all over again. Yes, AI stocks have crashed, but there's a lot more to to this story. We're going to get into how AI funding collides with its capabilities and whether or not OpenAI is on the edge of the cliff. And they're about to break, baby. Spoiler, it's not. Like, why would you say now they're not going to why are they going to watch, Kevin? Because Kevin will be talking about OpenAI's brand new voice integration, Claude's ability to interact with Blender. Oh, also Tom Cruise is running really, really fast now. And one of the fathers of ChatGPT has trained an AI model on old-timey techs. And lo, the appointed hour hath been arrived. We find ourselves to come at the last of this particular entertainment of the modern age. Just tell them what the show is, Gavin. Just say it. This is AI for Humans, good chaps. Welcome, everybody, to AI for Humans, your twice-a-week guide to the world of AI. And Kevin, today, we have yet another iteration, refrain that is coming back again that the ai bubble has popped and told you told you losers this is what you get from stealing from artists you've been talking about this forever kevin your whole thing is ai bubbles pop you've got ai is bubbled pop t-shirts that are on a hold right now that you're ready you should see the old english tattoo i have across my belly ye old ai bubble half popped the the wall street journal has a story about open ai's growth slowing down, which, you know, surprise, surprise, it's hard to attract a bunch of users, but on the backs of raising so much money for so many massive initiatives, falling short of, as you said, a billion users is actually, well, that's a reason to cry uncle and to, for an entire industry to collapse. So what are some of these numbers? What are these forecasts? And what does this mean for anybody who's like having a romantic relationship with their chat bot? Well, that's, there's two parts to the story. One is let's talk about what is in this Wall Street Journal story and kind of why it came out. Second of all, I think you and I both kind of feel this very strongly that there's two very different conversations happening here. One is the financial bubble that exists around AI, probably. The other is the capabilities of these AI tools that our audience and we know are getting better all the time. But first, let's start with the Wall Street Journal story. This is a big kind of exclusive story. It came out this morning. You know it was big because OpenAI themselves has got a lot of like people coming out and saying like, this isn't that big a deal. Trust us, blah, blah, blah. The basics here are that they are saying, Wall Street Journal is saying that OpenAI's growth has slowed down. And you know, as well as I do, every startup is kind of judged on its growth before it gets to the public markets. And one of the things that OpenAI has been trying to do this year is get ready for an IPO. And for those of you who are in our audience who are not like financial bro types, that means the idea that it is going to sell its stocks to the world at large. We also know that OpenAI has raised more private money than almost any company ever. In fact, that was like they raised $125 billion before they went to the stock market. So there's a lot of pressure on this particular company to grow and grow and grow. And the only way that this funding makes sense, and this kind of represents the overall AI business at large, is if this company continues to grow to the size of billions of users in the same way that Facebook is. And the idea that it would be slowing down and that it would not hit a billion users is putting a big kind of like, uh-oh flag in this for lots of people. There's some important context here. Even in this story, they talk about Anthropics growth, taking away some of OpenAI's momentum, which we know. Right. And Google as well. Yeah. And a lot of other people online have talked about the idea that like, look, OpenAI has pivoted now to this kind of new slimmed down, no Sora, more codecs, more programming, more business oriented approach. So there's a couple of things going on. But I do think it's important to hear first your take, and then we should try to get into that kind of deeper conversation about what this means for AI at large. Well, you every week scream at me. You're either growing or you're showing. And I never understood what that meant. And I think I'm getting what it is now. It means if open AI isn't growing, that they're showing weakness. Right? Oh, is that what this is about? That it's fair to say. Wow. Look, they're on the hook. Much faster than I expected. But keep going. They're on the hook for $600 billion. $600 billion in future spending while having only raised $122 billion, right? And they're going to burn that $122 projected in three years. Now, with Sora gone, yes, maybe they get 3.25 years out of it. I don't know. They were bleeding out with Sora. But there's some that would say that OpenAI isn't even really a tech company anymore. In fact, they're like the WeWork of AI. They're like a leveraged infrastructure bet masquerading as an AI company. I don't particularly side with that because a lot of the people screaming that about OpenAI are the same ones making memes about how Dario and Anthropic don't have enough compute to serve the models that they're announcing. So which is it? Did Sam Altman get his greedy, greedy eyes and reach for the infrastructure ring a little too soon? Or is he a genius that looked out on the horizon and thought, oh, we're going to need all this. It's going to be like electricity. We have to be able to serve it. or is it somewhere in between? I think there's a really interesting moment we're sitting in right now. And by the way, these companies and this idea of AI being this big is affected by more than just like our use of AI, the private funding of AI. Obviously there's things like geopolitical issues. There's all sorts of other things happening. The most important thing right now, I think, is whether or not OpenAI and Anthropic, the two kind of juggernauts in this space, will continue to prove useful and continue to kind of allow people to do more and more of their actual work with it so that people will pay for it. And I think that's a big question right now, right? You and I have talked about on the show many times. We personally find it useful, although I'm not sure how economically valuable some of the stuff we make with it is But the idea that business wise we not really the right example of that But business it does feel like a lot of businesses are finding use cases out of this Now, the biggest question I think ultimately will be, can that wheel turn fast enough? Because the other thing that's tricky about OpenAI, and I believe that there are lots of naysayers that have been out there and wanting this sort of story and this sort of thing to come true for a while is that there are so much, there's so much money now tied up in all of these giant tech companies in this AI build out that if this does fail in some form or another, or it does start to slow down, there is a little bit of a house of cards effect that could affect everything. A little bit? Yeah, a little bit. Yeah. I mean, Oracle is the biggest one, right? Well, here's like, you've seen the memes and I think we've discussed them on the show of the circular trading that happens between these companies, right? Oracle writes a big check to open AI to serve their models. Open AI writes a check to NVIDIA. NVIDIA writes a check to Oracle. Like it's like six companies all handing money around. And not only are the retail investors like highly leveraged in all of this, if you throw your money into the S&P 500 or anything like that, but your papa or your grandpapa, if you're one of the younger listeners, their pension is tied up in all this. So there is like, there is a bit of a, oh God, what's the shape Gavin? Where it's like a three, it's like three sides. It's like a triangle, it gets really tall. and there's a few companies and then everybody else is kind of buying in, but it all goes back to- No, don't say it. It's not a pyramid scheme. No, it's right. No, no, no. It's like more like a circular, like a rattler thing. And it's like the snake eating its own tail. Yeah. Yes, yes. No, look, there's a little bit of that going on, but I do just want to say like for all those saying that like this particular story and these, you know, like the six or eight companies, if you will, that are really pushing all this stuff, that them slowing down at all is a sign that the bubble is bursting. I don't think that's going to be the first sign. I think it's the million plus companies that you and I have talked about time and time again that went out and raised 30 million dollars because they put a skin on one of these companies and released an app or a claim that they were an enterprise solution for something i think there's a lot of the the dam is going to break there that's where the holes are going to be first before like open ai's slightly slowing growth right now is means that this bubble half burst well and also the number i want to point out here is the three year number which you know for a A normal person, a normal business might be like not that long at all, but three years in the AI space is a very long time. And I guess the question I continually come back to, and we're going to get into like why I don't think either of us believes this affects like AI, the actual technology at this point. But the thing I just keep coming back to is this idea that who knows what this stuff will do three years from now. Like I think a year from now, the vast majority of coders would have said, there's no way I'm going to end up doing most of my coding with AI. And now I think a lot of them, I would say a majority at this point now are coding mostly with AI, right? And that is like one year ago. So imagine a year, two years, three years from now, when these things get way more capable, and I do think they're going to, and maybe that's a good transition, Kevin, to kind of think about this separation of these conversations, right? Because I think a lot of people in the mainstream continually say like, AI is going to fail, it's going to fail. And that, yes, if the money side of AI fails, it will be harder for these companies to kind of make the bigger and newer models. But again, we just said it's not going to fail money-wise. Even if OpenAI doesn't make more than they're making right now, they have three years of runway left. That is a lot of time for these things to get better over time. And you and I have seen in the last three months, the acceleration of these things just go bonkers, right? right yeah i would say though i mean two two real shiny uh blinking red weak spots if you're a you know a final boss playstation gamer like the weakest points that are blinking right now is one it's like as we know a lot of times this infrastructure is a massively depreciating asset you spend billions of dollars to have all these servers and these high-end chips and then the next year nvidia releases something new and now your chips are half as capable let's say so there's there's that massive unknown, which is happening right now. And the other one is this open source thing that we keep talking about, where it seems like every few months, there's a new model that gets released usually by China that is a fraction of the cost. And it's almost as capable as the best things that these companies, which are raising billions of dollars are churning out. So yes, three years is a long time for open AI to figure it out. They could also like cut their costs and do ads and do a whole bunch more to boost their revenue. Sure. But these depreciating data centers the moment they're fired up, coupled with open source. Oh my God, it is a bubble, Gavin. We have to get out. Wait, Gavin. I have two counterpoints. I have two counterpoints. Okay, please hit me. Counterpoint number one. Recently, there's been a lot of talk and some of my analysis put out something about this, about the idea that older chips can actually serve the newer models better than they thought they could. So even though those chips might depreciate, they will still be able to serve- They're still very capable. They're still very capable and they may not be as capable as the brand new chips, but they're as capable. In fact, they're better serving the new models than they were serving the old models. That's one thing. The second thing, Kevin, is that so the new deep seek did come out. And if you didn't hear about that, I don't blame you. It was because it didn't make the impact that the last one did because it was actually about kind of a generation behind right now. It's equal to around Opus 4.5, maybe 4.6 level in that kind of era. And what's interesting about open source is open source might just be like a distillation so far of like what these frontier models are. I think to your open source point, though, the bigger question is, at some point, you run out of the ability to want to use this like super high end model, right? Because right now, I would say there's a lot of stuff that we can be doing with the current models that we're not doing, right? So maybe there is a world in a year or two where every open source model on the market is more than enough to serve every person's needs. And maybe that also makes the inference cheaper for these companies too, right? So there's all sorts of things that can happen from here on out. So I do want to shout out, I tweeted something about this. And Quindla is a good friend of ours in the open source world who runs a company called Daily and then also helped make PipeCat, the open source AI audio software, actually replied to me and said something really interesting. And we'll put the whole script thing on screen here. But his basic take here is just that he thinks that LLMs and AI at large are going to be bigger and more important than the internet And that we just kind of now scratching the surface as to what the use cases are And I think this was in response to me asking about like is this whole kind of bubble conversation around the fact that whether AIs are as big as the internet or they may be something less. And Quinda's argument, which I think is a good argument, is that actually they might be a lot more. And it's just a matter of finding ways to integrate all of these things and new capabilities into the sorts of stuff we do. And obviously Quinda does a lot of stuff with voice, but like it does feel like that's what we have this kind of moment of time right now. We're like this new magical thing has come into our lives and we have to figure out like, well, what the hell do we even do with this? Right? Like where do we put this and what does it go into? There was a time in my life, Gavin, and then I'm going to assume in yours as well, where I remember it was a transition. Sorry for the, for the old heads out there. Stay with me for the youngins. Just try to follow along. There was a thing called a four 86 Gavin and it was a processor and there were many before it a whole lot after it but around the time that the 486 uh became the pentium intel had this crazy new chip all these new capabilities then they were plugging ram into these computers the amounts were insane the hard drives went up from four gigs to like 16 gigs the numbers got bigger but something really interesting happened which is where you could offer somebody a six thousand dollar high-end pentium rig with all the ram in the world blah blah blah blah if it didn't have a modem in it and it couldn't connect to something called the internet, I would take the 486 with a monochrome screen and barely any RAM because that was clearly it. And I wonder if we're going to have that moment. I don't wonder. I have my opinion. I want yours though. I wonder if we're going to have that moment where we look at intelligence similarly. I'm not going to be interested in a device if it either doesn't natively have some sort of AI, some intelligence built in, or if it isn't readily, easily accessible by AI models to be interacted with or, you know, in some capacity. Do you think we're going to see it become that present? I think that's true. I honestly think that that's the thing that will prove the use case of this. And what's interesting is like, on the other hand, it also might be where AI becomes the commodity, right? Where it's just in everything. And then what AI is special versus not special? I don't know. And that becomes another question of like, are these companies worth as much as they're worth? there's no shortage of amazing things happening especially if you as a viewer at home push that like and subscribe button because you know what the amazing stuff all begins here we are the origin point the big bang of everything interesting comes out of us our two little heads explode out thank you and i do want to say like someone did say that we are the most impactful uh podcast ever released in the history of ever others said that we are the tastemakers for the community that without us ai would be a bubble that bursts we're the only ones like holding the door so to speak and I just want to say thank you and I agree. So please like, subscribe, leave a comment down below, juice that algo and if you want, you can back us on Patreon. Go to aiforhumans.show. That's our official website. You can sign up for the newsletter which still drops twice a week and you can buy us a coffee. How good is that? We like to stay caffeinated. Sip, sip. Newsletter drops once a week, unfortunately. The twice a week just couldn't keep going. Well, here's the thing. I get it on two different inboxes, Gavin. I only check one of those later in the week. So it's really like a second treat for me. You can do that too. Let's talk about all the cool stuff that people are actually using AI to make. And Kevin, I do want to start with this clip that you sent me, which is just a perfect example of how money should be spent in AI. This is putting Tom Cruise into famous movies running in them. Tell me a little bit about what this is and who made it. There is a YouTube channel called Alternate Reality Movies. There's still a sleeper channel. So shout out to them. Give them a sub. They've got a bunch of like kick-ass cameos starring Chuck Norris, where he just shows up unannounced in a bunch of movies. They're mashing up different genres. But this one was very simply Tom Cruise runs faster. And it is clips from everything from, you know, Forrest Gump to Back to the Future, where Tom Cruise shows up unannounced. He'll even facepalm a T-1000 and run faster. He runs faster than buses in movies. He'll run faster than Arnold Schwarzenegger on a horse. It doesn't matter. It's just Tom Cruise bolting at high speed. And it even kind of has the Tom Cruise run, which is, yeah, it's unbelievable. And I think it goes to the point like, you know, obviously you can't do this with a lot of current AI video models. This is probably being done with open source tools. So it just goes to our open source point before this idea that you can face swap in Tom Cruise and make this stuff. It's just a very, very fun use of technology. watching him throw the boys from stand by me away or um like uh hip checking uh uh sylvester stallone as he's running and rocky to go this to just so good tom cruise has become like the ai of hollywood in a lot of ways he's just going to be all actors in the future uh kevin we should keep going here there is a cool voice interaction from open ai that they're calling chappy which i kind of found interesting the coolest thing about this is that it actually allows you to use real time voice opening eyes real time voice to fill out forms which is a real good use case of open eyes technology here this is like okay to to the thing that i said earlier not to pat myself on the back abon but this the what's really cool about this demo is that it's yeah it's someone using their voice to interface with like a web browser but it's not doing the traditional agent thing where the ai takes a screenshot or or scrapes the dom of the page or whatever else it's like the the the tech stack gives the agent direct access and information about what's on the page, right? So filling out the form, like you said, or engaging in dark mode versus light mode. This is to me like the signal of like, oh, right. Like there were rumors of the open AI wearable, the big device with Johnny Ive is going to be a phone. This would be a use case. This would be an actual use case, yes. Do you want to play a second? It's an audio, it's got an audio demo. Let's just take a listen to a brief moment of this. In this demo, I've even added a cursor just to show the user what's happening on the screen. Let's start with a practical example. Here we have to find a simple application with a wake word and the ability to go from light mode to dark mode. Hey, Chappie, can you go to dark mode? It's done. Yeah, so what you're seeing on the screen is... I had to say it's done because it happens so quick. Go ahead, Gav. Yeah, no, and what's interesting here is you realize that the thing's not talking back. This is just you saying something and then it does the stuff automatically within the actual application Can we do knight to f3 This is a chess demo The piece moved already by the way like that quickly the piece moved because the ai didn have to read the screen see what he talking about who trying to whatever it just knows what's happening on the on the page and so when you extrapolate this to all of your apps across your entire ecosystem suddenly a device where you don't have to go and hunt for the thing that you want to load to then ask it to do something you just tell the ai and it inherently has access to all those things and can manipulate it. I do get excited for that device. Yeah. I mean, it goes to show you how important really good computer use is, right? Because when you can plug a very smart agent into a very good computer use, suddenly you're able to do all this stuff. It also made me think of all of the people who are paralyzed or who have disabilities, like the ability for them to, instead of having to like have a speech to text and try to find the actual form that's a massive level up too again this is just a cool thing that came out from open ai's developer channel and like this is the future of it all that is huge when you talk about like the bcis or brain computer interfaces something like a neural link is what comes to mind no pun intended for a lot of people usually that is think about where you need the mouse to go think about the click you need it to make think like that that will be gone um that's it's a huge huge boon for accessibility. You're totally right. Yeah. Another really cool thing that just came out is Blender is now being plugged directly into Claude. This is a direct combination of within Claude itself, where you can talk to Blender. If you're not familiar with Blender, it's an open source 3D modeling tool that I have actually spent a little bit of time lately with. And guess what, Kevin? Claude does Blender really well. I made a little kind of raccoon gangster thing sort of scenario, which is very cool. We're going to talk about that a little bit more on Friday's show. but it is a very cool integration and again this is another example of a very complicated system blender is a nightmare i tried to learn it myself i shouldn't say it's a nightmare i am i'm just not built to learn complicated systems in that particular way but claude is a translator in this way like it translates your ideas directly into blender and it gives you 3d models and it's not really difficult to do so i was also very excited about this this is like a i won't get too super weedsy about it. It literally just came out, but, uh, Nemo Tron three nano Omni. Oh boy. That's a fun mouthful, but NVIDIA released this. It's a 30 billion parameter model, uh, with a decent context window. So it can, it can cram a lot. But what I really think is interesting about this is that it is like an Omni model, which means it's one tiny model. Think of this running on your phone or running on a small robot in the near future. And it natively handles, uh, audio video and text so it does not need to call a tool or connect to something else to understand what it is seeing or what it is hearing it can process that natively and across modalities so you can feed it a video ask a question and it can answer you with audio like there's it's a really really interesting space i like nvidia has a vested interest in powering these things because again future of robots they're making things that plug directly into robots i just thought it was interesting, perhaps not as interesting as the talky LLM though. Well, this is the thing, like all those things we just mentioned are things that are important to understand about like how AI is advancing in different pathways. If there's AI video or there's other stuff, AI is also going backwards, Kevin. And this is actually a very interesting scientific project. What this is, first of all, it was created by Alec Rad and David, sorry, David, I'm going to butcher your Dukovny. Not David Dukovny, a very smart man. David Duvunad. Sorry, I did butcher it. And Alec Radd, if you're not familiar, is actually the person that worked at OpenAI and kind of was the engineer behind the first iteration of ChatGPT, GPT-2, and other ones like that. This is a model that essentially is only trained on text from 1931 or earlier. So what you're getting out of this is an LLM that is trained to answer, but nothing past 1931. And what's really fascinating about this is it just gives you a sense that these LLMs work on being trained on all this data, but we do have a lot of data pre-1931. And it speaks like an older person from that era. And when they ask a question of who's the president right now, it thinks of somebody in 1931. And it's just another good example of playing with the idea of what AIs are capable of, And then like maybe what smaller focused data sets could make AIs into, right? Because to me, I immediately think about like character stories, right? Or like, oh, what would it be like to have this AI write something versus an AI that we have right now write something? In general, I think it's a very cool idea. Yeah. And the important distinction, again, is that it was trained off of that data exclusively. So it's not like a newer model that's being told role play like you're an old timey something. a lot of that data came from patents and came from documentation that had to be scanned so there was like a lot of ocr involved because there was no yield reddit for it to scrape so i think that's cool i think having a model like that and seeing if it can like um uh investigate or uh uh or invent new science like modern science you know how would it react to being told that there is a device called a pager or a cellular phone or even a phone how would it react to that and then it got me thinking like what sort of what sort of other llms would you want to train exclusively on like like i was thinking like a like a guardians llm trained only on groot and it can only answer with group would be interesting to me that's a pretty easy you could fake that one pretty simply because it would just what about root uh b movie llm or cookie monster well see this is what i'm getting at is this idea that you could create an llm that would essentially be a much more diverse much more interesting, like very specific character. And you can think in the future of if you have, if everybody has this collection of AI agents, if one of your AI agents is like B-movie hero, and it's only B-movie dialogue and about what a B-movie hero would do, that would be a lot of fun, right? And like maybe useful for something. Maybe you give that B-movie hero, whatever the most recent technology development is, and they find a way to kind of open it up to a whole different world. But I don't know, this is just a cool way of looking at- Literally, this makes me realize that we're never going to be responsible for revenue at any of these companies. And I love that. No one should. No one should ever give us responsibility for revenue except for you when you go to our Patreon. Thank you, everybody. We will see you on Friday. Great show. And we'll talk to you soon. Bye-bye.
