Chapter 1: What milestones have been celebrated in episode 700?
Hey, what's going on, everybody? Today is April 10th, 2026. This is the Daily AI Show, and today is episode 700. We made it. We're here. We like the, I know, it's crazy, right? It's crazy. By the way, Andy and Beth are here with me today. I think it's just the three of us, unfortunately, kind of a bummer that just the three of us could make it on number 700, but we'll catch up with them.
Maybe we'll get Carl and we'll get Jimmy in here. We'll talk about it maybe next Wednesday or whatever. But we like to celebrate when we hit the hundreds. I think that's kind of our thing. I guess maybe 1,000 will go a little bit bigger in another year or so. But when we hit these little milestones, big milestones...
It's fun to just chat about and discuss because now at this point, we're hitting what two and a half years August, I think would be three years since we started the show. So yeah, it's kind of crazy. In fact, I was chatting with somebody you'd introduced me to Andy, and And while we're talking about that, we're like, oh, how do we know Andy? Right.
And it was it was like, well, I've never met him in person, but I have talked to him more than some people in my life over the last over the last two and a half years. So, hey, Carl. Hey, happy 700. Yes. Love it. All right. We got Carl here, too. Fantastic. Okay, so today I think we'll change things up just a little bit.
I mean, I still think let's leave a little time at the top for any quick AI news we want to get in before the weekend hits because there's stuff developing every single day. But then what I did, I was telling Beth and Andy right before we went live,
What I did was I used Perplexity's computer and pretty quickly said, look, I want to have a timeline, a journey to go on with our live audience over the last two and a half years of generative AI. not about our show or our topics per se, but just what we would have been talking about over that time.
And it put together this nice sort of journey all the way through from what's coming next, predictive, obviously, but even where some of the models are, the pricing, What they were able to do two and a half years ago versus what they are to do today. So I thought it'd be fun for all of us. And there's quite a few little like tidbits through there.
So it'll be fun for us to, you know, for like, hey, Carl, what do you remember this? Or what do you think about that? Or, you know, just to get people's opinion of like where it's going and stuff. So if you guys are game for that, I am. And yeah, we'll kind of we'll kind of get into this. But why don't we just do a quick round? We'll try to keep it quick.
Because I think this 700 journey here is going to take the most of the show. But Andy, you were saying you did actually have something, not about me using Perplexity Computer, but you said you had some news about Perplexity?
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Chapter 2: How has generative AI evolved over the past two and a half years?
So they also just recently added an integration that lets you do tax filing with the IRS and it automatically fills the forms. So now you can imagine Perplexity has built something that doesn't compete at the frontier model level. That's never been their strategy.
They're building a platform that could compete with TurboTax, with whatever the latest rocket money, all of those different little apps that people use to track their finances. Now go to Perplexity Computer.
I mean, crucially right, it has read access, not write access, right? From Perplexity. That's an important caveat that I think people would want to know. I have not used Plaid. I've used other tools like... I've used other tools to connect that I've been less than thrilled with. There always seems like there's one account that I have that doesn't connect. It kind of throws off the totality of it.
I've said this on the show before. I have kept a line item budget for the family since 2017. And it's laborious. And honestly, it got way, way, way worse when my wife and I started getting serious about building up credit card reward points and stuff like that. We realized that we were just missing out on money we were spending anyway. And so we really started to pay attention to that.
And I'm glad we did because it helps us travel and it pays for free flights and all sorts of stuff. But the trade-off to that is the complexity because instead of just having one credit card, there might be seven in rotation that are going around. I don't carry debt. I pay off all my bills. But you know what I mean? I'm doing it for the points, not for the debt.
So just to be clear, I'm not nine cards in with deficit spending. But nonetheless, that's my life, right? And it is a giant pain in the you know what to track it. It's gotten so much harder. Is it worth it? Yeah, because of the points and the things that it does for my wife and I and my daughter. But I do like this idea.
Now, the big if for me is not perplexity because I believe perplexity can actually build me something that is a replacement for the tool I have. Well, the manual that I built up because everything has categories and subcategories. And what I've always seen trip up is little things like... Payments being made to a credit card oftentimes end up looking like additional charges. Right.
And so there's some there's some nuance in there that I absolutely can smooth through.
And so, yeah, I definitely think I think you might be able to give perplexity computer access to the thing that you've built and say, run this for me.
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Chapter 3: What new features does Perplexity Computer offer for financial management?
So like you have to look at this stuff. But anyway, I'm excited about it. So, yeah, that's a really I think that's cool. And next year I will probably use it for tax stuff, too, because why not? Why not use the tools we have?
So I'm gonna take this as an opportunity to give a little bit more detail about what I talked about at the end of yesterday's show, which is Perplexity's billion dollar build contest or funding thing.
subscribe to perplexity max or pro to be eligible so you do have to have a paid subscription but it is a spring 2026 eight-week competition it's the billion dollar build can you use perplexity computer to build a billion dollar company brian or andy or carl or me yes Prove it. Compete for up to 1 million in seed investment and 1 million in computer credits.
Wait, wait, wait. If I build a billion-dollar company, how much do I win? And why does that matter if I've built a billion-dollar company?
You build the prototype, I believe, of the billion-dollar company.
Oh, I don't actually have to build the company. Okay, good. That's an important clarification. Okay.
We're searching for the first computer native unicorn. Perplexity computers, multi-agent AI system, et cetera, et cetera. You can register starting on April 14th. The investment opportunity is up to 2 million to build and scale your idea. Up to 1 million seed investment.
um shared among up to three winners okay so maybe a third of a million that's all right um and up to one million in computer credits computer being capital c perplexity computer uh their system so how to enter build ship reveal register Two, submit your product. Product video application and traction data. And three, live reveal. Top 10 finalists present live on video.
Five minutes to show your project. Five minutes Q&A with judges, streamed and recorded. uh so yeah um and they have they have suggestions of like the things that you could these are sparks not a short list the best entries will surprise us their examples personal relocation agent elder care coordinator side hustle cfo autonomous localization studio
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Chapter 4: What are the predictions for AI advancements in the next few years?
Well, there is also Codex news. OpenAI released their $100 plan as well. So $100 gets, it's exactly the same as Anthropic. $100 gets you 5x what you get for $20. $200 gets you 20x of what you get for $20.
So somebody smarter than me, explain to me why this is possible. Why is what Cerebrus...
It's basically running on a different chip architecture that Cerebrus built, which optimizes for inference. So, you know, just like Grok, the GROQ company, you know, built a special chip, a language processing unit, LPU. Cerebrus has wafer scale chips.
inference engine and it's a huge massive chip stack that you know is goes actually beyond i think the capabilities of nvidia's forthcoming vera rubin stack and and it's already out there and there are small data centers that can run using cerebrus and it's not inexpensive i i expect but that's what we're seeing if we're seeing just how powerful and quick ai can be when it's running on
optimized chip architecture.
And so the total time here was versus 200. I'm sorry, two minutes and 40 seconds. Sorry, Carl.
Yeah, yeah. Because I've been using Spark since they released it, right? And so it depends on what you do. I think there was news where they're just testing the infrastructure because the whole goal is to give Cerebrus to all the models, to run it off Cerebrus, but they have to test it first. Can you think of all the things you're doing
at that speed it do like the the like just the concepts of like forget like sure it'll take you a little bit longer but like 29 seconds when because what i've been doing and you get rate limited a lot right now i'm at the max plan and i you get rate limited like there's a separate rate limit just for codex spark
like on codex you have everything else it goes through but on spark there's another little like yeah it's um but what i've been doing is i've been doing plan mode on um whatever model and then i would execute in codex and it would be like this is ridiculous and then i would test it against like opus i would test it against that and what i'm building i'm like holy like and you can only do so much there's only so much they can give you
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Chapter 5: How are AI models impacting content creation and collaboration?
So there will be need for what we just saw, but I think it's going to be at the tip of the pyramid, the top unique use cases.
And I'm looking at the comments here. It's like, for complex things that didn't do well. Like, yeah, it was never designed to mimic 5.4 at the max. Right. it was there specifically for us to test it and test the infrastructure to see, and then also do really quick tasks. Right. It's just, that's the showcase. Imagine it, putting it into 5.5 for everybody to use.
It changes the entire landscape of how, what you can do, what you can build. Right. And so I don't know what, like, like Grok is the other one, but I think Nvidia bought Grok. They pretty much tied it up.
SpaceX and Grok, no.
SpaceX AI is a different company.
Grok with a Q. That's the thing. I'm curious. Who else is connected to... Does Google have the TPUs that are just as... Do they have an equivalent? I can't remember.
Probably in development, but we haven't heard about it yet.
Yeah, yeah, yeah. Because I would imagine in a year or two, everything is going to be at this speed, but you will need those data centers. You will need those. If you want to run something like this on your... PowerPoint presentation, you can have a lot of data centers because this is not, in my mind right now, it's really not really designed to do your PowerPoints or anything like that.
By the way, who does it? Most people in WeWork are going to have that two and a half minutes to go get their kombucha downstairs from the kitchen, you know what I mean, in the WeWork. So, you know, not everybody's going to need this kind of speed. Also, what it does, though, is it means you don't have to be right. When you can build a fully functional CRM, that team can say,
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Chapter 6: What are the implications of AI in healthcare and drug development?
That's all I need. It can look like a piece of crap, but it functions so well. That's kind of right. I think for a lot of teams internally, it's, Do I really need the visual? Not really. I just need it to work.
And then let me tell you something. It is so nice to build an internal tool because you're like, it can be hacky. It can glitch. It can like, and you're like, but it does, but it doesn't do what I need to do. Yeah. And you're like, yep. And then you can turn to your coworkers and go, you can't like, you can't say anything. It works.
You know, every time you build a client thing, there's obviously a higher expectation for it to look clean and polished. That's getting easier.
You're not telling this thing. You know, the point is you're not telling it.
I love a bit internal tool. It's just, it's just, it looks like something out of the matrix. You're like, that's what the heck is. It works for me. That's it. Hours a week.
That's all it is.
Yep. Okay. So I wanted to bring this up here. Let's see. Maximize. There we go. It brings us off the screen, but I'm just trying to help people be able to read it. We're going to go through this journey here. I know, Carl, you said you only have a few more minutes before you have to hop, but actually, you know what? It's kind of weird not seeing y'all.
So I'll just do it this way and I'll zoom in maybe a little bit from my side. So give me one second here. And this is just something... All right, we'll see how that goes. This is just something fun. I literally had Perplexity Computer do for me this morning. Great example of I just need it for today. It does not need to go beyond today.
I mean, I guess if anybody wants the zip file, I'll put it in the community if they want to play or read longer because there is a lot of content in here. But... I thought it would be fun to just kind of run through this. And basically I said, I need this for a live, for a live demo or presentation. So that is what it did. Now I will give you guys the choice dark mode or what do you guys think?
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Chapter 7: How will AI transform the software industry in the coming years?
137 billion global Gen AI market. And it's saying 78% enterprise adoption. Now, I think There's probably a lot of asterisks and caveats on that on, you know, like where and when. But that's what it's sort of giving us a starting point. And then it's given us a timeline here. And I don't know, you know, we won't read these verbatim. Maybe that's why I'll share it in the community.
People can go to it. But if we if we, you know, Wayne's World, you know, time warp back to 2023, what were we looking at? Now, we're not talking about the beginning of Jenny when the first opening models came out. We're just talking about when our show started. which was roughly 10 months after the first major release of ChatGPT and DALI.
So we had GPT-4 at that time, and it had scored an 86% on the MMLU benchmark. We had Claude 1, Midjourney V5. Meta had released Llama 2 at that time, and open source was sort of exploding. We had Daily A Show launch this first episode. That's right. Put it on the timeline. Then we had in September, we had Chachapati Code Interpreter goes mainstream.
The precursor to everything we're basically doing with Codex and Cloud Code really sort of goes back to Code Interpreter back in the day. It was a tool that a lot of people were using. Then we had GPT-4 Turbo, which got a lot bigger. And then we had Gemini 1. Remember, they had rebranded from BARD, but that was a little bit earlier than that.
As we move into 2024, we started hearing about the robots, right? So figure one, 01 had come out over that time. We're already up to, by March, we're already up to Claude 3. We're talking about Opus beating GPT-4. 4.0 comes out, 0 for Omni, right? Remember that. 3.5 comes out for Claude. Then we're still talking about 4.0 Mini coming out being 60% cheaper than 3.5.
We have the stumble with the Humane AI pin. That was in August of 2024. Big old launch and a big old flop for good reason. By the way, there was news about that. I just didn't get to it called Button. Did you guys see the news about Button? It literally is a button. It's like the Star Trek bridge, that kind of thing. But number one, it's big. It's bigger than you want the button to be.
And also, I'm just going to wait for Siri to be fully... you know, run by Gemini. And I don't know why you need a button. Anyway, that was news from today. So there was a stumble on that. Then we have like Alpha Fold 3 winning the Nobel Prize. Just talked a whole bunch about that yesterday. By December 2024, we're already talking about Sora, V2, Runway Gen 3.
So we're already into the multimodal and videos. Open AI Operator came out. I would have guessed that was 2025. So December 2024, Open AI Operator hits the stage. Now, as we get into last year, remember, we had that huge December. It says January. I'm going to say December. But right in that 2024 and 2025 pivot, that's when Deep Seek R1 hit the stage and everybody kind of freaked out.
It was like, oh, my God, what are the Chinese doing?
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Chapter 8: What insights can we gain from the predictions shared for the future of AI?
What can they do? This is amazing. Then we had Gemini 2.5 Pro and on and on. Let's see if there's any more. Waymo expands, 71 million miles driven, zero fatalities. Tesla Optimus, right? 5,000 robots in factories. Um, by late 2025.
And then this year we're, we're, you know, we're still talking about Gemini, obviously perplexity computer, which just was built on, um, years of the, it's the year of the agent swarm. I kind of feel like I, I tipped my hand on that one a little bit because of the way I did the prompting, but that's okay. And it's saying today, obviously we hit our 700th episode.
Now, this is what I find really interesting. Now, it's saying the models and the price collapse. So this is the MMLU benchmark. And if we look at just where GPT 3.5 was coming out in March of 2023, it was ranking at 72%. And now look at your frontier models today, and they're at 97%. And multiple models are there, right? So huge improvements just on the benchmarks.
And then if you look at this, like what used to cost $80 now costs 10 cents. Now, I went back and tried to verify this a little bit because I thought, hmm, we're mixing models here. Because at the top, it's talking about for GPT-4, which we said came out.
And it feels like I'm spending more now than back then.
Yeah, that's the trick, right? It's saying input was 30. This is correct, by the way. These numbers are correct. Input was $30 per million tokens and output was $60 per million tokens. That I validated because I was curious. At the bottom here, they have Gemini 2.5 Flash. And I was like, hmm, is 2.5 Flash a better model overall than GPT-4? Well, based on what I could find quickly this morning...
it could be considered comparable in what it was able to do. In fact, in a lot of ways, it was superior because it was multimodal versus for just only being text in, text out. And so if you compare that, GPT 2.5, I'm sorry, Gemini 2.5 Flash was roughly 15 cents per 1 million tokens. And I think the 60 cents is wrong. I really do think it's more like $2.
Either way, that would be a massive, massive price drop. Now, to your point, Andy, we don't necessarily feel it all the time. Because we're not still using GPT-4. But if the entire world was still using GPT-4, then yes, this is probably correct. Something that costs around $80 to compute and do with AI when we started the show now costs around $0.10.
I think this is probably the thing on here that blows my mind the most. Because you really don't think about it this way about... Gemini 2.5 flash versus GPT 4.0. And in fact, if you try to go research it, there's Yeah, well, I think Gareth had built a comparison chart, right? But like, we don't necessarily look back in the way back, we kind of look at what's going on today or in recent memory.
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