Figure’s AI Robot, AI News, Cognition’s Devin, and the biggest AI bet yet! | E1915

0:00okay january 1st 2027 a humanoid robot will be available for purchase yes and delivery yes you can have it in your home by January 1st 2027 2727 a humanoid robot robot will be available for purchase yes and delivery yes you can have it in your home And whoever's right, the other person buys the robot for that person. Wow. This is the largest bet in the history of This Week in Startups. There's 20 grand on the line here. What are we doing here on this podcast? I don't know. I mean, this is getting out of control. This is a big, major bet. It's a big bet. This Week in Startups is brought to you by LinkedIn Ads.

0:45To redeem a$100 LinkedIn ad credit and launch your first campaign, Go to linkedin.com slash this week in startups. Gusto is easy online payroll, benefits, and HR built for modern small businesses. Get three months free when you run your first payroll at gusto.com slash twist. And Adio, a radically new CRM for the next era of companies. Head to adio.com slash twist to get 15 % off for your first year. all right everybody welcome back to this week in startups it's twist it's madra mondays but we're moving from ai monday since we record on mondays and we're going to just start publishing ai tuesdays so it's gonna be ai tuesdays going forward with me i like larger mondays i know really we record on modular mondays okay and that is my partner in crime mr sunny sandeep madri you can follow him on twitter at sunday definitive uh intelligence has been uh merged into grok and so i'm now going to refer to you as what co-founder of grok or no technology officer what is your title going to be i am the general manager leading the grok cloud and our commercial business got it gm of grok cloud g-r-o-q as opposed to g-r-o-k which leads to i think maybe a good place to start i saw that elon you know has been um in this lawsuit with closed ai formerly known as open ai he said he dropped the lawsuit he's got a sense of humor obviously if they just changed their name to closed ai but uh they open source grok how big of a deal is it that he open source grok and what has the reaction been to g-r-o-k which is elon's yeah open sourcing what i would say not a big deal it's a huge deal you know it continues to show the constant battle between open source and closed source.

2:43And the biggest deal with their model is the size of it. So it's larger than any other model that's been open sourced. And so it really gives a glimpse to the community of what someone who has at scale resources is doing and opening that up. Because what we see from a lot of companies is the open source models, but sometimes even their smaller ones. This was sort of the primary one that they were creating. So I think from that perspective, it was really interesting. It also shows a different problem where because the size and scale of it, it's not as I'd say usable by the community, because in order to use a model that size, you definitely need like a really large cluster.

3:25So I think what it's going to do, it's going to show folks that it's going to give people the ideas of what's happening with the larger model. Now they didn't open the data sets that came with it. So in terms of the spectrum of openness they made the weights available but they didn't make the data that was available and that's you know for obvious reasons yeah because it's their proprietary data and they can't do that so other models like facebook's model do they release the data it's trained on or they just say hey we used open crawl or something they show you exactly what it was they used to train it on yeah now when an open source project does that in today's climate where we have a big debate people like friedberg are like yeah you can train on whatever data you want it's on the open web you know it's ridiculous position he has uh that you know nobody has any rights to their content uh when it comes to training data i think it's absurd but you know this is how a lot of googlers think you know he's a former googler and a lot of tech people think is if it's on the open web i can do whatever i want free use right yeah we just if it's on the open web it's fair game which is ridiculous like a lot of things are available in the open web that you just can't take and go leverage um but anyway putting that aside is now the reason why people are not going to share the data is they don't want to open themselves up to hey somebody posted to facebook you know somebody's copyrighted material then it got ingested into the model and now you have let's just take the biggest ip of all time disney marvel star wars somebody put up you know in their g drive or on youtube and hasn't been taken down yet, an Avengers film.

5:04And now you've trained on the Avengers data, which you don't have the right to train. Yeah, I think it's like a big smoking gun in some ways. You know, I didn't get a chance to listen to podcasts, the all in podcast, but I saw it in the show notes. Did you guys talk about the little mishap? Yeah. What was your take when the CTO of OpenAI talked about the training data for Sora? What data was used to train Sora? we used publicly available data and licensed data so videos on youtube i'm actually not sure about that what did you think of her reply there do you think she's lying she doesn't want to set up herself for a lawsuit because she's a cto shouldn't she know the data I was trained on?

5:52Well, that's where I was going to go. You know, if you're maybe talking to someone, even a low-level engineer that's not working on the project, they may or may not know they're working on the code for it. But I think someone in the position that she's in will have a full understanding of all technical aspects of what's happening and then data aspects of what's happening. So, and that's why I think when the question came up, you know, she had some very specific answers and as the interviewer probed it started to get much more uncomfortable yeah um yeah and i think it followed what you were just saying which is well if i can go and i think you know i don't use it this way but i think you can get to instagram via the web now like someone can send you a link and you don't have to open it in instagram yeah yeah and same with youtube right and so i i think what the argument that was being made the way i at least read it was well if you can just get to it on the internet without a login or anything else then it may be inside it's what she's saying it's on the open web by the way a lot of new york times stories are on the open web they don't put everything behind a paywall that is not the just because something's on the open web doesn't mean you have the right to exploit it for commercial benefit let's give two letter grades here what do you grade the cto's response at open ai since we like to give letter grades well look a response in that interview with the wall street journal gets oh the response was not great it was it would probably be you know i'd say like a c you know i think in that home yeah i think oh my god it's a big fail you have to be media trained on that what are they doing at opening night they should say we don't talk about the training data we license data and we use data that's openly available but we don't talk about what data we use that's a perfectly good response that's what i'm saying but we shouldn't blame her for that we can maybe blame the organization you know i think it's like that's what i'm saying great work yeah so yeah i don't want to single her out but yeah yeah the organization failed her and she failed the organization they need to be for this stuff you know the comms organization gets a bad grade oh my god they get fired if there is even if there is a comms group yeah i mean is there a comms group at open air maybe they just don't it sounded to me like an organization that doesn't have a comms group and doesn't speak yeah awfully about these things like you can't wing it when you're open ai and in a lawsuit with the new york times yeah like they're in a lawsuit with the new york times it's it's the this is the content i would say this is the content lawsuit of the century of the past hundred years i did you can't blame the cto though but that's why i said the comms team no i blame her too yeah she's got to think better on her feet and be thoughtful anyway i give it an f you give it a c what what do you give uh the impact of elon and twitter and grok and all this stuff open sourcing x open sourcing i think impact from you know what it means to the community and like advancing open source uh thinking around ai a a you know yeah it's an a plus yeah exactly a plus we can't give it that because like we'd want to see no data right right we'll just give it an agency exactly so you know there's a room to be better yeah and i think this goes back to maybe what the core mission of open ai was supposed to be advanced ai for all of humanity and so by doing something like that it does it does advance things for everyone let's get into other news we got our first two new stories out of the way we'd love to do demos here on ai tuesdays go to this week and startups.com slash ai to get to our playlist of all the ai demos we're doing we're well over 100 now folks yeah so this week we have actually two one that you know we just can't demo unless we maybe get the robot we can go see um the folks are doing it but the first one is figure ai and what i'm going to just show a couple of things here you know obviously i don't have access to this robot but i'd love to go and maybe we can go they're here in the bay area so we can go and see them you know so these folks have created this robot very much like uh you know the the tesla what's the tesla optimist yeah yeah and what they did that was really interesting and i'm just gonna show another video here really quickly this is a real world humanoid robot it is done with two legs two arms a head which why it needs a head makes no sense like what is the purpose of the head except for design i mean you could put all that in the chest i guess so i'm gonna i'm gonna show you why so this in this video it's just like a very short clip you're gonna see that this gentleman is speaking and you standing nearby with your hand on the table.

10:18Great. Can I have something to eat?

10:23Sure thing.

10:29They asked the robot to describe what was on the table. On the table were some plates, some glasses, a dish, rack, but one thing you could possibly eat, an apple. And they did a conversation, so it did voice recognition of him asking, I want something to eat. the robot, assess what's on the table, and I guess assume the only thing edible on the table is the apple. Am I correct? Correct. So we've described it for people who are not watching. If you want to watch, just type in This Week in Startups on YouTube. Navigating the B2B maze can feel really tough, huh? You're trying to hit the mark with all those top-tier executives.

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12:15Go to linkedin.com slash thisweekinstartups to claim your credit. That's linkedin.com slash thisweekinstartups. No spaces, no dashes. Terms and conditions apply because they're giving you a hundy. Why is this impressive? It seems very basic, yet it is kind of impressive. So why should we be super impressed here? Let's go in the following order, right? In terms of like creating human like interaction. I think this is where the head comes in, right? You know, of course you could have done the same thing and you could have had a robot without a head there and it would have been 10 times freakier.

12:46So one is just creating sort of, you know, comfort, I think from a human perspective, making the humans comfortable is why it has a head. Yeah. But two, here's something. And, you know, Elon says this when it comes to FSD, you know, the FSD with no LIDAR arguments or no ultrasonics arguments is he goes, look, we're a human. And, you know, millions of years of our biology have given us two eyes that give us stereoscopic vision. And that's what we can use for depth perception and everything else. And so the argument is, if you mimic the human form, and you give it, you know, two cameras, it has sort of all the features that humans have.

13:23And as you enhance its reasoning capabilities, it can do it the same way that millions of years of our biology landed us having a head with two eyes like this and ears at the side. So these are all evolutionary traits that there's millions of years of biology behind, but we can just copy it immediately and say, well, most likely we put the speaker right here. We put the microphones right here. We put the vision things right here. Biology has already figured out that's the best format. The same way Elon says you can drive a car with your eyes. So a computer should be able to do it just with its eyes yes it's just a matter of the software what the gray matter is in our skulls being able to catch up and that's the language model obviously so here we are starting to see the beginning of a language model being put into a robot now we have obviously the boston dynamics robots doing backflicks getting kicked doing all kinds of very interesting what you would call verticalized software right like very vertical software solutions here's how to walk here's how to pick stuff up what this is doing is very different explain to the audience why this is so different than the boston dynamics incredibly powerful you know demos that we've seen over the last decade and my guess is like this is building on the learnings from what boston dynamics were doing and all those crazy videos and what they were figuring out was movement and they were figuring out movement and stability and agility what now we're bringing into it is what i'd call reasoning.

14:50And in that particular video, you saw the human walk up to a counter and you saw the, you know, the robot have like a, again, the sensors that we have and basically to speak, to listen and to see. And the human said, can you give me something to eat? And the robot be able to reason over what's in front of it and basically decide, you know, this is the thing you should eat. And you can do this in an action of handing to the person. You can do the same thing yourself, right you could take a picture of a table and there could be five things there and say you know uh tell me the thing i should eat exactly and it most likely would tell you the right answer yeah it would and so it's emerging so i'd say boston dynamics was much more on the like physics movement agility side and you need that exactly and now you're bringing the capabilities of these large language models into place to do speech to text and then reasoning and then you text back to speech and then tell the human here you go and then combine that with all the agility stuff to hand the apple to the hand the apple to him because he says what should i eat yeah and it hands it to him so they've programmed the they've additionally programmed that language model to take an action and that i think is the most fascinating part there's no action when you take out your chat chp t4 take a picture of your counter and say what can i eat and it says oh oh, you can eat the apple, you can't eat the spoon and the fork and the plate, but you could eat the apple.

16:19But it said it took the action of handing it to them. So they have built software into this to know to give the apple to the human that the human wants the apple. There's some other code here, right? There is. And so that's a really great question, actually, super insightful, Jake. These LLMs now, they have something called function calling capabilities. And so when you're seeing a lot of the more advanced stuff coming out of builders, what they're doing is they're using the LLM to perform reasoning. And then basically in that reasoning task, they basically allow it to have access to a selection of tools and the LLM decides.

16:57So all of this is usually happening in the background. So if we go through the whole workflow there, and I don't know this for sure, but like I'd say, this is accurate, probably within 95%. It's initially speech to text, right? You got to take what the human says, got to turn that. We've all seen that happen. That's been happening for a long time. Then you got to parse what the human said, what can I eat here? That then triggered a function and say, well, let me take a look at what's in front of me, take a picture of it. And then I can ask the LLM the same question you or I would, is there anything here I should eat?

17:27And then when it says, yes, it figures out there's something there. Then there's probably some function calling that happens as well, based on what else was asked, what should you do next? And if one of its functions is, hand that thing and they could have hundreds or thousands of these yeah and so what's really interesting here is that's most likely what it's done it says one of its function calls if someone asks you for something and you have it we'll give it to that person right now if that had been if i had said what on here is the most explosive item then i said well this nitroglycerin is yeah now does it decide to hand me the nitroglycerin does it decide to hand me the grenade this is guard guardrails right now we're back to guardrails we're back to guardrails right and you know isomoff's rules around robots and not hurting humans right but i don't know this is back to prime directive what is the prime directive of these robots so now science fiction right in in the movie i robot there are directives in the knockoff robocop there are directives right and you can't hurt humans.

18:31So are we to believe that this company has in fact given prime directive to these robots because now it's doing interactions in the world? It must have don't hurt a human in there. So if I was building one of these and it might not be as simple as that, but imagine the whole thing is driven by a prompt. Yeah, there you go. The number one item would be do not hurt a human no matter whatever you do. And then I'd have guardrails outside of even the LLM. This is really fascinating because where this is intersecting again with Tesla is you've seen this in the evolution of FSD 1 through 11 and then 12.

19:11Yes. So the big jump from 11 to 12, which is not a jump because it's a completely different way. Exactly. And so it's odd that it kind of continued the numbers, but they just had to do it, right? Software versioning. But what they did was they went from creating code that was full of all kinds of branching, if this, then that, right? Yep. And there's a stop sign, do this. There's a speed limit, do this. There's a car runs across the road. A child runs across the road, do this. Yeah. To basically an approach that's built off vision and learning by watching the video over and over again. Listen, as a founder, there are things I love doing, like building products or meeting with partners, hanging out with my team and dreaming up new ideas.

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20:27Also payroll taxes. You got to get your taxes right. You can't make mistakes there. And you want to set up open enrollment. You want to be good to your people. Gusto handles onboarding, health insurance, 401k, time tracking, commuter benefits, awful letters, and they even give you access to HR experts. So Gusto takes all of this off your hand and lets you focus on important stuff, your product, and your customers. It's super easy to set up and get started. And if you're moving from another provider gusto will transfer all your data for you here's your call to action because you're a twist listener and you're part of the family you're gonna get three months free incredibly generous totally unnecessary thank you so much to our friends at gusto.com slash twist you must go to gusto again gusto.com slash t-w-i-s-t to get three months free thank you gusto team and so you know i was just watching the gtc keynote earlier that's the big nvidia conference and what someone was saying what jensen sorry now someone was saying in that conference which i'd never thought about before about like how do humans learn and we think about textbooks and you know reading on the internet it's mimicking but one thing he said is like you know a big way we learn is just watching tv so imagine you give that robot you just let it watch tv for you know an amount of time or consume things and so the ability to figure out even what those functions are and then how those functions operate can also become an ai task in and of itself wow so just to pause there for a second insert the clip here of the fifth element when mila jovovich the character wants to learn she just like touches a tv or something and all of a sudden the whole entire history of humanity including the holocaust and the moon landing just every similar thing she learns from a television as well in the movie the matrix it predicts i know kung fu he just watches every kung fu movie ever he watches every martial arts fight scene and now that's in his programming so now we start thinking about science fiction it literally predicted this that you could just watch the history of television all recorded and then learn everything learn wow it's just extraordinary and then all this work that waymo did all this work that tesla did on full self-driving waymo is done doing conditional statements, 100 % of that code is just going to be thrown in the garbage and never used again.

22:47It was all learning up until this point. Now that we have these models, we're just figuring out, hey, what has everybody else done at this intersection? And what would a human do in this intersection? When a bicycle cuts across it, you'd stop. Or how you learned to drive, or I learned to drive the same way, right? We looked at some rules we watch tv for a long time we knew that you shouldn't do x y and z this is crazy yeah hopefully it doesn't watch the french connection for people who are under the age of 40 great scene great scene i mean it's the greatest car chasing ever just type in front connection car scene okay so this robot is um super interesting Like it is going to take time, but because it's a human factor, what's very interesting about picking the human factor is evolution made humans to the dominant species on the planet, right?

23:43So whatever it is, you know, you might look at tigers and say that's more efficient or sharks in the water are more efficient. For some reason, our frail little bodies have done pretty well with the giant brain. Okay, fine. Now you start to think about, well, we also built the modern world. So we built the world, the door behind me, windows, chairs, office spaces, cities, computers. We built these for our form factor, cars, etc. So by building, even if the robot would be better as a little tank with, you know, four wheels or, you know, tall or small or whatever, by building it to be six foot tall or five, ten or whatever the average human is, five, eight probably.

24:28Well, it now can operate in the real world, a factory, a kitchen, a car, you know, walking through a city or a town. So it's kind of brilliant that we're making them to look like us. Yeah. And I think about, you know, one of your great investments, you know, I saw yesterday, I was in the airport, the Cafe X. Cafe X, yes. And think about the evolution for Cafe X, right? Could it be that you can, and I know you guys have done a lot of work with the robot there using the standard machines. How does it fundamentally change if you could use the figure robots and think about sort of all the software that would just fundamentally go away where it's you walk up and say, I'd love a double espresso, you know.

25:13It is obviously the future of it now. I think it would be slower than a purpose built. So we're now talking about narrow AI, verticalized applications versus wide. what optimus and this figure it's called figure this company figure yeah figure ai what they're doing is they're going for that like 10 years from now this thing you could general purpose robot just like you know chat gpt is general purpose or gemini's general purpose that means it's not going to do coffee very it's going to be slow and kludgy it's not going to move wicked fast in a contained space with walls around it that customers can't get in between it so you're going They still use vertical AI to win at chess or to win at making coffee.

26:00But if you were doing a restaurant, man, this robot would be pretty great to work at a holiday inn. Like, literally, you know when there's a holiday inn and they don't have overnight food? Like, this robot would be pretty dope to do that. But the ramen machine would be better at making just perfect ramen, like a verticalized ramen. But it also could be like an expansion for Cafe X. Like, they get it right and you sell them into Starbucks, right? Totally. They want to keep their storefront form factor, and you maybe want to talk to a human. Yeah, drop one of these in. Because, you know, it just increases their throughput.

26:31I mean, it's a brave new world right now, and this is moving at a crazy pace. I mean, looking at this, I think it's like a B. I mean, it's not super impressive to me. They've glued together the LLM and the robot. Congratulations. I'm not blown away yet. but i i am impressed that somebody has finally put a connection together but it's pretty basic i mean if it if it put a bunch of vegetables and fruit on the table and said make me a salad and then it asked me a couple questions like would you like maybe that's a challenge maybe that's a challenge the team that could be a cool thing here's my challenge we can get back i give this a c plus i'm giving this a c plus yes i'm i'm not impressed um with the robot because the robot's not as good as boston dynamics and i'm not impressed with the ai implementation here because it's base basic you get a c plus for plugging the two things together i want to challenge the team put a bunch of stuff on the table and in the refrigerator give it a knife and say make me a salad you make me a salad to my specification i'll be impressed wow that's my a plus so there's your that's it that's your test you're a tough customer that's my turing test what do you give it i i give it an a because i know how hard it is to put the robots together i know how hard it is to make all these things work because i do it day to day but there's a lot of you know i'd love to try one so you know what if if they can reach out or something you want to see if the apple's any good when he hands you the apple no i got i want to you know more experiments right that's just like a two minute video so but i see a lot of potential there you know i see a lot of areas where there can be some improvement like you know the voice reaction was a little bit slow maybe that could go faster but there overall i really like where this goes for and i i do believe i i think elon has said something is like there's gonna be something like 10 billion robots on the planet within the next 30 years of these humanoid robots one for one everybody will have their own robot it'll be like c3p why wouldn't you have a robot i mean if it costs i mean the idea that everybody would own a car was farcical like for a long period of time like why would anybody need that and now everybody has a car like i think there's more cars in the united states than people i don't know if that's that's true or not but so yeah why wouldn't there be i mean if they can get this thing i think they can get these down to 10 20 grand and then it's like buying a used car what would you rather have let me ask it this way would you rather have a robot that could you know do anything a human can do or you'd rather own a prius and you have to take public transportation and have your own robot or you can have a prius and not which would you rather take the i take the robot 100 everybody takes the robot everybody takes the bus and the robot yeah you could have the robot making money for you you'd be like hey you know what go find me you know uh go go pick strawberries go go pick go forage from mushrooms in the you know in portland and come back shovel the snow at my in tahoe in tahoe go shovel the snow right that's i mean it's two bucks has been waiting for this hasn't it yeah robotics has been waiting for this this is going to be bigger than ai itself i think when you think about it like it's like a related though right you know i know but ai without the robot means like the problem set is like uh you know 10 of the problems in the world yeah ai plus robot equals 90 of the problems in the world like i think it is almost everything what what couldn't the robot do like maybe fly or go underwater or maybe there's some problems it can't solve but you know this feels like whoa this is like whoa i'm kind of in the same spot as you i think seeing multiple companies do this, you know, between Boston Dynamics, the Tesla with Optimus, and then these folks, I feel like we're closer than ever.

30:39And I'd be willing to say definitely within three years, people are going to have these at home. Wait, wait, how many years? Within three years. Someone will have them at home. There's a bet. Hold on a second. Yeah. Startups and small businesses, listen up. You want a CRM that neatly organizes all your customer data so that you can avoid missed opportunities and you can deliver a personalized service. Rigid CRMs can adapt to your fast-growing needs, and that's where Ateo comes in. ATTIO delivers the goods. It's a custom CRM that's flexible and deeply intuitive. Ateo is built for the modern company, headed into the next era of businesses.

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31:50replicate and 11 labs and scale your startup to new heights with adio head to adio.com slash twist and you'll get 15 off your first year that's attio.com slash twist let's make this a proper bet we got a new bet alert this week in startups.com slash bets is where all the bets on the show are being put we got to go back to the um now that we have ai indexing the whole site we need to go back and find alexis ohanny and original bet but look at this this was this company root ai that got bought yeah yeah yeah um unfortunately it was like with the spact company and i think it went to zero okay yeah which kind of sucks but look at this robot yes zip zip zipping this is three years ago picking tomatoes and you know the hand is just perfectly designed for this and it's using computer vision and this is before llms were in the mix this is a verticalized you know application but look at how precisely it can go pick cherry tomatoes or it can do raspberries and strawberries here it's doing bell peppers as well yeah and so this idea that you would actually pick vegetables is going to be over soon now this thing only worked in vertical farms so you see this is an indoor it's not out in the field and it's not the dimensions of a of a human because you need a different type of hand but if you had the optimus or this future one you could take the it could take its own hand off of course yeah and put the regular hand on right so what's your bet frame a bet here come on i want to get a little okay well i just want to comment on that thing so what's going to happen is the same thing that's happened with llaps right where it's become a superpower and what people are going to do is the robot's going to be the blank canvas and then people are going the people are going to program them and prompt them there'll be a lot of different ways that they'll operate with them.

33:40And so the amount of energy it took to create that robot that you just showed us was immense. An amount of engineering and testing. And then you had this kind of had to adapt it to a certain form factor for it to work. But going back to where we started this conversation, if you have a robot in a form factor of a human, which means a human should be able to walk there and go and pick tomatoes, cherry tomatoes, and you give it the slight difference in the hand like a tool i think we're going to see that very very quickly so coming back to the bet i think what we'll see is yeah within okay here's the bet this is a it's gonna be their biggest one yet okay within within three years so at the end so 2027 end of end of 24 25 26 beginning of 2027 you will be able to get one of these for yourself okay january 1st 2027 seven yep a humanoid robot will be available for purchase yes and delivery yes you can have it in your home you can buy and have it in your home by january 1st 2027 27 okay and you're asking the bet is no the bet is i take the over the under is my well you take over under okay and whoever's right the other person buys the robot for that person up to a cap of ten thousand dollars for the robot let's say like 25 i think they're gonna be wow this is a big major it's a big bet yeah it's a big bet but you're setting the line so i pick yes so do we have to put the dollar amount of the robot in there like that's just a cap like if they're if they're you can buy them because i would think if you went and you offered a hundred thousand it would be because i'm yeah you're saying january 1st 2027 in america yeah around the price of a prius around the price of a prius for the price of a prius an entry-level price okay so now we got something to pin it off of for the price of the entry model the cheapest prius yes um so we could have two bets here the over under on the price and the date so we could do those so i'll go first i'll pick the date okay you pick the over under on the price of the item yeah which is a prius which i think right now an entry-level prius somebody can look it up but i think that's probably like 40k yeah i was gonna say 35 40 000 seems right 45 i don't know anyway we know we're kind of where it is all right so i'm gonna take the under on january 1st 2027 for 10k and then you take 10k of the bet for the over under on the price entry level prius the cheapest prius new you can buy yeah you think it's going to be over under that price under under oh i think you made a bad bet so i have the over okay i think it's going to be like 50 grand for these 75 no way no way really no way okay it's entry the entry price of the robot versus the entry price of the prius which i think is have a look at these things i think these things are the equivalent of a prius and i think it's got to be before january 1st 2027 gotta be it's got I mean, an Apple Vision Pro, which has all the brain and sensors, is only$3 ,000.

36:56This is the largest bet in the history of This Week in Service. There's$20 ,000 on the line here. It's a big bet. $10 ,000 and$10 ,000. I mean, it could cancel out. Or somebody could sweep$20 ,000. Yeah. Oh, my. What are we doing here on this podcast? I don't know. I mean, this is getting out of control. Our poker game is making its way into this. It's making its way into this. I mean, are we doing this podcast in order to place bets? Feels like it. And that's okay. We're making it interesting for us. We have a bet that now is going to go through the rest of 24, 25, and 26. So it's a two and a half year bet, folks.

37:29It's almost a three year bet here. But I like it. We'll be sitting here with more gray hair. Yeah. And yeah. Yeah. So I give this thing a C plus as done here. I want to see you guys make a salad. Okay. I think if my salad challenge. I think they should come on the show. Yeah. and maybe or we can go on site and see what it can do on site and see him make a salad that's like a real life because we haven't done one of those yet with someone let's go do it on site yeah i can get somebody like uh to do like a really good like get it we get a red camera or one of those like really good hd cameras we'll get makeup we'll get some old man makeup going yeah okay i like it all right let's do another demo and then we'll wrap here we got a lot done today well the next one i want to talk about as well it's not a demo and then i have an actual demo.

38:11All topics today. I know I have four queued up, but these are big ones. Okay. So you remember last year, you were starting to get excited about auto GPTs. Yes. This was baby GPTs and auto GPTs. Yes, exactly. So this company, which was founded by a couple of amazing engineers, the CEO is this guy, Scott Wu. Interesting background. This guy was a competitive coder. And so he had won competitions doing competitive coding. Incredible. And what this team did was they basically took the idea of auto GPTs and they really took it to the next level. And there's a few examples here. I'm not going to play the videos because I think everybody has seen it at this point.

38:57If you haven't seen this yet. This is Devin. This is Devin. Yeah. But what they did, which I thought was, and it's really, really insightful. everybody else was using auto gpts in a very constrained box like either in a terminal or something like that and it could kind of figure things out but it was really hard for it to think holistically what they did was they kind of flipped it around in my opinion they gave devon an ide that was built so it's an integrated development environment so it has access to code it has access to a terminal this would be like replet great example they basically gave it a custom replet that their ai can drive and so by giving that the auto gpt and in their case devon had you know access to much more uh much different set of tools so it's much more powerful and so because of that and then they obviously took a model and they fine-tuned it did all the good stuff and a great scoring on that model they really broke through what i believe was the barrier in the you know you sit down somewhere and you're like hey i want to make a site that basically does news and this is how it should work and all those kinds of things.

40:05And so they, in their IDE, have like a chatbot, they have a terminal, they have a web browser, they have all the pieces that you need to go off and do this. And so I really think that they've done something incredible here for that particular evolution of like the auto GPT style of applications. Yeah, it's super impressive. And this is the future. I think, you know, we have verticalized apps. Okay, I can beat, you know, Big Blue, Chess, I can be Kasparov. Great. Really programmed well. Okay, what's next? Co-pilot. Okay, really interesting. I'm working, the co-pilot's finishing my sentence, giving me an outline of my blog post or working with me on my code.

40:48And then we're going to agents, right? We called them baby GPTs when we started this journey. Yeah. But basically, it's a role. It is a worker. And so, the way we should think about this is, we don't use the term slave anymore i also got corrected by the way the language police i call something a master bedroom you can't really can't call it a master bedroom anymore because it's oh wow okay i hadn't thought about that so uh i think they call it primary so now they're calling it primary rooms okay i get it um and so but essentially you're creating a slave right and And that's what they used to call these things in programming code, right?

41:27You have this slave. So this is like a role. I'm going to just call it a role, a job function. And if this thing can operate through a role, what I described on the last all in on the one before was what I believe will be what I'll call maestro. The maestro is coming, the conductor. Oh, great name. Great name. Yeah. So the maestro is coming. And what the maestro is going to do is I'm running my one person company. And I just say, Okay, I need a developer. Oh, I need a little designer over here. Okay, I need a copywriter over here. And then what is my job every day? Well, I'm sitting there with these roles, right with these agents.

42:09And I've got these virtual employees. And I'm just pushing them along. Hey, show me a new design for that app. Hey, I want to add, you know, to this app uh twitter login and google login right now we log in through phone but i want to add the google login code boom it does it okay hey copy team let's write a blog post about this and do a tweet okay boom we got that queued up okay now i want everybody to build the launch plan give me the plan that we're going to launch this new you know login with google and i want to press release okay boom and it's like whoa now we start thinking about what would modern day entrepreneurship shipping it's going to be being the maestro maestro you're just going to be a maestro with a bunch of virtual assistants and then you might bring somebody in and so there's going to be a new class of company i predict uh where it will come in and it will be like hey you're using this ai to make your marketing plan so we're going to have a human review it with them right a marketing maestro now you got a marketing maestro at the company what do they do okay they got the copywriter ai they have the ad buying ai they've got the you know uh logo and the brand building ai you know the tone of voice ai the social media i mean this is going to get really interesting and i think this is where we get to a 10 person company you know making 100 million dollars each employee makes 10 million dollars and then you get 10 person company 100 million in revenue equals a unicorn right 10 times revenue and what would the margin on that company If you pay each of those people a million dollars a year, because why not?