# New AI Agent, GPT-5 Not That Good? 100 Billion Humanoid Robots, Mixutre Of AGENTS And More

## Метаданные

- **Канал:** TheAIGRID
- **YouTube:** https://www.youtube.com/watch?v=_MWfbCwlKfM
- **Дата:** 18.06.2024
- **Длительность:** 28:31
- **Просмотры:** 24,598

## Описание

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Links From Todays Video:
https://www.together.ai/blog/together-moa 
https://x.com/BenjaminDEKR/status/1801410715263373652 
https://x.com/ZetaLabsAI/status/1801298387335106719 
https://x.com/tsarnick/status/1801425561396646393 
https://humanoid-ai.github.io/ 

00:20 HumanPlus
06:49 Elon Musk Robots
11:48 New AI Agent Demo
16:08 OpenAI NSA
20:04 GPT-5 Not that good?
23:55 Mixture of agents

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## Содержание

### [0:20](https://www.youtube.com/watch?v=_MWfbCwlKfM&t=20s) HumanPlus

Stanford University basically Stanford University did a collaboration with Google Deep Mind before if you remember earlier this year they did the mobile Aloha thing that was a very interesting project where they demonstrated the ability for robots to do autonomous tasks now essentially what they're doing here is a different kind of thing which is along the same kind of guidelines and this is human plus so they essentially have a humanoid robot and they're trying to make them perform various tasks by imitating human actions this involves creating a system where robots can actually observe and mimic human movements and then use that data to perform the Tas asks autonomously so this is an entirely new pipeline of training autonomous robots using an RGB camera that actually allows you to observe human body and hand movements in real time and then that's how they collect the data so essentially the human motion data is collected using Advanced pose estimation algorithms and the robot then actually Shadows these movements using a policy trained in a simulation environment and right here you could actually see that this is the RGB camera where this is it observing the actual human in action right there so it's not the camera's on its head but this camera right here that is you know enabling it to Shadow it and this actually funnny enough kind of gives me some Real Steel kind of Vibes for any of you that have actually seen that movie before so once you have this single RGB camera that is able to you know Shadow humans you can see the camera is once again located in this area here and of course the robot is then doing those actions you can see in this scene that the camera is obviously located right here it's actually pretty hard to see and the base model that they've actually used on this thing funnily enough is actually a unitary robot I do remember when they released this robot I think this is the unitary H1 and this is of course an earlier model which goes to show the speed at which robotics advancements can allow for universities to be able to I guess you could say you know use them and actually see how effective they are now one of the things that they actually did talk about is they did actually talk about I didn't mean to pause it there but they did actually talk about how the fact that this robot doesn't actually have a lot of degrees of freedom so essentially what that means is that the unitary robot that they're using it doesn't you know like have the same range of motion that humans have like humans have a lot like a lot like a huge range of motion like your shoulder joints are incredibly you know flexible and you can you know rotate them in you know various different ways but this kind of robot it wasn't really built for those kinds of things so it's quite hard to do a lot of these tasks because the robot is very rigid in nature however it's not stopping them from being able to you know train certain tasks and then of course get policies that actually work effectively so the realtime teleoperation thing that they're doing here this is where they're basically Gathering data because um you know teleoperation in the other way is actually quite you know hard to do so they're essentially inventing a new way for teleoperation data to be captured um and of course you can see on the top of the you know on the robot there it actually does look like eyes of the robot like finally enough it looks like a kind of droid but these are just robots that they're using to of course capture the data and essentially a low-level policy is trained using reinforcement learning on a large data set of human motion which is actually 40 hours of diverse human activities and I think when you go onto the actual website the GitHub you can see that um the autonomous tasks that it's learned here are actually quite impressive now of course by the standard of the average person cuz one thing that I do find interesting is that I do sometimes like to show people what's going on and this is people that have literally no interest in robotics or AI because I want to see uh you know how they um look at you know Robotics and how it's done but you can see that you know some of these ones autonomously do actually look pretty interesting I do have to say folding clothes is definitely very hard you can see right here this one I think it was rather impressive you've got a high jump which is completely autonomous the robot is able to perform a jumping motion and then of course able to stabilize itself after the resulting you know forces have acted on it which is pretty hard considering that this robot is like super rigid so the fact that it's able to do this with not the best kind of movement is rather impressive um and all of these are fully autonomous so this is the robot executing based on the policies is previously learned so this is not teleoperated at all this is fully 100% you know automated uh I guess you could say so right here you can see this is the warehouse autonomous and then of course we have you know unseen objects right here which is rather effective so it looks like we are you know in a nice area and this is you know the previous mobile Aloha in a you know I guess you could say the teleoperation mode so overall it shows that there is a level of innovation going on at this lab that I think is really interesting and I'm always intrigued to see what you know teams that do some really effective stuff come up with again and again because it shows you know a nice track record of the fact that they're continually you know innovating on new methods so this is something really interesting now for the future what I would love to see is that the autonomous skills on a different Hardware platform for example unit's newest robot I would love to see you know some of the new policies trained on that because the robot is a lot more smooth it's you know it's got more degrees of freedom it's able to do a wide range of tasks and I'm thinking that if we can get robots that are you know this effective you guys can see right here like if it's this effective you know jumping or whatnot on such a limited platform um not not to you know hate on the platform or whatever it is still pretty good but I'm stating that when we get to True areas where we have you know true cheap robots that are flexible and we're able to use those for research I think that's when you know things are going to be getting very incredible and very futuristic because it's going to a truly advanced level of research that we can you know explore with these robots so autonomous humanoid shadowing imitation from humans I think human plus is fascinating now here's where we have a very fascinating thing and this is Elon Musk actually speaking about the Tesla Optimus so I chose this story to be next because I wanted to you know

### [6:49](https://www.youtube.com/watch?v=_MWfbCwlKfM&t=409s) Elon Musk Robots

transition smoothly from the previous story on how we just spoke about humanoid robots doing some tasks autonomously this is where Elon Musk actually speaks about the future of humanoid robotics now I do want to sayate there's a quick caveat to this because of course Elon Musk has been known to I wouldn't say exaggerate his timelines as some people would put it but I would say he's pretty ambitious within you know what he wants to achieve in a short amount of time so in this clip he basically talks about humanoid robots and being able to produce 100 million per year and those doing pretty much every task that you can imagine on Earth and Elon Musk has said some pretty ambitious things before but I think that with the rate that technolog is improving I don't think 100 million is going to be pretty easy but I do think that once certain you know like levels of AI are achieved like embodied AGI I don't think that this is you know completely out of the spectrum within the next 10 years I would say or at least 20 years so I think you know things are going to be drastic but um take a look because it's pretty fascinating uh when you think about the Optimus uh robot which is really a humanoid robot that is intended to um you know be able to do anything you wanted to do to be uh you know it's uh you know your companion it can be at your house it can sort of uh babysit your kids it could teach him uh be a teacher um it you know it can do Factory stuff like I think that the ultimate ratio of say how many super useful humanoid helper Droids do you want like who doesn't want a C3PO you know um uh you know but a c3p plus R2-D2 plus you know Plus+ would be pretty awesome uh I think everyone in the world is going to want one like literally everyone and then there'll be obviously uh robots in Industry um making stuff and so I mean I think the ratio of humanoid robots to humans will probably at least two to one something like that one: one for sure so which means like somewhere on the order of 10 billion uh humanoid robots um maybe 20 or 30 um and so then it's like okay well let's say you know you kind of make let's say the build rate is I think the build rate will be probably something ultimately like a billion a year humanoid robots like actually and if Tesla just has a 10% share of that and it might be a lot more than 10% um and there's you know we make like 100 million Optimus units a year and just I mean for reference the Auto industry is roughly 100 million vehicles per year um so that you know sort of similar bpark at least within an order of vitude I like I think we could make one for a cost of maybe at at really high scale of about $10,000 it's it's smaller it's be less expensive than a car so uh and I think if you sld for sell for $20,000 something this is at Large Scale volume um Tesla would basically make about a trillion dollars of now profit a year is pretty insane but um yeah I guess I guess we're going to have to see because a lot of the things in the future that are based on I wouldn't say baseless claims like some angry commenters do say I've seen that on various different forums and you know tweets and stuff like that but um yeah I mean we have to understand that the future is going to get pretty crazy in the future because if we actually you know look into the future and say okay let's say we have like AGI like a real AGI and it's actually embodied and it's actually able to do stuff how valuable would that be would it be more valuable than the car and honestly I think at that level like at where society would be I do think it would be more valuable than a car because I think that you know having your own you know person basically for $220,000 that can do pretty much anything that's going to be you know smarter than you it could you know uh clean your house whenever you wanted not like there's not going to be some specializ M made version of it but I do think that you know having that around um you know is going to be kind of interesting because I do think there's probably going to be specialized version whether they're like you know girlfriend robots or you know husband robots but I definitely feel like where the way Society is going to be um they're definitely going to be like employed it's probably mainly B2B where Tesla you know um has them working in factories and they're just deployed for maybe like government projects to build more data centers or you know to build more companies for new projects whether it be you know Dyson spheres I don't want to get into you know some crazy stuff but the point is that if we actually imagine a future where you know a Tesla humanoid robot is as good as the average human or like let's say 20% better with their hands I mean you have to think about how quickly you know Society is going to evolve because we can just you know basically okay just hear me out for a second you can basically like print employees that would work 24/7 and do whatever you want that would need any breaks and wouldn't get sick so you have to think about that uh on a really high level and those employees can even make more employees so pretty crazy stuff when you start to think about how this Gale of this could be over the next decade or even 20 years so now this is something that actually caught me off guard some former meta researchers actually released a new agent and this was actually rather impressive I'm going

### [11:48](https://www.youtube.com/watch?v=_MWfbCwlKfM&t=708s) New AI Agent Demo

to show you guys the demo and then I'm going to give my opinions cuz I do think that this is going to be the year of Agents but this surprised me because I think okay and maybe just maybe I think that what's going on right now is that you know other companies are starting to catch up to open Ai and starting to eat into their market share not that this is that big in terms they didn't get that much of a reception on social media but the point I'm trying to make is that this is something that I thought that I would see open a ey demo first but I guess they're still doing iterative deployment but anyways Z Labs Chase hi I'm Frederick co-founder of Zeta laabs I'm here to introduce Jace your AI coworker with just one instruction Jace can handle any task for you for example Jays can plan a full-fledged trip it will ask you for all the necessary details and make all reservations for you this is possible thanks to our autonomous web agent one model a one with a one Jays can control and perform actions in a browser just like a human would let's take a look at the first few steps in the Life View jce is starting on Google going to the Airbnb website entering all the details and clicking search Jace isn't just an assistant it can take on entire roles imagine a recruiter who never sleeps Jace finds candidates schedules interviews and manages the hiring process effortlessly while using Jace we quickly realized we could take it a step further so we asked Jace to create a company on its own with a simple prompt it created a plan registered the business found the first client and made its first Revenue Jay still has its limitations it can struggle with complicated tasks and the current browsing speed is somewhat slow we are working very hard to make it faster and more reliable we can't wait to see how Jace will help you in your life so I mean the L claim on the video is pretty crazy if it was true because they said this was an agent that was able to create an LLC um you can see here it you know you can see like it's being able to plan it out and I think the reason I think this is going to get a lot crazier is because a lot of the information that we have about AI agents and what they're going to be able to do the problem right now which is why you know a lot of startups like I think it's aept AI that you haven't really seen many you know announcements from um on real on really good stuff is because agents struggle with planning like they just struggle with multi-step reasoning and multi-step planning so I think if we do have a model like GPT 5 that is able to solve that then this thing right here is going to get really crazy but you can see it's able to do some very interesting things you can see here are some of the best registered agent Services you can see registered agent this this what whatever um and then it says appoint your registered agent for LLC um and then you can see these are all of the things that it was able to do so I mean it's going to be kind of interesting to see if this is something that actually works if you do go onto their web page you can actually join the wait list but I don't expect this to be open anytime soon like I've seen a lot of uh AI agent things at the moment but I do know that unless you kind of I wouldn't say invent a new architecture but like you're truly training a new model or you kind of do something truly Innovative um you know things aren't going to get crazy just yet but I do think that by next year this time we will have probably um really really capable agents that are able to do quite a lot because from what we've seen certain Frameworks even surrounding the llm technologies that we have today do provide like a noticeable jump just from the base level of GPT 4 so with whatever next model does get released which whatever model is at the frontier um standard I think it's going to be interesting to see where these agents are placed in the hierarchy now something that was I want to say a surprise but in hindsight it's not a surprise because we kind of knew this was going to happen so openai actually

### [16:08](https://www.youtube.com/watch?v=_MWfbCwlKfM&t=968s) OpenAI NSA

added a former National Security Agency to its board so you can see that this guy is pretty pivotal in things and the reason I say that this was something that is a surprise but also isn't a surprise because recently in a interview on the Dual crash Patel podcast Leopold Ash brener the former openai employee that did an entire essay on the future of AGI and artificial superintelligence and how we're probably going to get to AGI by 2027 actually said that labs are going to be nationalized which essentially just means that there's going to be quite a lot of government oversight and right here we can see that this is probably one of the first steps we have someone who basically was very connected in US Government now working at open AI so this is a pivotal piece of information because it goes to show that some of the predictions from Leopold Ashen Brenner's interview and of course his document on the future of artificial intelligence are already coming true not only a week after they were released but this is always something that you know a few people including myself have echoed in the community because if you just think about like the future of where these systems are going to get to these systems will shift the dynamic of power to whoever who holds them and that you know sets a remarkable standard for what is going to be necessary in order to actually take control of these systems and in order to ensure that they don't pose any threat to National Security and of course the public there are a lot of people who are discussing these claims on Twitter you can see kim. com says open AI just hired the guy who was in charge of mass surveillance at the NSA he outsourced the elite legal Mass spying against Americans to British spy agencies to circumvent US law he gave them unlimited spying to us networks tells you all you need to know about open AI this is referring to the huge drama that happened previously with the NSA when basically we found out that the National Security Agency was basically just spying on Americans on their conversations on the phone and there was this huge entire thing don't really wanted to get into all of that but it's big point but overall this doesn't come of any surprise I mean like I said before I do also believe that you know how we currently get these leaks or whatever I do believe that by like 2025 I don't believe that we're going to be getting any leaks about future models I know that it might seem like it but I just think that by the time these labs are nationalized and you know the true scale of these things are realized this is going to be some kind of Manhattan Project where the majority of the information is going to be under serious lock and key meaning that unless your security clearance is above a certain level you are not going to have access to what the next level of systems are being you know are being done and there's probably even some projects Manhattan going on right now with an open AI that we have no idea about and if you're not sure what project Manhattan was basically it was a secret basically Town SL facility where they developed the first nuclear bomb and of course they had to do this in secret because they needed to get to it before other countries did and with the way timelines are going right now I mean it would make sense for there to be some kind of not National Security effort but some kind of effort in order to create AGI as quick as possible maybe in some field somewhere maybe not a Los Alamos but if you watched open Hina you would know about this um but maybe somewhere in America and I I truly do believe that because it does make sense some people would even argue that whoever gets to ASI first is going to control the world and that's something that's been ushered by people who do work at open AI so this kind of trend is going to continue now here's where we had something that was a little bit confusing because this was a clip from MMA not MMA miror morati and essentially

### [20:04](https://www.youtube.com/watch?v=_MWfbCwlKfM&t=1204s) GPT-5 Not that good?

what she said in this clip confused a lot of people because she said that inside the labs the models that they have are not that far ahead from the ones that are you know out in the public but listen to what she says because I'm going to play it once then I'm going to replay it to you because I think there might be a mistake on the majority of people's part who are interpreting this clip inside the labs we have these capable models and you know they're not that far ahead from what the public has access to for free and that's a completely different trajectory for bringing technology into the world that what we've seen historically and it's a great opportunity because it brings people along it gives them uh intuitive sense for the capabilities and risks and allows people to prepare for the Advent of this of bringing Advan AI into the world and obviously the opportunities are huge now it's normal that we talk a lot about the risks uh because they're so important so basically this clip here has a lot of people you know I guess you could say rattled because they're thinking wait a minute I thought opening eye was so far ahead of everyone else that you know they were on GPT 5 and GPT 6 according to a lot of the leaks and according to you know just thinking that if open AI had gbd4 in 2022 in 2024 they must have a truly Advanced model now maybe sheima spoke maybe this isn't true but I think either one thing has happened here either she spoke the truth about what she's seen or potentially just maybe there could be some overhype going on okay and I don't know okay I think on one hand I think the most likely thing that's going on here is that and I know this didn't mean to drop that but I know that this doesn't seem likely but I do think that it's just potentially just poor communication from open AI one of the things that we actually you know got to see from open ai's recent fiascos from in the past 12 months is that a lot of the times people don't even know what's going on at this company and it's crazy to say that but there are a lot of things that go on between the CEOs CEO like even when Sam out one was fired a lot of people didn't even see that coming of course there might be a separate board issue but there were so many different isolated incidents that I think you know even if this statement is true I still do think that they are probably working on some super Advanced models that you know maybe she wasn't thinking about at the moment in time not to say that she's completely wrong but I just think the fact that if we saw you know not only yesterday the day before that the months leading up to this that you know people such as Microsoft CTO was literally stating that GPT 5 from what he's seen has been like the level of a PhD researcher it could be able to do your PhD and then samman saying that gp4 is dumb and then many other you know opena employees very much so hinting at the fact that GPT 5 is going to be a remarkable jump and Sam Alman stating that the jump is going to be quite similar I mean stating that there's not that much to advance right now I mean there's quite a disconnect there but the only thing that we can truly say is that when GPT 5 or whatever Next Level system is released then we're truly going to know what these systems are capable of or if we've hit the plateau because right now that that statement is definitely confusing and I guess we'll have to see if there is a plateau or what opening eye is truly doing so it will be interesting to see if this statement does hold up but I'm not paying too much attention to it because this it hasn't been the overall theme from just the many sources that I've seen that have operated on open AI so will be interesting to see exactly how this progresses so then we had

### [23:55](https://www.youtube.com/watch?v=_MWfbCwlKfM&t=1435s) Mixture of agents

something here that I think was truly fascinating because this once again another reference to Leopold Ashen brener shows that you know the kind of scaffolding and all these kinds of other techniques that you can apply on top of large language models can effectively be used in order to push them further ahead in terms of their capability so right here you can see that say we introduce mixture of agents and approach to harness the Collective Strength of multiple llms to improve state-of-the-art quality and we provide a reference implementation together mixture of the Arts which leverages several open- Source llm agents to achieve a score of 65. 1% on alpaca EV valve 2. 0 surpassing the prior leader GPT 4 the long story short here guys is that basically they had and they use these open source models to surpass GPT 40 on this pretty difficult Benchmark so that is pretty crazy guys they used open- Source models they basically just used an entirely new framework of I guess you could say interacting with these models and in doing so they managed to push the bar ahead and guys they weren't even using models like Gemini Claude and GPT 4 these were open source models which aren't anywhere near the level of GPT 4 so how did this work so basically what they did was they used a mixture of Agents you can kind of think of it as like this so basically we're going to get into that in a minute but you can see right here you can see that the comparisons between the single model versus the other kinds of models is pretty intense so what you can see right here guys is that we have okay the single model right here and this is in yellow you can see that the yellow okay is a lot less than the blue and the blue is with the responses from the other models so basically overall they were able to improve the responses of these models by combining their effectiveness together to get further and you guys can see that there is a huge inrease increase in these kind of gaps where these models actually work so this kind of thing is very effective but how on Earth did this work so basically what they did they decided to kind of like organize these robots into layers you can see right here that we have layer one then we have Layer Two three and then we have layer four and basically what you essentially have here is you organize these llms in these areas so you can see right here what you have is an open source here an open source AI here and then essentially you can see the outputs and then fed back in to the same layer and then they do that three times and then you get the final output so you have your prompt here you might be liking you know why is the sky blue then you have three of the llms they all three contribute to an answer that is then given to a synthesizer so basically what a synthesizer is you can see right here basically a synthesizer or an aggregator these models synthesize the different responses from the proposed into a single high quality response so basically you just have one I guess you can say AI system that looks at all of them and then it says okay I'm going to combine all of these and then give it into you know some more information and then from that information three of them do a lot again so one layer of information is passed to the next layer of AIS and then the second layer looks at all the answers from the first layer and tries to come up with a better answer by combining the best part of each one and then they do this again and they're able to literally beat GPT 40 on this Benchmark with open source models so this is pretty incredible I know there's probably going to be some videos about this I might even make a further video about this cuz I think this does deserve you know a bit more attention but it was something that I did want to include on this video cuz it was pretty crazy testing 1212 this is to hear what the sh microphone sounds like again in Virtual cam 2 now if you're someone who's serious about the AI Revolution don't forget to check out my post AI preparedness Community currently you're going to get access to my post AI framework my personal strategy for making money with AI and of course exclusive tutorials like how you can actually use agent based Frameworks that are actually pretty easy to use and of course the AGI proof Investments that I'm going to be making so I'm not economically unvaluable that sounds useful to you don't forget to check out the link in the description but that being said hopefully you all enjoyed this video

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*Источник: https://ekstraktznaniy.ru/video/14240*