OpenAI's Leaked INTERNAL AI AGENTS,,New Custom OpenAI Models, Google Research, A.I GENERATED GAMES,

so with another crazy week or slash day in artificial intelligence this video is going to cover some of the most pressing stories that you most likely did Miss so let's not waste any time one of the first things that was actually rather fascinating is the I wouldn't say

Discovery but the talk and they speak about the Sora model even though the opening ey Sora model hasn't been released yet there is still a lot of information surrounding that model that is shrouded in controversy and one of those things is of course the training data for this model so if you don't know when these AI models are made they have vast amounts of training data that they usually scrape from the internet and in this article right here you could see that it says open eye training Sora on YouTube videos would violate the platform's rules in a interview with Bloomberg Youtube CEO Neil Mohan doesn't confirm whether openai used YouTube videos to train its text to video AI model but he says it would be a clear violation of the platforms if it did he states that and I can't show the clip for copyright reasons but he says that when a Creator uploads their hard work to our platform they have certain expectations one of those expectations is that the terms of service is going to be abided by it does not allow for things like transcripts or video bits to be downloaded um and then the crazy thing as well was that you know last month and the reason that why this is such I wouldn't say huge debate but the reason I I would say that you know a lot of people were discussing this is because the last time that this was a thing okay and there was a interview with Mira morati on the inner workings of Sora when asked about the training data Mira morati said that she didn't know where the training data was from she made a weird face people have been making memes about it um and it's been something that you know has just been widely discussed as uh like I wouldn't say a shot at open a ey but I would say it it's something that people are continuing to question because of course as you know before with darly 3 and all these mid journey and you know previous AI systems people are wondering where did you get your artwork from and you know are you going to be impacting artists with this especially with video creators it's like you know when you upload your content you have a certain rights and uh you know things that you know other people should abide by and it's like you know if you're open Ai and you're able to train an entire model of all of this video data where was that video data sourced from so it's quite controversial at the moment one of the things that I don't think open would do anyways is release where they got the training data from so I think even if open was going to you know get sued by someone they would have to like you know get access to Sora try and back test it against so certain videos and try and recreate those videos with Sora to see if there was any I guess you could say similarities in those videos and I guess that's probably going to be the only way now I don't think Google is petty enough to go after open AI for this kind of thing but you never know because as the O as the race heats up it is really crazy and we know that Elon Musk is currently going after open AI for various things so um I guess it will be interesting to see how this thing kind of plays out because training data whilst it isn't the biggest debate it is a big debate in Sora because the video model is really good um and people are wondering how they got it to be so with that being said uh let me know what you think about that training data at

the back next in AI news we had Co here introducing command R A state-of-the-art retrieval augmented generation optimized large language model to tackle entreprise grade workloads and speak languages of global businesses says r series model is now available on Microsoft Zer and coming soon to additional Cloud providers you can see currently the benchmarks in RG are state of the-art which essentially means that this is the best model out there now if you don't know what this model is and essentially how it's uh different from gbt 4 basically this model is something that is I wouldn't say hallucination free but it is you know it kind of steers into that area where businesses need to work with their private data offline or you know for privacy reasons and essentially they just want to be able to have Business Solutions with that data that are really effective so one of the key differentiators between this and GPT 4 is that this optimization allows for in-depth analysis of documents that enables the model to deliver millions of answers efficiently and essentially you know a command R is built to specifically excel in you know RG and Tool use and RG enhances the model's ability to access private data to power applications while the tool use feature actually allows it to interact with external tools and databases enabling a richer set of behaviors now the performance and scalability of command R are also pretty effective we've seen that it is often more effective sometimes than the base model that GPT series usually has like gbt 3. 5 or gbt 4 it's usually uh quite a lot better than that and in addition there is also very competitive pricing um essentially command is usually cheaper than opening eyes GPT 4 Turbo making it a really attractive option for Enterprises looking to deploy AI Solutions at scale without you know in incurring those high costs usually come with calling the model several times like I said before it's basically you know basically hallucination free I mean it's not but it's pretty much there now there was actually a very interesting paper

that was called mixture of De paper and this thread kind of explains why it's so important and the tldr which is the two long than read is basically that this paper just allows you to use less comput for these same kind of questions so essentially right here this guy breaks it down he basically says um why Google's Deep Mind mixture of depth paper and more generally Dynamic compute methods matter most of the compute is wasted because not equally not all tokens are as equally um hard to predict says for example you need a lot more compute to figure out what is in the first token after full stop if you think about it planning the next sentence is a much harder problem than placing a punctuation and this is pretty much true it's kind of like similar to how humans think and it says in the ideal case the model should only allocate the exact Computing needs to accurately predict a token there is long and Rich research Behind these ideas and this is what Google D mind showed with llm Transformers he said it's anagist to mixture of experts that was essentially where you have you know smaller AI systems um that have domain expertise in for example maybe math maybe coding and then you essentially have that all combined into one giant model and that is able to be very effective at pretty much any task because you have you know six smaller experts or eight smaller experts that are fine-tuned on that specific area and it's able to do really well and he basically says that you know it's pretty similar to that um and essentially you know it it's able to skip layers and in the orange area right here you can see that this is where compute savings are had and then this is where he talks about uh the savings are

further compounded when paired with mixture of experts and we're entering an era of scalable compute of llms tokens will not have fixed cost the machine will take the time to it needs to think massive improvements for both GPU rich GBU P so essentially it's like you know certain questions are going to be weighted differently than other questions and I've always thought that this does make sense because simple questions do like have simple answers and those are a lot easier to predict but um you know with a mixture of Experts of course you're saving compute because you're not using the entire llm you're just using a subsection of that and then you know with this new thing where you're using a mixture of depths you can see that you know as the like the compute you know the compute cost is just continually going down which is um really good to see because like I said before what people don't realize is that yes whilst we do need uh faster chips and faster a systems I can't remember where I read this ages ago but it's basically like uh I wouldn't say a high of mind but just if you think about every single you know piece of software every single GPU all of those things around AI are making maybe 5% improvements a month and because all of these things are improving at small areas you do get essentially a huge benefit over the long time and that's why these exponential growths can happen because if we now can have a system that you know uses less compute maybe it loses 20% 5% 10% less you know you can now start to do even more things on top of that find out more solutions and it's just overall it's not self-improving but it is something that is compounding which is really good because it now means that you're allowed to get more out in terms of output in terms of the compute that you actually have then we had Microsoft's

official blog and we had a breakthrough in some Computing I wouldn't say breakthrough but you know they just been uh getting really good at being able to do this so essentially what we have here is Microsoft and Quantum have made a big step towards Quantum Computing they've basically created the most reliable logical Cubit so far and cubits are the basic units of information in Quantum Computing similar to bits in regular computers but much more powerful logical cubits are actually made from multiple physical bits cubits and are actually less prone to errors making them more reliable for complex calculations and this is actually pretty imp important because this development is a big deal because it actually moves us closer to building supercomputers that can handle reliably complex problems that are much faster than today's computers and these could include finding new ways to fight climate change developing new materials creating more effective drugs you know just a crazy level of Discovery could really happen if quantum Computing does get solved at the crazy level now what was actually crazy about this as well was that by using a special system developed by Microsoft that checks and fixes errors in Quantum calculations they've managed to run over 14,000 experiments without any mistakes and this achievement actually demonstrates a significant Improvement in the reliability of quantum computers so I'm actually intrigued to see you know what kind of breakthroughs we make in the future because this kind of breakthrough could lead to a you know very exponential increase in what is capable because quantum computers are able to do so much more than a classical computer um and it really does just go to show that we really could be living in a Sci-Fi world in the future provided you know only a few breakthroughs are met um but it just goes to show that the future might be crazier than we do think so I'm going to keep an eye out for Quantum Computing cuz I think while P many people think that you know it's something that is far away I think once we do get certain breakthroughs it's going to provide us with a whole wave of untapped potential that is just sitting there now this is actually AI

news/ Tech news and the reason I think this is something that's rather important but pretty hilarious at the same time so this is a piece of news that you know I guess went completely viral because it's absolutely insane because a lot of people did think that on the back end this was AI technology but it just seemingly wasn't at all so it says Amazon ditches just walk out check out as its grocery stores says Amazon Fresh is moving away from a feature of grocery stores where customers could skip check out all together now if you don't know this is just absolutely crazy so Amazon Fresh has this store where they piloted it and they said look we have this amazing Store where all you have to do is you walk in there you pick up your products you leave and you will be automatically charged they were like it's the first of its kind it's a technological breakthrough it's just amazing it's called just walk out so it was a checkout list grocery stores and I've used these stores they were actually pretty effective you'd walk in you'd beep your Amazon thing so it knows uh you know that you're in the store and then as you leave you don't need to do anything and you just get your groceries it was something that was really effective however there was something that they revealed recently it says okay that though it seemed completely automated just walk out allied with more than a thousand people in India watching and labeling videos to ensure accurate checkout and the cashiers were simply moved offsite and they watched you as you shopped and this is something that uh went completely viral initial tweet I saw I think it had 30 million views or 11 million views I'm not sure which one it did but um it was simply absolutely incredible because this kind of thing you would think that it was powered by some Advanced Vision system potentially you know like a vision model in AI like some kind of you know accurate YOLO v9 or V10 or something like that with potentially maybe multiple cameras and multiple sensors but it seems that they just had a th000 people now the reason I'm actually talking about this is cuz I think that in the future this is going to be really you know interesting because in the future we won't need a thousand people in another country watching you uh browse and do whatever what's going to happen is that you're only going to need an AGI level system you know with artificial general intelligence it makes things like this possible because if check out you know if this checkout list store didn't work simply because they just didn't have the technology an artificial general intelligence system could actually provide us with the capability to do this so with that level of you know understanding we could now start to I wouldn't say predict but look at how at certain stores might actually operate this because this is why I included this story because let's say like a th000 you know Indians or whatever or 1,000 people in another country we know that currently okay paying a th000 people whilst yes in another country probably isn't as expensive as paying someone in America because uh the wages are significantly lower in those countries I still think it's going to be a lot more expensive than just running a few AGI systems and a few Vision model cameras and just making that more effective and the reason I'm saying that is because it now gives us a look into the future with AGI multiple different things that weren't possible four are going to be possible just like you know self-driving you do need an AGI system to be able to take a look at things and not just like a vision model um and a text model you're going to need like a AGI level system that is able to you know interpret multiple different things have really good reasoning and come to a great response and I think what this shows us as well like if you have AGI I think this might be the future of stores because you know if you have bunch of people you know of course you're going to have the people that are going to need to uh pack the food you know under the delivery trucks all that stuff yeah you're still going to need people but in terms of you know Cashers people doing the checkouts and stuff like that I think that might be largely automated and these stores actually did run pretty effectively they did have different people but it just goes to show that in certain cases You Know Your Role isn't going to be completely gone but you definitely uh will be changing in that role so people who were previously cashiers they were probably just people who helped around helped people find things in the store um and helped you know load and unload the store in terms of certain things and just keep it running and make sure that everything's operational but of course that could be disappearing as well but with AGI we never know because it's largely a singularity now another thing

that open have actually been doing is they've been you know training custom models for a variety of different use cases and I think this is something rather fascinating because it gives us an insight into what openi is doing on the back end they are doing a lot of stuff and they have been hiring a significant amount of people I mean rumors have it that remember when they had 774 employees apparently they've hired as much as 500 people in offices around the globe so it seems that openi is trying to become a behemoth in the AI space and one of the ways that they are doing that is by partnering with different people in different sectors and building custom trained models for different professions right here we've seen that Harvey partners with openai to create a model for legal professionals and essentially right here if I just scroll down to this is going to show you exactly what's going on so the prompt is what is a claim of disloyalty and this is something that is different compared to GPT 4 you can see the custom trained model was preferred 97% of the time and this is a custom model that was trained on a bunch of legal data in terms of the way that it is formatted and in terms of the sources that it sites and we can see that GPT 4 has a very standard response to this so what openai are doing with a lot of companies which is rather fascinating is that they're building these AI systems that are fine-tuned and customed like custom models that are going to be a lot more effective than we initially thought now I do wonder how this is going to work once GPT 5 comes out are they going to have to retrain it again or are they just going to have to you know do it simply with the same process but I think this goes to show that opening ey isn't just you know trying to build the next GPT 5 or GPT 6 they are really trying to I guess you could say as I've said before come after the entire stack in terms of what's possible with AI they do want to be pretty much everywhere and it's clear now that open AI is going to be a major player in the space they aren't just going to be a company that has text Vision they are truly going after everything and I think if open AI currently since they have the market leader position if they able to continually train models like this and go after certain sectors whether it be in healthcare in legal in accounting they could really be like I don't even know a trillion dollar valuation I mean it could be absolutely insane the amount of economic output this company could get because I mean companies are already using GPT 4 and if there is you know a custom version like this uh all of that data is going to be you know going back to open ey all of that Revenue not all of it but like a lot of the revenue the amount of uh you know calls are going to be going back to Open Eyes Revenue so I think it's going to be very fascinating and what's crazy is that they said what's next okay what's Harvey tackling next they said of course um one of their main focuses is Agents or how to combine multiple model calls together into a single working output this would simplify the user experience and reduce the amount of prompt engineering and typing users need to do the vision is for to serve as a supportive member of the team because of course the volume of legal work is growing and associat spend countless hours on complex but routine tasks the opportunity we have not just with legal but with all Professional Services is to take care of the routine tasks so professionals can focus their time on client interaction and this is rather true a lot of legal work is just quite boring just sifting through files looking through uh you know I guess you could say uh sources and citations for certain cases but um yeah it's very very fascinating but it seems that they've managed to figure out a solution and this is not the only customer solution that you know open ey has on their blog they have so many different um things I will show you that in a moment but it's absolutely incredible what open ey like I said before is doing on the back end and on another one right

here this Twitter user points out in a recent openai customer stories post on their site they hinted at GPT based agents soon taking basic actions online and in the real world you can see that this is a company that is mainly focused on the future of email and they state that what's next superhuman imagines a world where GPT based agents will soon be able to filter triage and respond to email automatically scheduling meetings and appointments and taking basic actions online in the real world the success of instant reply proves this agent L email future is not too far off and we know that open aai their Focus right now is of course AI agents so the companies that are working with them stating that this is their next Focus isn't a surprise at all now the next

thing that we have here is of course some speculation but I think it's pretty wild I won't be making an entire video on this but it's something that you should be paying attention to so essentially there was um some old domains from open AI this is Jimmy apples an Infamous open AI leaker and he says curious to see some people not understand all the testing checkpoints models and research that open Ai and others do we don't have X we call it y model C hasn't finished sitting on the last checkpoint Etc their old domains give you an idea and you can basically look through their old domains to see where certain um of course systems were in their face for their training their red teaming or whatever now essentially there were these domains that were to interest of some people because they said very interesting things so for example we saw some of these domains that said uh evaluation leaderboard scientist internal at openai then we see um we see agent chat API scientist internal at openai and we see um other ones that are very similar so what it could be I mean this is some true speculation because we really have no idea what this could be but we know that open AI like I just already said they're working on agents so for them to have agent chats and for them it for it to say scientist at internal at openai could this be a link where they were internally testing scientific agents that are doing research I mean it's possible open AI have said that they Define AGI as when a system can generate new scientific knowledge and samman did talk about how he thinks you know AI being able to do scientific research is one of the most important things because that is going to give the most value out of any kind of breakthrough that we've ever had because if AI is able to generate consistent breakthroughs reliably that is going to be truly transformative for society so this internal links agent chat uh scientist internal open AI it does give us a slight hint into what could potentially be coming but then again this is also something that could just be something that they're testing internally that we might never ever see um because it is of course just a test

we also had this okay this demo right here and this is two Infinity AI making history with the first completely AI generated YC demo Day presentation let me know what you think about this my name is Lena and I'm the CEO of infinity AI actually no um I'm not Lena I'm an AI clone of Lena and you are watching the first ever AI generated demo Day presentation Infinity is a script to movie Foundation model you give Infinity a script and it makes an entire movie since we launched 2 weeks ago our users have made over 2500 videos that have gotten more than 320,000 views on social media our users have created everything from a math class taught by Kim Kardashian to a MC Beth play starring Elon Musk my co-founders and I are engineering phds from MIT in Stanford before Infiniti we started our first company together a profitable ml company that made over $10 million we believe that a high schooler will create the next Seinfeld Infinity is building the tools she'll use to do it thank you my name so uh yeah let me know what you guys thought about that I think it's really interesting to see all of these consumer AI companies coming in uh and creating these you know specific use cases for AI we've seen that different companies have been offering this like haen and a bunch of others and I think it's rather fascinating to see other companies trying to take uh the space because I think now that that's there we're definitely going to be seeing more competition which means better AI footage and again once again some more issues with relations to I guess you could say privacy relations to deep fakes and of course how this transformative technology is actually used now in more news at YC I don't know

if you're going to be excited or uh I guess you could say not disappointed but rather fearful of this update and this is autot tab it says autot tab is a digital robot that you can hire starting at a doar an hour it works 247 365 and does not need lunch breaks so essentially right here this is basically an AI agent system that can control your computer and do mainly right now it can do mainly repetitive tasks and this currently runs at a dollar an hour and I think this is kind of fascinating because although we've had rudimentary systems like this before I do think that the future of the internet is about to get crazy when we do have agents running around I've been wondering and speculating myself that are some websites going to be banning systems like this because you know there have been systems that have been able to click and to do things before but we are moving to a level that you know it seems very human um and you know another aspect of this is that if these agents are running a dollar an hour running 247365 how fast is the economy going to move you know with all these workers because you know currently things were moving at you know 9 to5 that's when the economy shifts and then as you know you wind down it's a global economy and other countries are moving but if you're able to have you know workers 24/7 365 zero lunch breaks that is going to be an insane productivity boom that we haven't seen and of course another thing is that are we going to see more layoffs because you know when you extrapolate this information out you can see you can hire someone for a dollar an hour and it works 24/7 365 uh and it does not lead lunch breaks and I think that's pretty crazy that you know he added that because I think that goes to show that this is of course definitely going to replace possibly some people so I mean it seems very fascinating because they actually talk about all you need to do is literally record yourself doing the task and then it's going to be able to do that task as effectively as you do so I mean this is going to be something that you do need to pay attention to and definitely one I'll be paying attention to as well then what we had was stable

audio 2. 0 a new model capable of producing high quality full soundtracks with coherent musical structure up to 3 minutes long at 441 khz from a single prompt and this is pretty crazy so take a look what you think about this compared to Cena I mean to be honest it doesn't really sound bad but I do think that this might be the year or towards the end of the year where AI music does start to catch on because what we've seen with sunnov V3 and a couple of other systems I think that you know it is starting to hit the mainstream a little bit then we also had

a tweet from Sam Alman stating that movies are going to become video games and video games something unimaginably better so this is a very cryptic tweet it might just be a tweet where he's just you know venting about something that he's doing or it could just be something that he's thinking about in terms and relations to open AI so this is pretty incredible so for some speculation what this could actually be is that this could actually mean that we are going to get interactive narratives so AI could enable movies to become more like video games through blurring the lines between what is real so for example this could require AI being able to dynamically generate or alter content based on viewer decisions creating a personalized viewing experience which would fundamentally change movies forever we could also get enhanced realism in video games and as video games evolve to become something unimaginably better AI could be at the Forefront of this transformation and this might involve creating highly realistic and responsive uh video games I mean you know video games becoming something unimaginably better could mean that we get AI agents AI generated content AI NPCs pretty much everything that is uh generative and then um you know the video games are just entirely personalized or entirely unique where we could just have these virtually generated worlds that are so immersive and so lifelike that we truly are immersed and are addicted to these games now I think they would be fascinating and of course addiction is usually a user problem but I do think that this tweet does go to show that you know Sam Alman does really know how crazy the applications are and one of the things that we haven't seen take off yet and one of the things that I would love to see is video games that truly take advantage of generative AI in terms of what's possible with NPCs and generative content to allow us to play games in a generative way that are really new and effective and I think the first game to do that very effectively is going to be probably a very staple title now what was

crazy is that it seems that open a/ mman have been you know trying to poach some of Elon musk's employees you can see that Tesla's computer vision cheap Ethan Knight has left Tesla and joined Elon musk's x. a company and Elon Musk says it right here that Ethan was pretty much going to join open AI so with either X aai or them he says they have been aggressively recruiting Tesla Engineers with massive compensation offers and have unfortunately been successful in a few cases and he says Ethan is very talented but Vision Chief would be overstating things there are over 200 excellent engineers in the Tesla AI team and he says that the talent War for AI is the craziest talent war I've ever seen and this is something that I've talked about before if you are in the top of your field of AI right now do you have the very nice luxury of being able to go wherever you want because AI you know Talent right now is pretty scarce because all of these companies are trying to build the best models the best systems and those who are the very best are getting huge compensation packages because they know that if your company manages to get a state-of-the-art model it's pretty hard for others to catch up and of course it's no surprise that Elon musk's company um is getting poached by opening ey since they have an ongoing feud that has been going on for quite some time so let me know what you think about