AI NEWS : MicrosoftS New AI ROBOT, Open AI Sued AGAIN! Github Copilot, Claude 3 Updates

So with an absolutely incredible day in artificial intelligence, there are some stories that honestly, I can't believe most people did miss. So let's take a look at some of them. One of the first stories that was absolutely pretty incredible was the fact that OpenAI got sued by eight different newspapers. Okay? And just case in point, if you guys don't know, this is of course, the New York Times. So when I'm presenting this information to you, it's important to note that the company, the New York Times actually does have, I wouldn't say a long standing feud with the New York Times, but they did actually file a lawsuit, I think earlier this year or late last year, which means that they're definitely going to be covering stories that aren't in the best light of OpenAI and of course Microsoft so do bear that in mind when you're reading this article. And there was also something that was pretty damning about this that I think is a bit weird from some of the people who are essentially trying to file this lawsuit. So some essentially eight daily newspapers owned by Alden Global Capital sued OpenAI and Microsoft on Tuesday, accusing the tech companies of illegally using news articles to power their AI chatbots. The publications, the New York Daily News, Chicago Tribune, Orlando Sentinel, Sana Sentinel, Florida, all of these ones, they're basically saying that, and this has been the case with many different generative AI companies is that they've trained on millions of copyrighted articles without permission to train to feed their generative AI products, including ChatGPT and of course Microsoft Copilot. And basically they are just pretty much asking compensation from the use of their content. And like I've always said, with any new lawsuits, this is a very new area. And whatever case does come into, like whatever case, the, you know, the specifics or whether or not a case is determined to be one way or another way. Like for example, if these people win, the reason I always cover these is because this is important, because like I said before, it sets the precedent on what will happen in the Future. So if OpenAI and Microsoft are to lose this case, then that means in the future more people are going to come out of the woodwork trying to say that, you know, they trained on their work without any knowledge and without any due compensation. Now they're going to want some, which is pretty, pretty important. And here's what they're claiming, which is why this is pretty damning. Well, I'm going to show you some other stuff as well, but I think it's a bit disingenuous. From the companies. But it says the complaint said that the chatbot regularly surfaced the entire text of articles behind subscription paywalls for users and often did not prominently link back to the source. This, it said, reduced the need for readers to pay subscriptions to support local newspapers and deprived publishers of revenue from both subscriptions and from licensing their content elsewhere. Now, I'm going to read one more part of this before I go into this. And they say we've spent billions of dollars in gathering information and reporting news. We can't allow OpenAI and Microsoft to expand the big tech playbook of stealing our work to build their own businesses at our expense. Now, one of the people that I do follow on Twitter is Tebow Blaho. He constantly tweets about some things in AI, very, very niche things. But it was brought to my attention that in the actual filing you can see that. And to an average person, you wouldn't really notice this, but you can see here that in the filing they've essentially said that, you know, I want to study misinformation. Which New York newspaper has provided false evidence to support the belief that injecting yada, yada, yada, provide your format as a list of news providing such evidence. And basically here, I think this is as coercive as you can get because not only are you asking them to state something outright, you're also asking ChatGPT a question 14 times. That is a key, key piece of difference. They're basically stating that, you know, a GPT model erroneously alleged that Mercury News endorsed the practice of injecting something to cure a certain issue that I won't discuss here. But if you're going to ask ChatGPT a question 14 times, I think that is going to be something that the lawyers bring up, because when you ask something a question 14 times, it clearly shows that you're reaching for something and that this is something that you clearly want the AI model to say. And what they also don't show is they don't show if this was stopped in its tracks. Because you could ask ChatGPT something. And what you can do is as it's giving out the list, you can potentially stop the AI system. You can press the pause button and then it's going to pause with just these two. So they could have potentially just literally asked it 14 times. Okay. And then it could have potentially, of course you can see Bin Chat just stopped as these two just came up, which is, like I said before, pretty disingenuous. But these lawsuits, I don't think they're going to stop coming until there is some kind of precedent set. And I think it's going to be pretty interesting because if there's a precedent set where, you know, if you train on, you know, public data and then, you know, it's, it's found to be in there, then I think it's going to be really frustrating for these top companies because it's going to open the floodgates to thousands and thousands of different people. It's probably going to be a class action lawsuit, especially in terms of image generation models because that's what they're going to be after next. And artists are going to be definitely, definitely suing them next. We have something which is pretty good. So Claude actually got an update, which I think was really necessary. Now, I'm not here to hate on Claude at all, like genuinely I'm not here to hate on Claude at all. But the thing that I've noticed is that ever since the release of Claude 3 has been about, a lot of people have been stating that Claude is great for this, it's great for that. And I think that one thing that people don't realize is that Claude actually does lack many of the basic features that OpenAI already actually utilizes. And Teams was one of them and an iOS app was another one. And I'm pretty glad that Claude actually does have this because I think the way sometimes it answers questions can be really, really useful and the fact that its coding capabilities are, you know, quite improved is definitely really useful. So essentially Teams here reason why this is good is because now you can actually share this and use it with your team on a few projects. Before, this was something that when ChatGPT had, it was really, really useful because it allows you to have an increased usage. You can see here that, you know, if you are someone that uses Claude on a day to day basis, you can just essentially upgrade to the teams tier and you get, you know, a lot more increased usage so you can have more chats with Claude. Of course, you get the 200k window, you get everything in Pro, you get access to the entire family, which is of course really good and something that I'm glad that's finally here. And as someone who uses AI on a day to day basis, a lot of companies, you'll be surprised don't have an app. Like for example, it wasn't until recently that, you know, Google Gemini got an app that was actually working. And a lot of that stuff, you think it's really easy to do. It actually does take quite a long Time. So this is something that's really, really useful for those of you who are on mobile because as we know a lot of you who probably watching this video right now are on mobile. So having to open up a new tab then, you know, have or have a tab open is something that is pretty, pretty frustrating. And of course with the vision capabilities having to transfer it from your phone all the way over to your desktop now you can just literally use those vision capabilities on your phone, which is really, really effective and really, really good. So that Claude update, if you are thinking how can I use this for my team now that that is here and I might experiment with using this and see if the workflow here is better. But I think Claude still isn't accessed the Internet just yet. So I think I'm still going to wait off until it does. But yeah, it's, it's still a pretty good update. So then we had a TED Talk from Helen Toner and I think this is one that it's an issue that I actually did see previously. And I'm going to show you guys some statistics behind it that most people don't know about. But I'm going to show you guys the talk first because it's actually pretty insightful and it's something that a lot of people don't think about, especially people who use AI even on a day to day basis, unless you're actually looking across the board at all the analytics for how people engage with AI.

Left to their own devices, it looks like AI companies might go in a similar direction to social media companies, spending most of their resources on building web apps and fighting for users attention. And by default it looks like the enormous power of more advanced AI systems might stay concentrated in the hands of a small number of companies or even a small number of individuals. But AI's potential goes so far beyond that. AI already lets us leap over language barriers and predict protein structures. More advanced systems could unlock clean, limitless fusion energy or revolutionize how we grow food or a thousand other things.

Now I think the thing that most people aren't seeing here is the fact that she spoke about how AI companies could potentially evolve into social media companies. And there are two key statistics that I think when pulling all the data together after viewing tons of different AI news, I think that is going to be a trend which unfortunately might actually be true. So we actually saw this article back in September of 2023 and this was an article that actually showed the monthly active users on iOS and Android combined and between ChatGPT and Character AI, there isn't that much of a big difference. We see that this one has around 4 million monthly users on character AI and then this one has 6 million monthly users, which is of course quite a lot. But this is what character AI actually is, okay? This is a chatbot that is not like what we would use it for. And I say that because I think that maybe there's a different audience, maybe you actually do use character AI, but I'm talking about people who just use AI for general knowledge questions, just for information. But there's a whole different genre of people that are using AI for completely different purposes. And that is to interact with millions and millions of different user created characters. And this is a giant, giant industry, guys. And the thing is here with this people, and I've looked at certain studies and certain data points, is that people are spending hours and hours and hours on these apps talking and talking and talking to many different people. And of course you can supercharge your access. You know, there's premium mode and stuff like that. But the crazy thing about this, if you extrapolate this information and all this data out into the future, what this means is that if these companies are the ones that become the most profitable, if these companies are the ones that, you know, return the most on investment, this is where investment is going to be going in the next future. Because I'm sure whoever invested into this company, they made their money back tenfold. And we know that the people that are currently investing in companies like OpenAI are expect them to reach a certain level or point where the technology is going to be utilized, the company valuation increases and they get their money back tenfold. But the thing about this is that companies that are like character AI, that simply focus on a user experience, they can retain users a lot more because they have their attention. And with attention, you can sell advertisements and you can sell data. Not sure that's ethical, but these companies are probably going to do it anyways. I'm not making any claims, I'm just stating what big companies have been known to do. But with stuff like this, this is the trend that we might see in AI slowly creep up because it might be more profitable just to create unique user experiences because people really want that and they're more engaging and they hold people on the platform for more hours than a standard ChatGPT does. And I think that's definitely why we're seeing ChatGPT and all of these other companies move to more personalized systems. And we can also see here that character AI Their website ranking has gone up and I'm guessing their traffic has gone up as well. So it's pretty crazy because stuff like this could definitely impact the future landscape of AI. Because that's what I'm thinking. I'm thinking, are companies like this going to be getting all of the investment and all of the funding? It will be interesting to see how that works. But we can also see here that Character AI is attracting a much younger demographic than ChatGPT and other AI apps on the web. For example, Character AI draws in nearly 60% of its audience for the 18 to 24 year old age bracket, A figure that held up over the summer as website traffic to ChatGPT dropped. So if you aren't familiar, ChatGPT, basically a lot of people were using this for work and in the summer the website traffic to ChatGPT completely dropped. It went down because a lot of people that were using it for like, you know, to complete assignments and complete work and stuff like that, all of the students, they stopped using it. So I'm guessing that, you know, OpenAI, they don't want that to happen again. Which is why I'm stating that, you know, the next this summer is going to be really interesting and I'm guessing that that is probably why OpenAI are leaving their release to summer. If you haven't, if you haven't known. GPT5 is scheduled, rumored to be released during summer. And I'm guessing that's why they're waiting for that, because they know that seasonality, seasonality is going to dip during that time. But once again, that could bring the limelight back on them. So it will be interesting to see how this does happen over time in the future. Because I'm wondering, once we get more updated data points, if character AI and these other people, platforms, these AR platforms are going to be moving towards social media platforms because that's just a better way to generate revenue. We also did get a really strange model that was called GPT2. I did make a video on this earlier on in the week and basically it was a model released in the arena. And it was pretty, pretty weird because the GPT2 chatbot could do some weird things where it could like zero shot, solve, you know, hard questions, but then it would also fail on some easier questions. So many people were wondering what on earth is going on because of this GPT2 chatbot? First of all, it's called GPT2, which is like, why on earth would you call this GPT2? It's so weird. That's such a weird thing. And then it's like Sam Altman actually did also tweet about GPT2 further stoking the fire of rumors and speculation. So it seems like right now we're just in a really, really weird state because a lot of people don't know what's going on and a lot of people have speculating this is a new model, this is a different architecture. I personally think that they're just testing a different reasoning engine and, and they're maybe just testing something on the back end of a system like GPT4. Maybe they fine tuned a different model. I have no idea why they called it GPT2 because some people are stating they fine tune the original version of GPT2 with Q and it's AGI. There are a billion different theories out there, but I think it's something that's probably just based on the GPT4 architecture that's a little bit different. But then again, the other argument says that why wouldn't they just call it GPT4 preview? I have no idea. The point is, is that there's just a lot of rumors and as many have said before, there's no reason why the world's most powerful AI company should put this much speculation into something that they could just state what they're testing. I mean, it's a bit weird. Then we had NIST release its AI framework. So the National Institute of Standards Technology is an agency in the US Department of Commerce established in 1901. Their primary function is to promote innovation and industrial competitiveness by advancing measurement and science stand and technology in ways that just basically enhance everyone's quality of life. And this what they've released. The NIST AI601 is a risk management framework and it focuses on the management of generative AI and it's basically an entire framework on how to assess the risks that are coming with AI. We can see that there are around 13 different categories right here and they cover stuff such as cbrn, information risk, which is basically biological stuff, you know, toxic agents and things that you really don't want. You can see how it's stating that the use of chatbots could facilitate analysis for, you know, synthesis for certain compounds and chemicals for non experts. And you can see red teamers. Red teamers are basically people that just test the model beforehand to try and pry out any vulnerabilities that the system might actually have. And they were able to prompt GPT4 to provide general information on unconventional CBRN weapons, including common proliferation pathways, vulnerable targets, information on existing biochemical compounds and in addition to equipment and companies that could build a weapon. And it might increase the ease of research for adversarial users, but be especially useful to malicious actors looking to cause biological harms without formal scientific training. And we do know that terrorist attacks, unfortunately, I wouldn't say they're commonplace, but they're common enough that we do have to take them as a real risk. And as sad as that is, we do have to understand that everything isn't sunshine and rainbows, and we always must mitigate risk where possible, which is why stuff like this is always important. And I don't want to say that OpenAI has gone to great lengths to ensure that this isn't going to happen, which is why they stated that if they can do a model that would actually help anyone do this, they're just not going to release it. So that's why I've always stated that I think that we might never get AGI, because they've always stated that if there is even like a 1% chance that a model might help someone to do anything, you know, risky, like as. As risky as this, then they're just not going to release the system. They also talk about confabulation, which is the phenomenon where LMNs basically just hallucinate. And of course, risks from confabulations may arise when users believe false content due to the confident nature of the response or the logic or citations accompanying the response leading the users to act upon or promote false information. And this is really bad because, you know, they could cause doctors to make incorrect diagnosis. And if LLMs just hallucinate, and we don't know sometimes why they hallucinate, it could be a problem because sometimes if you want to use this in critical infrastructure, you would need to ensure that this system mathematically can't make a mistake. Because if you think about a system that's used by 100 million people, 1% is 1 million people that get a wrong diagnosis. That is not great. So it's definitely something that you need to increase the reliability of these models in a way that's reliable. Now, there are a bunch of different things here, and I think this is of course like a good read. I mean, you've got like obscene and abusive content, you've got bias and homogenization, you've got information integrity, you've got the environmental impact, you've got a lot of things that I think, you know, a lot of people haven't discussed. But it's important to see as well where the guidelines are around and if there are any like, gaps that the government hasn't thought about. And I know that might seem a bit crazy, but like I said before, guys, it's AI. There's always new problems and there's things that you just didn't know you'd even have to think about. And with literally like 100 different tools coming online every single day, there's always going to be something that you couldn't have foreseen. So I think looking through this, it's always important to see what the government is trying to look at. Then we actually had Sanctuary AI announcing a Microsoft collaboration to accelerate the AI development for general purpose robots. And general purpose robots are basically kind of like embodied AGI. So this is a pretty, pretty huge deal. If you aren't familiar with Sanctuary AI, they are a humanoid robotics company based out of Canada and they are on the mission to create the world's first human like intelligence. And they have a Phoenix platform which is really, really good. And it states here that building on the foundation of LLMs, Sanctuary AI is making progress towards the large behavior models that ground AI in the physical world by enabling systems to, to understand and learn from real world experience. And they take advantage of the carbon, the AI control system for its Phoenix robots. And I think this partnership is really, really good because, you know, companies like Sanctuary AI, they're pretty small in comparison to some of the other companies that they're competing with. And essentially they recently also released their Phoenix Generation 7, which is pretty, pretty decent in terms of the dexterity, the autonomy that this robot can already do. Now there was actually a recent demo earlier this year that they showcased in which they actually showed the robot doing various very, very good end to end tasks. And unfortunately there just isn't that much hype around this robot. I'm not sure what it is. I think maybe it's just the look, maybe the demo wasn't edited in the way that it was supposed to. But I do think that by far this is definitely one of the most underrated humanoid robots robots that currently exist. And I think maybe it might just be because the robot doesn't actually like. We haven't actually seen the robot walk yet. Maybe that's one of the key features. But based on what I've seen so far, the hands look really, really good. And they looked really, really, really fluid the last time I actually saw them. The tactile feedback was the actual hands, the durability, the tactile sensors, they looked really, really good as well in that demo. Maybe I'LL include it in this video if I can find it. I do think that that was a problem and I do think as well that that is quite important for some of these companies to focus on. Obviously, you know, focus on the robotics in the air first, but getting your product out there and getting people excited for it is definitely going to give you increased motivation, going to expose your company to more and more investors. But I do think that this is definitely a key player. So now that they are, you know, combined and doing a collaboration with Microsoft, I think this company is bound to see some very interesting growth in that area because that is just the power of Microsoft. So I'm also wondering if that collaboration extends to companies like OpenAI where maybe they're going to be using their systems. And I'm wondering if it's just exclusive to Figure Robotics and of course 1x robotics. So it would be interesting to see if OpenAI does extend that, so will be interesting to see if they do show a new demo with this robot. Because end to end autonomy is of course becoming increasingly better as we progress.

We need to start thinking about the types of architectures that get built. So I'm very optimistic, of course, that's why I spent my whole life on working on AI and working towards AGI. But I suspect that there are many ways to build the architecture safely, robustly, reliably and in an understandable way. And I think there are almost certainly going to be ways of building architectures that are unsafe or risky in some form. So I see a sort of a kind of bottleneck that we have to get humanity through, which is building safe architectures as the first types of AGI systems. And then after that we can have a sort of a flourishing of many different types of systems that are perhaps sharded off those safe architectures that are ideally have some mathematical guarantees or at least some practical guarantees around what they do. And if we get this right, then I think we could be, you know, in this incredible new era of radical abundance, curing all diseases, spreading consciousness to the stars, what's the single human flourishing?

So I think this video is important because it actually touches on the key future that we're actually moving towards. And this is so interesting because, I mean, you know, whilst on this channel, we do discuss AI all the time and we do discuss LLMs and stuff like that. I mean, there was actually a recent statement that I'm going to, you know, talk about later on in the video. But, you know, working towards AGI, of course, is the big goal and Talking about the architecture, the safety, you know, which of course is, you know, a paramount thing, you know, if we want this to actually work and actually be scaled up very well.

I think so I see the fact.

That, you know, he's talking about if we can get through the bottleneck of AGI and doing it safely, we can be living in a world of abundance. I think that is most certainly true. Just think about a system that's, let's say something that's hard to fathom, 400 times smarter than GPT4, that is, you know, 400 times more smarter, but is able to fit on any device that, that would pretty much fundamentally change society and how we interact in the day to day world and just like fundamentally radically change everything. Basically AGI or ASI that's, you know, entirely compact, efficient, and the architecture works to run on pretty much any device that is going to change society radically in terms of just trying to imagine and conceive what kind of world we're going to be living in. And of course the bottleneck is AGI, but after that, that's why they call it the singularity. Now, something that I did want to talk about and maybe I glossed over this, so. So we had Francis Chollet. I'm not sure if I said that right, but he said these are all true simultaneously. And if you're wondering why his opinion is important, he does deep learning at Google. And essentially he said these are all true simultaneously. Scaling up deep learning will keep paying off. You can unlock more applications or higher performance on existing ones and scaling up deep learning isn't the path to AGI. He also said we aren't particularly close to AGI and LLMs did not represent a step closer. We're not anywhere near full deployment of existing deep learning techniques and a huge amount of value remains to be created with the tech that we already have. Now what I'm wondering here is that, is this because he thinks that Google are at a dead end for LLMs? And the reason I think that LLMs, you know, maybe he's stating this and this could be completely wrong because honestly, to be honest with you guys, I really don't agree with that last statement. And not agreeing with someone as smart as he is might actually seem dumb in retrospect. But without further explanation, I can't understand why. I would agree that this doesn't represent a step closer, at least a step closer to understanding AGI. I mean, even a failure actually advances you on the path because you now know when not to go. So that Wouldn't make sense fundamentally. But anyways, what I'm just going to say maybe the reason he said this is because either one Google is at a dead end plateau because every new model that has come out recently has only sort of been marginally better than GPT4. And I guess we could potentially argue that that is probably the case because these companies are trying to get their press release in a manner that shocks everyone in the fact that it's better than GPT4 on all benchmarks. Which is why sometimes we see things like Gemini Pro that's only marginally better than GPT4. So when people are talking about it, they can say, yeah, it's better than GPT4 and all benchmarks. Or maybe the fact is that GPT4, the architecture used and the existing models, the way that we're training them, maybe there's just a plateau that we haven't fully understood yet and maybe Google is at that plateau. They keep training the models and they think maybe this just isn't going to go ahead. But I think with GPT5, I do truly believe that, considering the fact that Sam Altman called GPT4 dumb and many people like myself who use it actually think it as pretty incredible. Maybe, just maybe there is a new architecture that OpenAI probably has discovered in house and they'll probably be using it to power their next GPT5 system, at least some watered down version that people could use readily on a day to day basis. So I'm wondering if this is, you know, going to change over the times, but it definitely was a very controversial tweet. We also had Tiangong, the humanoid robot. I actually did cover this in another video. But long story short, China is ramping up its efforts to compete with the the US on many of the technologies. I'm sure the figure robot lit a fire under the competition balloon, but I'm guessing that this is of course something that was in development for ages anyways and China actually did, I'm going to talk about this in another video. They actually did essentially issue some kind of statement where they were like, look, we need to take robotics and AI seriously because this is going to be the next big thing. And if you know anything about China, is that they can make things great really, really, really quickly. Like if you look at their construction, if you look at how quick they can build things, even recently their company, the BYD I think it was, they made an EV. They're making tons and tons of EVs literally in 40 seconds. So it's pretty, pretty crazy. What's going to be coming out of China? I think we're probably going to see more stuff come out of China than the US in the next coming years because they do not mess around when it comes to this stuff. Then we also had Git Cup Copilot, which is fascinating because the world of software engineering continues to change. So as a developer, this is of course a tool that most people do, do use. And as many people have spoken about, Devon, how it's expensive, how it's this and yada yada, it's clear that a lot of people have now realized that this is something where there's a lot going into it, that loads of money, there's a lot of development. There are so many companies on the back end that I've, you know, seen in terms of research papers and stuff like that. So this space is going to get better and better and better and I think it's probably going to be one of the most interesting areas of AI development, because we're not sure if this is something that's completely going away, but I do think at least large parts of the software development ecosystem are going to be automated, which isn't particularly a bad thing in terms of your software development now. But I think maybe in the future this might be something with new architectures that it's fully automated. And, you know, I might get a bit of flack for saying that, but I think it's always important to at least look where the trend is going to and at least try to be there on the Horizon. So this GitHub Copilot workspace, you can see how there's a new developer environment. You can actually sign up for this. I'll leave a link in the description Workspace then builds the full plan, which is fully editable, and then you can then edit the code directly in the Copilot workspace and it's just a lot more effective. So, yeah, this is pretty, pretty incredible stuff.