EP 433: AI News That Matters - January 6th, 2025

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Enough beating around the bush. We're going to have AGI agents in the workforce in 2024. Did I read that right? Yes, I did. That's some of the biggest news this week in AI, as well as, I mean, a little bit of everything else. Meta had a Disastrous experimentation with AI generated profiles. OpenAI is looking beyond AGI to ASI and AI is about to take over CES. Just an Alphabet soup here to start your morning. All right. There's so much going on in the world of AI. You could spend, I don't know, a couple hours each and every day trying to keep up with it and say, hey, how is this going to impact my company, my career, my department? You could do that or you could let us do that. That's what we do almost every single Monday here on Everyday AI. So welcome. My name is Jordan. I'm the host of Everyday AI. This is a daily live stream, podcast and free daily newsletter helping everyday not just learn AI, but how we can all actually leverage what's happening to grow our companies and our careers. If that's you, maybe you're listening for the first time. Welcome. Thank you for joining us. This is live, this is unedited, this is unscripted. It's the realest thing in artificial intelligence, and we do this every day. Where you can continue to do this is our website@your everydayai.com there you can sign up for our free daily newsletter where each and every day we recap the podcast episode. But you can also go on there, sort anything by category. No matter what you want to learn. Do you want to learn about AI and hr? Do you want to learn how artificial intelligence is impacting marketing or communications or the ethics behind it? It's all on our website, sort of by category, where we've talked to hundreds of the leading experts in generative AI across the entire world. It's all there for you for free. Free. Go watch, listen, read your everyday AI dot com. All right, without further ado, let's get into the AI news that matters for the week of January 6th. Live stream audience, thanks for joining, as always. We got Wall street warlord on YouTube. New face, thanks for joining. Big boat, big bogey. Jordan, Brian. Joe, Peter joining on the Twitter machine, Marie, Rolando. Joe. Thank you all. All right, if you haven't seen this piece of AI news, don't worry. It is Fresh and hot off the presses. So OpenAI is now confidently pursuing AGI artificial general intelligence, with now plans, or at least now increase expectations for AGI agents to join the workforce. So, in a blog post on his personal website, OpenAI CEO Sam Altman talked about stride the company is making toward achieving artificial general intelligence with a clear roadmap that introduces the introduction of AGI agents into the workforce by 2025. Yes, let me repeat that. Open AI. Open AI CEO Sam Altman in a blog post just a couple of hours ago, said he feels pretty confident that we will see AGI agents joining the workforce this year. Yeah, wild to think about if you would have said this, even, I don't know, eight months ago, 10 months ago. So the company has expressed strong confidence in its ability to build AGI, marking a pivotal moment in AI development that could reshape industries and job functions. So, couple things if you didn't read the post and we'll be linking to it in our daily newsletter. They said that they would be gradually releasing it into the world for safety reasons and that they are confident that they know how to build AGI. So a direct quote from Sam's blog post saying, we believe that in 2025 we may see the first AGI agents. Oh no, sorry, AI agents. I won't go back and edit that. Don't worry, sorry. AI agents joined the workforce and materially change the output of companies. So OpenAI's approach emphasizes the importance of gradually releasing technology into society, allowing time for adoption and ensuring that the benefits of AGI are broadly shared. So yeah, to correct myself, OpenAI said that they are confident and know how to build AGI and that we will see the first AI agents join the workforce in 2025. So in the post, Altman also said open AI, yes, slipping this one in here, is actively aiming to super intelligence. So previously, Sam Altman said that they are thousands of days away to super intelligence. But now, at least on his personal, personal blog post, which the the company Open AI did retweet on Twitter his blog post, but they said that they're actively aiming to super intelligence. So if you are brand new here, maybe you're hearing all these acronyms. I know I've already dropped a couple on you already, I'm sorry, but AGI, artificial general intelligence, that's essentially when a single AI system can perform tasks at a higher level than almost any human. All right. And depending on what definition you're looking at. Right. This is one of those where the goal posts are always moving. I'VE said this before, I had a dedicated episode. If you look at definitions of AGI from 15 years ago, we're definitely there. But as AI progress progresses, so does to the definition of AGI. So Sam Altman saying, hey, we've figured out AGI and we're going to be slowly releasing it and we're going to see AI agents in the workforce, but also saying we're working toward or aiming to super intelligence. So asi, if you haven't heard of that, the short way of saying it, it's past AGI. It's when you have AI systems that are smarter, not as smart as, but way smarter than the smartest humans at every single task and can also self improve. Right? They can, you know, it's when open or when Chat GPT is making the next version of itself and doesn't need humans to check its work. Right. So that's essentially what ASI is. Also one other they did share a little bit, which you don't really see numbers shared a lot. But OpenAI said that they've seen a weekly surge or, sorry, a surge in weekly active users increasing from 100 million to over 300 million. Yes, OpenAI and Chat GPT are winning the kind of LLM or Chat AI chatbot race. And it is not even close, right? Second place, third place, fourth place, fifth place combined are not even close to where OpenAI is at. I would say a big reason behind that leap from 100 million to 300 million active or weekly active users. Two things. One, it's, it's, well, maybe three, it's having the chat GPT search. All right. But then it's also having that available for free. So OpenAI has really changed its free free plan, so giving at least limited use. Right. So now what they're trying to do is instead of using Google, they're like, hey, use ChatGPT. Even if you have a free account, you know, you can use Chat GPT search. Also you can use Chat GBT as of a couple of months ago without even being logged in. So a lot of those things are really adding to kind of their, their lead in that department. So we do know. So when we talk about AI agents joining the workforce in 2025, is that actually possible? Well, I'd say it's already happening, right. If you look at Microsoft with their autonomous agents in Copilot Studio, if you look at Salesforce with their agent force, although I don't think that's going to be very successful early on by charging per conversation, however, it's already. It's not a far out, you know, thought to think about. But we do know that OpenAI, according to reports, is set to be releasing Operator or at least releasing some details around their operator agent. The that is supposed to be debuting some point this January. So I don't think that that will be the AGI threshold. Right. That we've all been talking about, but I do think that probably we will see some sort of release this year from OpenAI that's like, yeah, this is definitely AGI, but I don't think we're going to see that with this January Operator release. I don't think it's. Until you combine that autonomous kind of agent nature, if that is called Operator, but combining it with a more powerful model. So whether that's a GPT 4, 5, a GPT 5 in O1, in O3. So these O level models right now don't have access to any tools. So maybe that could be the thing that pushes OpenAI over that line. All right, our next piece of AI news. Yeah, you're going to be hearing about AI a lot this week. Sorry, it's going to be like AI in fridges, AI in microwaves, AI in your gym sneakers. That's because. Because CES is upon us. Well, in a couple of hours. The Consumer Electronic show, the biggest tech show in the world, is set to kick off tomorrow in Las Vegas and it promises to be a significant event for tech enthusiasts, particularly those like us who are interested in AI. So a couple things that have already been announced or leaked or previewed. Samsung is aiming to introduce its AI for All Everyday Everywhere initiative featuring, yeah, this is real AI fridges that can anticipate temperature changes when groceries are unloaded. LG is introducing Affectionate Intelligence. Y', all, can we stop trying to name, rename AI like Apple Intelligence? And now LG is, is saying they have affectionate intelligence. Can we stop that? That's not smart. Sorry. Anyways, LG is introducing Affectionate Intelligence, a concept that suggests a more personalized interaction with technology. Although what that actually means is not yet clear. Hey, lg, how about first work on, I don't know, creating dishwashers that work instead of, you know, trying to rebrand Affectionate Intelligence. Yeah, if you listen to the show, I've had a lot of problems with, with dishwashers and washers and dryers over the last couple of months, so. Also the TV industry. Yes, we are going to see generative AI in TVs. That's going to be fun. Nvidia is also expected to unveil, which might be one of the biggest announcements coming out of ces. We'll see. Nvidia is expected to unveil its next generation GPUs with the RTX 5090 rumored to be up to 70% faster than its predecessor. Also, Microsoft is set to announce and launch some more powerful AI features in its next generations of PCs, urging users to upgrade from Windows 10 to its newest operating system. All right, so there's going to be a lot more and we're going to be throughout the week we're going to be sharing about what's happening at ces. I do believe the majority of the more noteworthy noteworthy announcements will be coming Tuesday, so make sure you check out our newsletter for that. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Gen AI. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, or you can partner with us too. Just like some of the biggest companies in the world do. Go to your everyday AI.com partner to get in contact with our team. Or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on gen. All right, so yeah, big bogey face says currently at 0% of artificial super intelligence. Marie, I am not going to CES this year. Maybe next year we'll see. Here's one that's fun. And by fun I mean I'm glad this happened. Meta has shut down AI profiles amid user backlash and technical issues. So Meta has decided to delete Facebook and Instagram profiles of fake humans. Right? So they essentially it was announced last week even though these AI characters had actually been out incognito ish in the wild since September. But Meta did finally say, all right, we're gonna not do this whole AI profiles thing anymore. So essentially the company initially launched these AI powered profiles in September 2023 as part of an experiment, but user Interactions have raised significant concerns, leading the company to essentially squash this project. So if you missed did come out last week and we covered it in our newsletter, news of this. Even though Meta had been testing these AI generated profiles out for more than a year, but news came out last week that Meta was going to start to roll these AI profiles out more broadly. And you might be thinking, why? Isn't that like spam? Isn't that like, you know, just potential for misinformation, disinformation? Well, Meta wanted to do it to increase stickiness and increase engagement on the platform. So when you take a photo of your Thanksgiving dinner and put it on Instagram and you only got three likes and two of those were from your mom's normal account and your mom's burner Instagram account, right? Meta's like, hey, if we just get a bunch of, you know, millions of AI generated profiles and they can start commenting and liking people's content, people will spend more time on our platform, which is an absolutely terrible idea. I am sometimes baffled at the, you know, AI ideas or AI initiatives at some of the biggest companies in the world. Like, I know that people in Silicon Valley live in a bubble, but come on, everyone, everyone saw this and said, this is dumb. I don't know anyone that thought, you know what, you know what we could use on social media? Some. Some AI profiles. Millions of them, please. Yeah, I would love to have fake engagement. So anyways, the company, like I said, had previously introduced 28 AI Personas in 2023, but decided to shut down most of them by summer of 2024, with the last profiles now appearing recently. So here is an AI feature that I'm glad gets squashed. We don't need AI everywhere. Like we don't need AI fake generated profiles on social media, please. So despite the removal of these profiles, users can still create their own AI chatbots which can be used on the platform. So that includes various roles such as therapists and relationship coaches. Right. So this is more of like creating your GPTs and then you can use them across Meta's different platforms platforms. Also, Meta in those chatbots has included disclaimers warning that some messages may be, quote, inaccurate or inappropriate, end quote. So legal ambiguities regarding the responsibility of chatbot creators for the actions and statements of their AI companions, as highlighted by a lawsuit against character AI which claims the platform encouraged harmful behavior in a user. Yeah, I don't think, and I don't personally want to see these, you know, AI profiles on any platform. Right. There's already way too many bot farms, right. With fake profiles on social media that are powered by artificial intelligence, but these are not affiliated with the actual companies that own said social media platforms. I think fake profiles are a huge problem on social media and I don't think this was a good idea by Facebook to even. Or, sorry, by Meta, to even run these experiments. But I am glad that they squashed them. So, yeah, live stream audience, what do you think? Juliet said this is the opposite of intelligence. Yeah. And Michael said, because social media isn't addictive enough. Yeah. They were just trying to make it stickier. Right? You go on and you post, I don't know, some quote you think is super inspiring but doesn't inspire literally anyone. And then you get, you know, 30 comments from AI bots, bots that are like, oh, this is the best thing ever. Right? Keep posting. No, stop. Stop with this madness. All right. Speaking of madness. Yeah, we didn't see Grok 3. So Elon Musk's Grock 3 model is facing delays. So the anticipated launch of Elon Musk's Grock 3, which is Xai's next major AI model, has been pushed back, highlighting ongoing issues in the AI sector regarding product timelines and scaling limit. So Musk previously stated that Grok 3 would be released by the end of 2024. But yeah, here we are in 2025 and there's no signs of Grok 3, which is to the surprise of probably no one, unless you are absolutely addicted to everything that Elon Musk says and you eat out of his Twitter account like it's cereal on a Saturday morning. So yeah, I've said this all along. I'm not shy in saying that I don't think Grok is a serious model, mainly because it is largely trained on Twitter data, which is a cesspool. So reports suggest that an intermediate model, GROK 2.5, may be released before GROK the third of indicating potential setbacks in development. So Musk admitted in an August interview that Grok3's availability in 2024 would depend on luck. So first he said, yeah, we're going to release it in 2024. And then a couple of weeks ago he said that Grok3's pre training was complete. So everyone's like, oh, the pre training is complete. That means we're going to be getting the model. No, I do like Xai or Grox move here because they did kind of preview a web only interface. So at least moving the Grok AI platform off of Twitter, which I think is a smart move however, because so much of the model uses real time data from Twitter, I don't think any companies will ever actually use it in production. Yeah, it might be fun to go on there and just have a second model or a fifth model to back up what you're already researching. Or if you want to, you know, go use their roast Me feature or to roast a certain, you know, X profile. But aside from that, I don't see any business anytime soon actually using Grok until they separate it from Twitter. So at least I like this direction that they're going with having a dedicated web only interface which I think will give business leaders the proper way to test grok. And yes, they have. They built their super gigafactory of compute and they're built like buying like a trillion Nvidia GPUs. But that does not matter if you still are using the Twitter slash X platform as one of your biggest pieces of pulling in new information. That is dumb, right? Like that's like meta hopefully is not using all of the content that was created by those AI generated profiles to create its next version of Llama. Right. I think there's a difference between thoughtfully using synthetic data from a model to either distill other models or to train models versus using what's on social media. That is a big difference. Yeah. Dr. Scott saying Musk question mark delays. Really? Yeah. Shocker. Right. Michael said I use Grok a couple of times because it's the quote unquote free speech, quote unquote less restrictions model and I came across the same restrictions and biases. Yeah, it's a bunch of marketing. Not very good. All right. Speaking of failed promises, OpenAI's media manager tool also delayed amid IP concerns and legal challenges. So OpenAI's anticipated media manager tool, which was designed to allow creators to manage how their works are used in AI training, has yet to launch seven months after its announcement. This is another one of those things. OpenAI said that it would be released in 2024, yet we are in 2025 and we haven't heard a peep on the Media Manager tool. So like I said, it was intended to identify copyrighted content across various media types and reflect creators preferences, aiming to address criticism and legal challenges faced by OpenAI. Insiders suggest that the tool was not seen as a priority within OpenAI. With reports indicating little internal progress or focus on its development. OpenAI has missed its self imposed deadline to have the Media Manager operational in the 2024 calendar year. So right now, leaving content Creators, media, publishers and everyone else without a comprehensive opt out solution for their works. So right now, current methods for creators to opt out of AI training, such as submission forms for removal, has been criticized as cumbersome and ineffective. So yeah, there actually is a way on OpenAI's website that you can essentially say, hey OpenAI, stop scraping my website, stop using my content for your models. It is not super intuitive. So that's why OpenAI did announce the Media Manager, which when we first covered it in our newsletter in early 2024, I thought it was a great idea if it came to fruition. However, it seems like, I don't know, maybe AGI and ASI have suddenly become more important than, you know, the data. And here's the other thing. These large language models, these big tech companies, they need the Internet. There's this, you know, the big elephant in the room as well. These models are essentially scraping copyrighted content and using it to train their models. And we're going to be talking about a lot of lawsuits in 2025 that may or may not prove that exact same thing. Right? That's the, the big secret in the room that is not really a secret. All of these big tech companies are scraping the open Internet, which includes obviously copyrighted works. Right. And it's, it's essentially, that's how generative AI works, Right. It's instead of reproducing a one to one copy of something that is copyrighted, instead of, it uses maybe dozens or hundreds or thousands of variations of different copyrighted content and essentially blends them all together and spit something out that is technically unique, but technically just derived from dozens or hundreds or thousands of pieces of copyrighted content. So there's a very informal lesson in how generative AI and large language models work. So OpenAI faces, like every other big tech company, faces class action lawsuits from multiple creators and large content organizations, including authors in media conglomerates, claiming that their works were used for training without permission. Yeah, but it is hard to prove unless a model spits something out verbatim, which obviously, you know, you can kind of scheme to do that with some, you know, fancy prompt engineering. So yeah, we're going to be seeing this a lot in the courts in 2025. So legal experts have expressed skepticism about the media manager's ability to, to resolve ongoing intellectual property issues, highlighting challenges in ensuring compliance and the burden it places on creators to manage their own rights. Right, yeah, it's kind of like, and this isn't just OpenAI, this is everyone. Right? But kind of like the unofficial unwritten rules right now are like, hey, yeah, we're going to essentially take every single piece of content that's on the Internet, whether you give us access to it or not, right? Unless you jump through some hoops and make it hard for big tech companies to not scrape it and to not use it all. But that's how the Internet works now, right? FYI, speaking of big tech companies, Microsoft is planning for an 80 billion dollar investment in AI infrastructure for the calendar year. So Microsoft has announced a significant investment aimed at enhancing its capabilities in artificial intelligence and cloud computing. So the tech giant plans to invest approximately 80 billion, that's with a B Y', all, $80 billion this year to develop data centers specifically designed for training AI models and deploying AI driven applications. So the investment comes in the wake of a surge in generative AI interest, obviously following OpenAI's ChatGPT launch in late 2022, as businesses across the globe scramble to try to use as much AI as possible. Well, what does that mean on the back end? Number one, that's why Nvidia is, has been the most valuable company in the world by market cap, which I told you all like two years ago and don't believe me. But also it means that data centers are growing. It's meaning that we need more, more power, more energy to power all of these giant clusters of GPU chips that are running infere in the cloud, right? So, you know, if your company is using AI in pretty big way or maybe, you know, you or your team are heavy users of, you know, Chat, GPT or Claude or Gemini or whatever, right? Somewhere in the world that inference or that compute is happening. It's happening in the cloud, right? So these data centers are going to get bigger and bigger. You know, that's why we're talking about nuclear power. That's why we're talking about, you know, where these data centers are even located and building, you know, these huge new data centers that are essentially, you know, tens of thousands or hundreds of thousands of GPUs. So that's what happens, right? Unless you're using Edge AI, which is a large language model that can run locally, right? Because then all of that is happening on your device. But the majority of the power applications of these, you know, AI chatbots or whatever you want to say, it's cloud compute, right? So Microsoft announced they are doing $80 billion this year in new AI infrastructure developments. So as the primary backer of OpenAI, Microsoft is obviously positioned as a key player in the competitive AI landscape benefiting from its exclusive partnership with the partnership with the AI chatbot developer. Also, more than half of that planned $80 billion investment will be directed toward projects in the U.S. all right, speaking of Microsoft and large language models, some dorky news here, which I loved getting my hands on. This one. Instant screenshot, instant read from me. But Microsoft's new research has revealed some unforeseen insights on AI model performance and parameters. So in a new study from Microsoft, they've estimated the sizes of powerful AI models. Why does that matter? Well, the size of all of these large language models is typically shrouded in secrecy. No one knows. No one knows, right? No one knows the size of these large language models. For the most part, companies aren't, at least when we're talking about proprietary models, for the most part, companies aren't announcing it. It's different with open source models that you can download in fork. Well, because you're downloading so you can kind of deduce the size or the parameters in these models, right? So even if you're a non technical person, here's why this is important. That scenario that I just described for you, right? Let's say your, your company, there's 10,000 employees and all of you are using generative AI. Well, there's a good chance that that company, like OpenAI, is maybe losing money on that, right? Especially if you are power users, right? If you're, you're paying $20 a month for ChatGPT plus you're paying, I think it's like 50 or $100 now for an enterprise seat, right? But all of that power that you are needing from the model is being drawn from a data center. It is very costly, it is sucking up a lot of energy. So models, presumably even these large language models have been getting smaller. But until this study from Microsoft, we really didn't know it because the smaller the models get, the essentially less power they suck. However, most proprietary models don't want to say, hey, here's what's, you know, under the hood of our model because that's proprietary information. That's the secret sauce, right? Like the weights of these models. So the, the research is showing that the models, even the large ones, are getting significantly smaller. So here's some of the deets. Ready? So Microsoft suggests that as an example, Claude 3.5 sonnet contains 175 billion parameters, whereas O1 preview from OpenAI boasts 300 billion parameters. A good benchmark, which is one of the kind of first models, large language models that it was widely Reported to know the size was GPT4. The original GPT4 was reportedly about 1.8 trillion parameters. So they're there as an example. Claude 3.5 sonnet at. Let's see, I'm not good at math on the fly, but I believe that's about 10% of the size. So as models get smarter, as the process of, you know, reinforcement learning with human feedback gets a little better, as data source quality improves, post training improves, the models are essentially able to get smaller, which is huge. So OpenAI's smaller models, the O1 Mini and GPT4O Mini, are estimated to have have 100 billion and 8 billion parameters, respectively. So let me repeat that. So GPT4OH Mini, which is more capable now than the original GPT4 Turbo or, sorry, the original GPT4, GPT4 1.8 trillion parameters. GPT4OH Mini 8 billion. All right? It's a fraction of the size. So why is this important? Well, there's been all this conversation lately about AI hitting a wall, scaling. Hitting a wall, right? That would be true. I think people who are saying that don't truly understand the impact of these models being smaller and smaller because what that means, essentially, I think, you know, let's say we have a GPT5, right? And there's a GPT5 mini, all right? There's a likelihood that that GPT5 mini could live on a device, right, as computer hardware. So as these GPU chips in our computers, as these NPU chips, these neural processing units that are kind of like referred to as AI chips, right? As these tpu, these data center chips, right? As the chips get more powerful and at the same time as models get smaller, guess what that means, that re that reduces kind of this carbon footprint. But here's the big piece, right? One of the biggest reasons that AI adaption hasn't been like a thousand percent is companies, rightfully so, are worried about their data. They're worried about their privacy, right? Because they're essentially like, oh, we don't want to send all of our data and all of our information to the cloud, which is, is not smart, because guess what, big companies, you're already storing all that information anyways on cloud servers. But I'll leave you to just go ahead and think about that yourself in the corner. Like, oh, okay, why am I okay with us using cloud hosting for all of our important data, But I'm not going to use that same provider to use AI models. Whatever. That's your own really smart decision to ponder over. However, as These models become smaller in parameter size. That means, in theory, we will be able to run proprietary state of the art large language models on device, Edge AI running these locally in the very near future. Therefore, you won't need to worry as much about privacy and security because you're not sending all of that data, which a lot of times it's proprietary sensitive, whatever, you're not sending it to a third party. It is on prem, it is on your device. It is edge AI. So this new study from Microsoft might seem dorky, it's a bunch of numbers, but it is actually huge because like I said, we haven't really known, aside from GPT4, which we kind of knew from a lot of Reporting was about 1.8 trillion parameters, but we didn't really know how much are these, how big are these newer models? Well, they are a fraction of the size. And that is why, you know, when everyone's talking about, oh, AI is going to hit a wall. No, it's not. Because these models now are less than 1% of the size and exponentially more powerful. Those two things cannot coexist and not lead to exponential scalability, period. I don't know, I think sometimes like to just make. People like to make these, you know, weird claims like, oh, AI's hitting a wall, right? It's like, oh, right, like as a reason for not using it or as a reason to like, I don't know, be like a hipster skeptic of AI, right? But that's. I don't know. One plus one in this instance is going to equal two, no matter how much you want to throw in this Common Core math that I don't understand. Does anyone know Common core math? Does 1 plus 1 still equal 2? I don't know. All right, that's it, y'. All. Let me go over a quick recap of all the AI news that matter. Sorry, got on a little weird tangent there. So here we go. Story number one, Open AI through CEO Sam Altman's blog post, saying that they are confidently pursuing AGI, they know how to build it, and they're planning for AI agents to join the workforce in 2025. Next, we're going to be seeing a ton of AI, probably too much, at the CES Consumer Electronics show in Las Vegas this week. Next Meta thankfully shut down their AI profile experiment amid user backlash and technical issues. Next, Elon Musk Grok 3 model is facing delays and was not released in 2024 as promised. Speaking of delays, OpenAI's media manager tool was delayed amid IP concerns and legal challenges, Microsoft is reportedly planning $80 billion investment in AI infrastructure. New AI infrastructure for this year. And new Microsoft research is revealing some new and I think exciting insights on the size of large language models. All right, was this helpful? Or do you prefer spending hours every single day sifting through, reading the news and worrying about how it might impact your career? That's what I do. Stop wasting your time. We do this. So almost every single Monday, we do this AI news that matters, right? It makes sense, right? I do this every day for a living. I talk to the smartest people in AI. We put together an AI newsletter. I read over the AI news every day. So just join us Mondays. Please join us every day. But if you can only join us once, join us Mondays to go over the AI news that matters. If this was helpful. 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