Everyday AI Podcast – An AI and ChatGPT Podcast - EP 433: AI News That Matters - January 6th, 2025

Episode Date: January 6, 2025

Sam Altman JUST said that AI agents may "join the workforce' in 2025. Just hype? Or a preview of our near future? Tune in to find out about the OpenAI CEO's latest projections and a TON of other AI news that will impact how you work. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:1. Meta & AI Content2. OpenAI Media Manager Delay3. Microsoft's AI Model Research4. OpenAI's AGI Progress5. Grok 3 Model Release Delay6. AI Implementation in Consumer ProductsTimestamps:00:00 OpenAI plans AGI workforce integration by 2025.04:34 OpenAI preparing for AI workforce integration08:13 AI agents entering workforce; OpenAI release anticipated.13:27 Meta halted AI profiles over user concerns.17:26 Elon Musk's Grok 3 model faces delays.19:04 Grok AI depends too much on Twitter.23:23 Generative AI blends and transforms copyrighted content.25:07 Microsoft invests $80B in AI infrastructure 2023.30:02 AI model size comparison: Claude, OpenAI, GPT-4.31:47 Smaller models enable device storage, easing privacy concerns.35:24 OpenAI pursuing AGI; AI developments face delays.Keywords:Meta, AI content, ethical issues, AI-synthesized data, social media scraping, OpenAI, media manager tool, IP concerns, legal challenges, opt-out methods, generative AI, copyright issues, AI training, Microsoft, AI investment, AI model research, model parameters, Claude 3.5 SONNET, GPT-4, AI model size, on-device processing, AGI, AI Agents, Elon Musk, GROC 3, CES, AI advancements, Samsung, AI-enabled fridges, LGSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

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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 experiment. with AI generated profiles. Open AI 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 news that are helping everyday people, 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 at your everyday AI.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. talk to hundreds of the leading experts in generative AI across the entire world. It's all there for you for free. Go watch, listen, read your EverydayAI.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 bogey joining 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 Open AI 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 strides 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 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 a 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 join the workforce and materially change the output of companies. So, Open AI'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, Open AI 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, St. Altman said that they are thousands of days away to superintelligence,

but now, at least on his personal blog post, which 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 goalposts 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, too, 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 HGI. 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 Chad 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 thing, 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. Open AI and Chad GPT are winning the kind of LLM or 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 Open AI 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, 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 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 chat GBT, even if you have a free account, you know, you can use chat GBT search. Also, you can use chat GBT as a couple of months ago without even being logged in. So a lot of those things are really adding to kind of 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 co-pilot 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 Open AI, according to report, reports is set to be releasing operator or at least releasing some details around their operator agent 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 Open AI 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 GPD-5, in 01, in 03, so these O-level models right now don't have access to any tools. So maybe that could be the thing that pushes Open AI 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 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 of things that have already been announced or leaked or previewed. Samsung is aiming to introduce its AI for all, every day, 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 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 this show, I've had a lot of problems 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. Invidia is also expected to unveil, which might be one of the biggest announcements coming out of CES. We'll see. and Vyme 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 announcements will be coming Tuesday. So make sure you check out our newsletter for that. Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience. Meet Firefly AI Assistant.

Now live in the Adobe Firefly app, the all-in-one creative AI studio. Powered by Adobe's creative agent, Firefly AI assistant lets you start with your vision, just describe what you want, and shape the outcome as it takes form with the assistant. The assistant orchestrates multi-step workflows, drawing on 60 plus pro-grade tools across Adobe Creative Cloud apps,

including Photoshop, Illustrator Premiere, Lightroom Express, and more to help bring your ideas to life. You can also get started with creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible so you can refine, redirect, or take over at any time. You stay in the driver's seat as the creative director.

Adobe Firefly AI assistant now in public beta. See it today at firefly.adobie.com. So yeah, big bogey face says currently at 0% of artificial super intelligence. Marie, I'm 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 going to 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,

to eventually squash this project. So if you missed it, it 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 a 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 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 23, but decided to shut down most of them by summer of 2024 with the last profiles now disappearing recently. So here is an AI feature that I'm glad. It's squash. 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 GPs and then you can use them across meta's different 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 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 GROC 3. So Elon Musk's GROC 3 model is facing delays. So the anticipated launch of Elon Musk's GROC 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 limitations. So Musk previously stated.

that GROC 3 would be released by the end of 2024. But yeah, here we are in 2025 and there's no signs of GROC 3, which is to the surprise of probably no one unless you are absolutely addicted to everything that Elon Ma 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 GROC is a serious model, mainly because it is largely trained on Twitter data, which is a cesspool.

So reports suggest that an intermediate model, GROC 2.5, may be released before GROC 3, indicating potential setbacks in development. So Musk admitted in an August interview that GROC 3'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 GROC 3's pre-trained. 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 GROC's move here because they did kind of preview a web-only interface, so at least moving the GROC 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. And 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 go use their roast me feature or to roast a certain X profile. But aside from that, I don't see any business anytime soon actually using GROC 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 GROC. And yes, they built their super gigafactory of compute and they're 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 Lama, 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 Grock 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, Open AI's media manager tool also delayed amid IP concerns and legal challenges. So Open AI'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. Open AI 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 Open AI. Insiders suggest that the tool was not seen as a priority within, Open AI with reports indicating little internal progress or focus on its development. Open AI 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 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 is, 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 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 essentially, that's how generative AI works, right?

It's instead of reproducing a one-to-one copy of something that is copyrighted, instead, it uses, you know, 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 Open AI 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 resolve ongoing intellectual property issues, highlighting challenges and ensuring compliance,

and the burden it places on creators to, to manage their own rights, right? Yeah, it's kind of like, and this isn't just open AI, 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 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. deploying AI-driven applications. So the investment comes in the wake of a surge in generative AI interests, obviously following OpenAI's checked GPT 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 has been the most valuable company in the world by MarketCap,

which I told you all like two years ago and don't believe me. But also it means that data center. are growing. It's meaning that we need more, more power, more energy to power all of these, you know, giant clusters of GPU chips that are running, you know, inference in the cloud, right? So, you know, if your company is using AI in a 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 Open AI, Microsoft is obviously positioned as a key player in the competitive AI landscape benefiting from its exclusive 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 announced. it's different with open source models that you can download and fork, well, because you're downloading them. 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 company, there's 10,000 employees and all of you are using generative AI. Well, there's a good chance that that company, like Open AI, is maybe losing

money on that, right? Especially if you are power users, right? If you're paying $20 a month for chat Chbchee+, 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 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. For example, Claude 3.5 Sonnet contains 175 billion parameters, whereas 01 preview from Open AI 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 there, as an example, Claude 3.5 sonnet, 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 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 01 mini and GPT40 mini, are. are estimated to have 100 billion and 8 billion parameters, respectively. So let me repeat that. So GPT4O mini, which is more capable now than the original GPT4 turbo or sorry, the original GPT4, GPT4, 1.8 trillion parameters, GPD40 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 GPT-5. 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 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 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. It's like, oh, 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 one plus one still equal to? I don't know. All right.

That's it, y'all. Let me go over a quick recap of all the AI news that matters. 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-Grock 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 has 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.

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