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Dominance of OpenAI in the LLM Race: Current State and Predictions for 2025
As the world of Artificial Intelligence thrives and evolves, multiple tech giants are vying for the top spot in the race toward developing superior Large Language Models (LLMs). Key players in this race, including ChatGPT, Gemini, Perplexity, and Claude, have been monitored for their growing interest using Google Trends. However, one noteworthy Leader that consistently demonstrates higher interest and search volume is OpenAI's ChatGPT, making it a household name synonymous with AI for the majority of the public.
Dominance of OpenAI's ChatGPT
OpenAI's strategic and successful marketing strategy, launched at an opportune time, has resulted in its widespread recognition and usage. It competes closely with Google Gemini, which faces challenges due to its less user-friendly interface and difficult access. OpenAI is predicted to maintain its dominance in the LLM given its well-rounded front-end that includes reasoning models, internet access, and different tools.
Impact on Decision Making
The comprehensiveness of ChatGPT's front-end holds significant weight in shaping the AI space. This is especially crucial for non-technical business leaders who often make decisions based on features and interfaces, rather than on technological capabilities alone, which both Google Gemini and Claude continue to lack.
Advancements in Smaller Models
Given the increase in powerful hardware, the future trend is expected to shift toward smaller language models. These could be particularly useful in everyday personal devices, marking advancements in Edge AI. This shift is attributed to the speed, security, and reduced environmental impact of these smaller AI models. OpenAI is making significant progress in developing these smaller, more powerful language models, which is viewed as another key advantage.
OpenAI Financial Struggles and Strengths
Despite achieving supremacy in the AI space, OpenAI has experienced financial hardships, including a reported $5 billion loss in 2024. However, OpenAI continues to leverage its large user base, which generates valuable data for improving models, contributing to training data and thus, refining their AI technology.
Edge of OpenAI in the LLM Race
While there is an ongoing stiff competition from Google and other tech giants, OpenAI continues to excel in the development of smaller language models. Their model, GPT-4o Mini, with 8 billion parameters, has demonstrated impressive performances on standard evaluation metrics, signifying OpenAI's promising prospects in the LLM race. Furthermore, partnerships with tech giants Apple and Microsoft indicate OpenAI's strategic importance and reliability in future AI developing endeavors.
The Future of Large Language Models
In the increasingly tightening AI race, OpenAI is predicted to remain a leader. While the competition from Google grows, smaller players such as Claude might struggle to remain competitive. The future of this ever-evolving AI industry might see numerous models being orchestrated by one large model, also hinting at the potential for mixed expert models.
Deciphering the LLM Race: Final Thoughts
The LLM race holds considerable significance due to its wide application across business, career, and personal domains. It is the driving force behind numerous software and enterprise solutions, carrying the potential to redefine personal and professional lives globally. Therefore, industry leaders, decision-makers, and anyone interested in the future of AI must stay abreast of the ongoing developments in the LLM race.
Boosting AI Knowledge for 2025
With technology improving at a rapid pace, it is recommended for everyone to equip themselves with AI knowledge to stay ahead of the curve. Resources for learning about AI are abundant and could range from daily newsletters to podcasts and articles. They could provide valuable insights into the current state of AI, potential future leaders in the LLM race, and the far-reaching impact of AI developments across various domains. Industry leaders, businesses, and AI enthusiasts are all encouraged to join the dialogue to learn and contribute.
As 2025 approaches, the LLM race is set to be more exciting and transformative than ever, with OpenAI leading the way. Remember, subscribe to reliable sources, stay informed, and dive into the exciting world of Artificial Intelligence.
Topics Covered in This Episode
1. OpenAI’s Dominance in LLM Space
2. Shift Towards Smaller Language Models
3. LLMs and Internet Connectivity
4. OpenAI's Focus and Competition
5. Popularity of Different AI Systems
6. LLM Predictions and Outcomes
Podcast Transcript
Jordan Wilson [00:00:17]:
Will OpenAI run away in the large language model race in 2025, or has Google already caught them? Or maybe anthropic Claude will wake up from its late 2024 nap of not too many updates and come back and retake all of the spotlight. We're gonna be talking about that today in a lot more on everyday AI. What's going on y'all? My name is Jordan Wilson and welcome to everyday AI. Before we get started, have to give a quick shout out to our partners at Microsoft. So why should you listen to the WorkLab podcast from Microsoft? Because it's the place to find research backed insights to guide your org's AI transformation. Tune in now to learn how shifting your mindset can help you grasp the full potential of AI. That's w o r k l a b. No spaces available wherever you get your podcast.
Jordan Wilson [00:01:19]:
Another place you can get your podcast, well, right here, but our website. So, if you're new here, thank you for tuning in. My name is Jordan Wilson. This is everyday AI. We do this every day. This is your daily livestream podcast and free daily newsletter helping us all learn and leverage generative AI to grow your companies and your career. So you could spend, I don't know, hours a day trying to keep up, trying to see what it all means, or you could let us do that. Tune in every day, subscribe on the podcast, and go to our website, your everydayai.com.
Jordan Wilson [00:01:52]:
On there, it's like a free generative AI University. 100, hundreds of episodes. You can go back, watch them, listen to them, read all the important insights on our website, all for free. So that's your new home away from home, so make sure you go check that out. Alright. Before we get started, now I'm excited today to talk about the large language model race in 2025. Not quite a prediction show. Gonna Gonna have that coming for y'all in 2 weeks.
Jordan Wilson [00:02:17]:
Been spending, like, dozens of hours on that one. Alright. But before we get started, let's talk about, as we do almost every day, the AI news. So Microsoft has announced a $3,000,000,000 investment to boost AI and cloud services in India. Microsoft's significant investment in India highlights the country's growing importance in the global tech landscape, particularly in AI. So Microsoft plans to invest 3,000,000,000 to expand its AI and cloud services in India. The company aims to train an additional 10,000,000 people there in AI skills, which could enhance job prospects and career growth for many in the tech sector. CEO Sadia Nadella emphasized the exciting diffusion rate of AI in in India, indicating a strong market potential for AI technologies.
Jordan Wilson [00:03:07]:
Microsoft operates 3 data center regions in India already and is preparing to launch a 4th aiming to develop a scalable AI computing ecosystem for startups and researchers. Alright. Next in AI news, Google is reportedly building a new AI team that aims to simulate the physical world with advanced models. Yeah. More world model updates. These are important. So Google is making headlines with the formation of a new team at Google DeepMind focused on developing AI models that simulate the physical world. Here's why it's pretty noteworthy.
Jordan Wilson [00:03:44]:
Well, this person leading it, former OpenAI employee. So Tim Brooks, formerly a co lead on OpenAI's video video generator, Sora, will lead the new team, which aims to tackle, quote, unquote, critical new problems in AI modeling. The team will collaborate with existing projects such as Google's Gemini, Veo, and Genie enhancing capabilities and image analysis, text generation, and video production. So Google's Gemini's, Gemini series is already recognized for its versatility in AI task, while Veo focuses on video generation, and Genie simulates games and 3 d environments in real time. So, this development of world models could revolutionize different sectors, including visual reasoning, simulation, and interactive entertainment, potentially inter impacting how video games and movies are created. Alright. Last but definitely not least, you're gonna be hearing a lot more about CES this week, but CES is off to a big bang. So the biggest tech conference kicked off hours ago with NVIDIA CEO Jensen Huang delivering the keynote address.
Jordan Wilson [00:04:58]:
Alright. So like I said, we'll be covering this a lot more in today's newsletter and throughout the rest of the week. We'll probably have a dedicated episode, maybe on Thursday or Friday recapping everything new. But here's what NVIDIA announced, and why did NVIDIA, keynote, the one of the biggest tech shows in the world. Right? The consumer electronic show. Well, because everything that they announce impacts everything in technology. Right? They are literally powering the generative AI movement, with their GPU chips. So speaking of that, some new GPU announcements, the RTX 50 series GPU was announced with Blackwell architecture.
Jordan Wilson [00:05:37]:
They have 4 new models of that, which are ridiculously priced. The RTX 5070 starts at $549. How's how's that even possible? Yeah. If if you're not a dork, in RTX 5070, the new model for 549 is is baffling. Also, the g p the GB 10, which is the Grace Blackwell superchip for desktop AI, computing, announced updates with the Cosmos platform for physical AI and robotics training. Probably one of the biggest updates we saw last night, NVIDIA getting into the desktop computer game with project digits, its first supercomputer. It's priced at $3,000, but it is ridiculously powerful, more powerful, than literally any computer that you can buy right now. Also, they announced a partnership with Toyota for autonomous driving systems, and also Uber and NVIDIA partnered to enhance AI technology in autonomous vehicles.
Jordan Wilson [00:06:41]:
So, yeah, a lot more AI news in our newsletter. So please go to your everyday aidot com. Sign up for that free daily newsletter. Alright. Yeah. Fred just said project digits. Wow. Yeah.
Jordan Wilson [00:06:54]:
Juliet, the the keynote, I believe you can go replay that. We'll leave that in the newsletter today as well. Alright. I'm excited for this. So we'll open AI runaway in a large language model race this year. So this is actually, your show. So I in the newsletter yesterday, I said, hey. We got our hot take Tuesday coming up.
Jordan Wilson [00:07:14]:
What do you want to hear? So, if you are a long time listener to the podcast, I literally started this thing for you guys. Right? I noticed that when I was trying to learn more about, generative AI AI like 4 or 5 years ago, I noticed it was only for highly technical people. So I wanted to create something that's for all of us. So sometimes in the newsletter, I'm like, yo, what do you guys wanna hear tomorrow? I'll stay up all night, putting together a show just for you guys. So this is technically a user request. Alright. But let's talk about it. So right now, I'm really just focusing on OpenAI, Google, and Anthropic for this, you know, who's gonna run away with it, episode.
Jordan Wilson [00:07:54]:
Here's why. Obviously, some of the biggest names in the game are playing different games. Right? Microsoft in their Microsoft 365 Copilot right now is using OpenAI's GPT 4 0 to power, their system. So a lot of people are like, oh, what about Microsoft? Well, even though they are developing, their own models, their 5 models are, fantastic small language models. They are, reportedly gonna be offering, new models or new choices in the future aside from OpenAI's GPT 4, they're not a player in this game, not in the large language model race. Also Meta. Meta is going open source ask, not truly open source, but I think they're playing a different game as well. And there's all the Chinese companies as well that I think are going to be, really thrusting themselves into the conversation for 2025.
Jordan Wilson [00:08:49]:
And and like I said, we'll have our whole 2025, prediction shows. I think we're gonna break it up this year, in a couple of weeks. But this is just about the large language model race. Who is going to win it? Well, first, let me start by saying, why does this matter? Well, you probably are using March language models every day if you're listening to the show. That's why it matters. Right? Probably in every aspect of of your business, you you know, your company, your career, your personal life, you're probably using AI a ton. So this kind of frontier model race, right, it impacts us all. Right? And even if you are not a huge, you know, large language model user right now, probably there's thousands of name brand pieces of software out there that you probably don't even know are leveraging these technologies.
Jordan Wilson [00:09:46]:
Right? So that's the other thing. At least when we talk about the quote, unquote big three here, with Google, OpenAI, and Anthropic, their APIs or their back ends are powering just about everything. There's very few enterprise softwares right now that are not using AI, that are not using large language models. And in most cases, in the overwhelming majority of the time, they're using one of these three models. So even if you're not logging in into the front end of these tools, you're probably benefiting from them. Right? They're starting to seep into every aspect of our daily lives. That's why this race, this large language model race is incredibly important. Alright.
Jordan Wilson [00:10:31]:
Livestream audience, let me know Who do you think is gonna win this race? Alright. So is it a is it going to be a, OpenAI? Is it going to be b, Google? Is it gonna be c, Anthropic? Might it be d, Meta, or you can leave e, other in the comments. I'm curious what everyone else thinks. Right? Part of this doing this everyday AI thing, together with you all is learning from you. Right? I I come in from my perspective. I'm lucky enough to spend the majority, or maybe dorky enough to spend the majority of my day playing with large language models, testing new features, helping large enterprise companies. Right? People are always like, oh, Jordan, how does this everyday AI thing, you know, make money? Well, we're lucky enough to have great, sponsors and partners like Microsoft, but enterprise companies hire us. Right? And they're like, hey.
Jordan Wilson [00:11:24]:
Hey, Jordan and team, we have, you know, 5,000 employees or 500 employees that need to learn ChatGPT or we need to learn Microsoft Copilot, and then we go help them. So, you know, I'm lucky enough to be able to interview Copilot and then we go help them. So, you know, I'm lucky enough to be able to interview people from these companies, but also help, enterprise organizations and small and medium sized businesses actually learn these, but I wanna learn from you guys. So, yeah, a lot of people here so far are saying, you know, Marie said, Marie said a. Kathleen said, a, which is OpenAI in a landslide. Fred is team Google. Douglas says OpenAI in Microsoft. Jackie says it's a 2 horse race here, between OpenAI and Google.
Jordan Wilson [00:12:07]:
A a lot of people. No no single votes for Anthropic. That's interesting. It's interesting. Right? Depending on where you look, where you read, you would think anthropic is the only large language model out there. Right? I think people on Twitter, for whatever reason, are very, very bullish on anthropic. Right? Like, you would literally think no other large language model exists. So that's why I like asking, you all.
Jordan Wilson [00:12:35]:
But, let's let's go ahead and talk about it. And I wanna give you three reasons. Alright? Yeah. This is hot take Tuesday. I'm gonna accidentally go on a rant. I'm gonna, you know, keep Fred on the treadmill longer than normal. Sorry. Or if you're walking your dog.
Jordan Wilson [00:12:53]:
Alright? But, I'm gonna give you three reasons why OpenAI might win this race and why they might not. And at the end, I'm gonna give you my honest take who is going to win this. And, again, let me remind you of the importance. Your company is probably making long term, maybe 6, 7, 8 figure financial decisions on what large language model they use, whether you're using it on the front end, in a team, or an enterprise account, or maybe you're building something on the back end with the API. There's a good chance your company is making major investments in large language models and how you use that to change knowledge work. So, keep that in mind. I always like to reframe this and tell you why it's important. So let's start with reasons OpenAI might not win the large language model race.
Jordan Wilson [00:13:49]:
Yeah? You might you might be curious on this one because you're like, Jordan, you talk about OpenAI all the time. Well, yeah. It is. It I mean, OpenAI is the the company that's technically started the generative AI wave. Yes. The transformer technology in GPT, originated with researchers at Google, but OpenAI in November 2022 technically started this whole generative AI race with its AI chatbot ChatGPT, even though there had been many different large language models available for developers prior to that. But reason number 1, they might not win the race even though they kind of started it is because I think the race is going to make way for reasoning and agentic models. Or in other words, the the way that we look at this race, right, like who's winning, we look at benchmarks.
Jordan Wilson [00:14:43]:
Right? We look at things like MMLU or MMLU pro or human eval. Right? We look at all these dorky benchmarks. But then we also look at, head to head scores. Right? So probably the most popular one out there is the LM arena or the chatbot arena, previously under the hugging face umbrella, but now it kind of has its own domain. So this is where millions of users have gone on and they put a single prompt in, and then they get 2 outputs, and then they judge which one is better. Alright? And that, gives us what's called an ELO score. So think of it like, you know, how, they had the blind taste test for, you know, Pepsi and Coke. That's kind of what this is.
Jordan Wilson [00:15:27]:
There's, dozens of Frontier models, that go head to head blind scores, the top model, the model that wins the most essentially gets the most points. I think in 2025, these big companies are gonna care less. I think in 2023, benchmarks in Elo scores largely drove the conversation. And it actually I think just these two metrics influenced, decision makers on which model they should try. And I think part of it rightfully so. Right? Because when you looked at capabilities, again, up until the latter part of 2024, these two benchmarks, these two metrics alone, right, the, chatbot arena and benchmarks, that told the whole story. Right? And that's what companies race toward. I don't think it's gonna be like that as much in 2025.
Jordan Wilson [00:16:30]:
I think companies like OpenAI, are gonna stop caring less. And you can't say that they didn't care. Right? Because what you would see anytime one of these companies, you know, released a model, and then they, you know, were, kind of crowned the top of the chatbot arena board. You know, literally, you had a day later, other company would release an update to their model that they'd been sitting on because they're like, oh, we got, you know, overtaken on the top of the chatbot arena board. Right? So you can't say that this wasn't a driving factor for releases in 2023, 2024. It was. But I think in 2025, we're gonna be talking much, much more about business value. Right? I don't think it's going to matter as much about benchmarks and Elo scores because we're already topping out.
Jordan Wilson [00:17:20]:
Right? If you're a dork and you follow MMLU like me, I mean, all the new models are gonna be 88, 89, 90, 91, 92. Right? They're gonna be in the in the high eighties, low nineties, which is smarter than the smartest human, smartest single human, and it's not even close. Right? So we've already gotten past the point when large language models, you can't make, you know, as long as you know what you're doing, which a majority of the people talking about AI or sharing about it online literally don't know what they're talking about. But as long as your company knows what they're doing, and they probably do because you're investing in the technology. Right? There's a certain point of of diminishing returns. I think once you hit a certain point on these benchmarks, once you hit a certain MMLU, right, once you hit a certain Elo score or a head to head win rate against the other models, like, I think there's a point of diminishing returns where it's like yes. I think it turns into a simple yes or no. And I think the, the the smart, companies have already figured this out.
Jordan Wilson [00:18:19]:
Right? You you know, overfitting a model to go from, you know, 88.7 to an 89 on the MMLU is not going to be a driver driving factor anymore. So what I'm trying to say is OpenAI may not be atop the benchmarks, atop the leaderboard, for the majority of 2025. Like, they've probably spent, 80% of the time since these benchmarks, became widely used since the chatbot arena, started becoming, you you know, a main discussion piece. They probably spent 80% of their time at the top. I don't think it's gonna matter anymore or as much. Alright. Fred said people do keep leaving OpenAI. That's the truth.
Jordan Wilson [00:19:07]:
Alright. Let's keep going Because OpenAI still has their old model, quote, unquote, old. Right? GPT 4 o, which was announced in May. It is still batting at the top of these, like, chatbot arena boards, which is another reason why I think they might not technically win the race. I think the race is just gonna be redefined, right, in terms of how we, measure the large language model race. I think it's gonna be more about creating business value than it was about these other things. So reason number 2, OpenAI might not win the race. ChatGPTsearch is seriously flawed.
Jordan Wilson [00:19:56]:
Seriously. Okay? So without going into, too much of a side tangent, most large language models, aside from Claude for whatever reason, are not connected to the Internet. Alright? So that is problematic. So Internet connectivity is a huge part at least of using these models on the front end. Because in often, sorry, in in many cases, the training data. Right? So, essentially, think of large language models. There's a training cutoff. Right? So, you know, you have all these smart researchers.
Jordan Wilson [00:20:32]:
They, you know, they gobble up all the information on the Internet. A lot of it copyrighted. Right? They have smart humans train these models and then release it to us all. And there's usually a knowledge cutoff, but that knowledge cutoff is generally somewhere from 9 months to 18 months in the past. Right? And most things you're working on, you need up to date information. So a large language model's ability to connect to the web is huge. Alright? So previously, OpenAI used, they had a feature called browse with Bing. Alright.
Jordan Wilson [00:21:08]:
And then I believe it was late, we'll just say, October, October, November of 2024, OpenAI rolled out ChatGPTsearch. So from a UI UX, right, so from a user interface, user experience perspective, there's great things. Right? It's bringing aspects of Google Map. It's bringing these rich snippets. Right? ChatGPT search. It's it's they're still using, as far as we know, the, the Bing, the Microsoft Bing technology somewhat on the back end. They haven't really described it a lot. But JetGPT searches how open AI and how JetGPT, stays connected to real time up to date information past its knowledge cutoff.
Jordan Wilson [00:21:54]:
It's seriously flawed, though. Browse with Bing to not have these problems. And I think this is important to talk about. You know, I always keep saying, like, oh, maybe I'll have a dedicated show on this, but I know at any time, OpenAI could just fix this. They have to know it's a problem. Here's what's seriously flawed right now. Yes. It's great.
Jordan Wilson [00:22:15]:
You can ask ChatGPT what's going on this weekend in Chicago, the city I live in. Right? It'll give you this nice Google esque like search results, right, with rich snippets lists. You you know, little photos. Nice to use. Right? Now we're seeing rollouts on mobile, that give you, essentially map results. Right? Very nice and intuitive to use. However, iterative prompting is broken when you are using ChatGPT, search. Okay.
Jordan Wilson [00:22:45]:
So there's a little globe icon. Sometimes, ChatGPT will use this feature, or call this tool on its own even if you don't call to it. But, so much of using a large language model is what happens after the first prompt. Right? It is the iterative nature. It is going back and forth. Right? It's going like as an example, you know, our prime prompt polish, you know, our PPP method. It's not just putting in one giant prompt. It's having a conversation.
Jordan Wilson [00:23:13]:
It's going back and forth after your first response. For whatever reason, since it came out, ChatGPT search, it gets stuck in a loop. Right? You can't really iterate or build upon, a result. I don't know why. It's been broken for many months. And that's concerning when a feature that big, not a 100% of the time, but a good chunk of the time, it gets stuck in a loop. So let's say if you ask as an example, what's the biggest AI news? Right? And then ChatGPT is gonna use ChatGPT search because it knows it needs real up to the up to date information for that. It might spit out some some trends.
Jordan Wilson [00:23:54]:
Right? And then you go back and you refine it and you say no. Please give me the top AI news for January 2025. Guess what? It's going to, in most cases, spit back the exact same response. I don't know why OpenAI hasn't fixed this. It's a little concerning because there's 100 of millions of people using, ChatGPT and ChatGPT search. It's concerning that they haven't fixed this. I know I'm not the only one complaining about it, but I've been complaining about it pretty pretty loudly, but that's some reason they might not win. The fact that they haven't fixed this yet and it has been a terrible, terrible user experience for multiple months.
Jordan Wilson [00:24:36]:
I get it. December, they shipped like 2 years worth of features and updates, but it looks like chat gbdsearch just got glazed over. Right? The core functionality. Because at its core, it is broken. If you compare it to browse with Bing, which, after the browse with Bing updates of of the latter part of 2024, it was essentially a perplexity light already. Alright. Reason number 3, OpenAI might not win the large language model race. Well, they're burning cash.
Jordan Wilson [00:25:15]:
Right? And they're facing an increase. This is all reportedly right? Reportedly, OpenAI lost 1,000,000,000 of dollars, in 2025 or sorry, in 2024. So according to reports, OpenAI experienced a $5,000,000,000 loss in 2024. So that's another reason why OpenAI might not win the large language model race. They're burning cash, right, reportedly, and they need to turn a profit. They they did just release, their new and more expensive pro plan. That's $200 a month. OpenAI OpenAI CEO Sam Altman did go on Twitter and say, oh, we're actually losing money on this.
Jordan Wilson [00:26:06]:
Right? So, I'm sure investors weren't thrilled, to see that tweet, which led to a lot of news and and media coverage on, hey. OpenAI is losing more money. So one reason they might not win it is because the advancements that they might wanna be working on from a large language model perspective might not be getting the resources that it needs. They're losing key people like we talked about at the beginning, at the beginning of this show, You know, Google's new AI team, and now they have Tim Brooks, formerly a co lead on their video generator, Sora. So they're burning cash. Right? They're reportedly losing money. And that might yeah. I mean, between that and their increased, at least, from an external, perspective, their increased focus on HEI, on ASI, so artificial general intelligence, artificial superintelligence.
Jordan Wilson [00:27:03]:
Right? Their increased external focus on this could, in theory, keep them from their internal, daily driver, which is improving their two classes of models. Right? So they have their GPT class of models. So we have GPT 4 o. And then they have their reasoning class of models, the o one, you know, so o one, o one mini, o one pro, and then you have your o three, which may or may not get released in 2025. We'll see. But they could lose their focus on actual large language models chasing agentic AI, chasing AGI, chasing artificial superintelligence. So it could keep them from that day to day race. Alright.
Jordan Wilson [00:27:51]:
Before we get into the three reasons I think they might still win the large language model race, let me tell you a little bit more about Microsoft WorkLab. So why should you listen to the WorkLab podcast from Microsoft? Because it tackles your burning questions about AI at work, like how can I guide my org's AI transformation? How can AI help maximize value and create new products and business models? What mindset shift do we have to make if we want to tap into its full potential? Find the answers on WorkLab. That's worklab. No spaces. Available wherever you get your podcasts. Alright. Straight into it. Now three reasons why OpenAI might win the large language model race of 2025.
Jordan Wilson [00:28:36]:
Number 1, they got the users, baby. They got everyone. They got the users, and with the users comes the data, and with the data comes better models. Right? Still, I don't think people realize how good of a deal that $20 a month to use it, a pro plan of and Claude anthropic. Right? Even though if if you look at Claude the wrong way, you you hit a rate limit. Right? I saw someone in the comments here on our livestream. Someone, was tweeting on the livestream. I think it was Michael just about, like, rate limits.
Jordan Wilson [00:29:12]:
Right? Yeah. But, you you know, even at these $20 plans that are extremely $20 a month plans. Right? From Microsoft Copilot, from ChatGPT, from Gemini, from, Anthropic Claw, from all these other large language model makers. If you're not opting out of data, you are the product. Right? And so many people don't know any better. So many people don't know how to turn off their training data. Right? And there's more, I would say, protection over your data as you are on higher plans. Right? So, I have normal, you know, normal paid accounts.
Jordan Wilson [00:29:54]:
I have team accounts. I have enterprise accounts. Right? Because we, advise companies on how to use this at scale in their organizations. Right? So I know the different, kind of data controls that you have at different levels. So even at the base level or the free level, right, so many people are on free plans, and they're just dumping in all their company info. That's why I think they're going to probably still win the wireless language model race. They have the data. They have the users.
Jordan Wilson [00:30:27]:
Alright? So let's look at this here on my screen for our livestream audience. This is just a, Google Trends comparison. Alright. And this isn't like overall searches. This is just interest over time. Right? Comparatively. So comparing ChatGPT to Gemini to perplexity to Claude. Right? Just as an example, talking about some of the popular, AI systems there.
Jordan Wilson [00:30:54]:
And, yes, perplexity is more of an answers engine. So that's why I didn't really include them in this conversation either. Right? I'm talking about large language models. For the most part, perplexity, you just use one of these models and then you its technology is more of an answers engine. Alright? But what this graph shows is the interest, the search volume, and the users for ChatGPT are 3x5x greater than all other competitors combined. It is not even close. OpenAI is synonymous with AI. Right? Which is weird because artificial intelligence has been around for many decades.
Jordan Wilson [00:31:37]:
But you ask the average person on the street, hey. Have you heard of AI? Not not all you all. Right? You guys like me have probably used dozens of large language models. Right? But ask the average non everyday AI listener. Right? Hey. Do you know anything about AI? They're gonna say, oh, like ChatGPT. Right? My mom uses ChatGPT. I didn't even tell her to do it.
Jordan Wilson [00:32:02]:
Right? She probably did it from, I don't know, maybe listening to the show. So hi, mom. But, you know, most people don't know anything about AI. Right? We live in a bubble here on this show, on social media, in our own echo chambers of artificial intelligence. Most people when they hear a AI, they just think Chad GPT. Right? Not the fact that, you know, traditional machine learning and neural networks have been widely used for many decades. It is synonymous. That is one of the, the benefits of OpenAI's go to market strategy.
Jordan Wilson [00:32:37]:
They made us huge splash. I think, you know, at the end of November 2022, it became especially heightened. You know, we were still, you know, kind of in this COVID phase. Right? People were spending more time indoors using technology. Right? More people were working at home, and it just came at the perfect time, and it blew up. But they have more users, more interest, more name brand recognition than everyone else combined, and it is not even close. More users, more data means you're probably gonna win. Alright.
Jordan Wilson [00:33:11]:
Let's keep it going. I'm gonna wrap this one up. Try to go quickly. Reason number 2, they might win. Yeah. Good good question here. Actually, Cecilia is saying, doesn't Google inherently have the potential users? Kind of. Right? Yes.
Jordan Wilson [00:33:27]:
Google has 100 of millions of users of their technology. What people don't know is you have to be on a paid plan. Right? So, it's it's an additional add on right now. Right? Gemini. Or if you are on a Gmail plan, you you know, you can use Gemini for free. But for the most part, it is extremely hard to use Gemini on the front end. It is hard for organizations to roll this out. Right? You have to have literally, like, a degree sometimes in order to give your organization, a pro version of Gemini.
Jordan Wilson [00:34:02]:
So, yes, I do believe that Google will catch them eventually. But right now, in terms of active users, right, ChatGPT is blowing everyone else away. Alright. Reason number 2, OpenAI still might win the LLM race. Only they are the only front end model with a reasoning model, projects, the Internet access, code rendering, and tools. Alright? Google Gemini is catching up. Their front end was essentially, you you know, the the red headed stepchild, of AI until December of 2024. No offense against redheads or if you are a stepchild or if you are a redheaded stepchild.
Jordan Wilson [00:34:46]:
I'm just, you know, using analogies here. Sorry. But they were lar like the the front end of Gemini, gemini.google.com was largely ignored until December. Google tucked away all of its best technology inside developer platforms, inside of Google's AI studio, inside of Vertex, and people don't know that. I I did a whole, ranty episode on this a couple of weeks ago, so go listen to that if you want to, but Google, I think, ended up losing 1,000,000,000,000 of dollars in market value because they didn't understand it is nontechnical people making decisions for Fortune 500 companies. And what they're doing, what everyone's doing to test out AI, right, quote, unquote, to test out large language models, before implementing it in their organization. Right? I've literally talked to dozens of Fortune 500 companies that do it this way. Nothing wrong with it.
Jordan Wilson [00:35:41]:
Right? Usually, an individual or a group of individuals or teams will start using a large language model on the front end, usually before their company has an official AI policy. Then they'll go to leadership and show them something. They'll log on to ChatGPT.com or gemini.com or claw.aiorcopilot.microsoft.com. Right? And be like, oh, wow. Look at this. Right? What I'm saying is very I won't say very rarely, but it's not commonplace that you have your technical people, your CTO, your CSOs, your CMOs doing these things on the back end. Front end is where decisions are made, and ChatGPT has a stranglehold on front end features. It's not close.
Jordan Wilson [00:36:25]:
Google Gemini, catching up finally, but until 4 weeks ago, Google Gemini, sorry, was trash on the front end. They didn't put their most recent models. 5 months ago, it had a problem using Google. Right? Yeah. Claude, great I mean, Claude's great at some things. It's not connected to the Internet. They don't have a reasoning model yet. So OpenAI is the only model that has everything.
Jordan Wilson [00:36:55]:
They have everything you need on the front end. Are there improvements to be made? Absolutely. Do other, models excel in other areas where OpenAI doesn't? Yes. Right? Google Gemini, is is technically has the better model, right, right now. By a thin margin, but they have a better model. Claude, their in so their artifacts feature that you can render code way better than OpenAI's canvas, even though they're kind of 2 different things. So, yes, these front ends for Google and Claude have advantages, but OpenAI has it all. Alright.
Jordan Wilson [00:37:33]:
And just like we saw, OpenAI came out with projects. Right? Which tells you, yeah, anything good that a competitor has on their front end, OpenAI is going to implement it or it's probably already, been in the works. Alright. And, I mean, we haven't even talked about what else might come to the front end of OpenAI. Right. Hopefully, we'll see an an updated DALL E or maybe it'll just be Soarra photo. Right now, it's a different, front end. Maybe we'll see Soarra inside the ChatGPT interface.
Jordan Wilson [00:38:03]:
You know, maybe we'll see the new operator, which is the agentic system, inside the ChatGPT interface. There's something that's been rumored, called tasks where you can schedule essentially prompts to run. Right? So the front end interface is only improving, and I think for whatever reason, their 2 biggest competitors have been too slow, too stagnant, in bringing features consumers want to the front end. Alright? Business leaders are not making, at least across the board, they're not making decisions based on API. Even though that's where they may ultimately be using the large language models, where they're testing them out, where they're making their decisions is on the front end. ChatGPT.com, gemini.google.com, claw.ai, and OpenAI is running away with it. Alright. Reason number 3, I saved the best for last, y'all.
Jordan Wilson [00:39:05]:
OpenAI is actually crushing one of the most important games that I don't think anyone's paying attention to, The small language model game. Alright. Let me share. And I'm on record saying this back in 2023. I've said the future of large language models is small language models. As hardware becomes more powerful. K? The AI chips are getting better. Right? Your your GPUs, your NPUs.
Jordan Wilson [00:39:40]:
Right? Edge AI. Using a large language model on your device, on your phone, or your on your computer is going to become more and more commonplace in 2025. Why, you might ask? Well, it's faster, number 1. It's more secure. But right now, when you use all these models on the front end, right, you are sending all this information to the cloud. It makes it more expensive. It's worse for the environment, and there's less safety. Are we going to be able to use, you know, OpenAI models or Google? Well, Google already has some, or Claude models locally.
Jordan Wilson [00:40:15]:
I don't know. But OpenAI is winning the game of smaller models that are more powerful. No one's paying attention to that, And that is, I think, one of their biggest wins they have going for them right now. Let me quickly explain here. Alright. There was a Microsoft research paper, we covered this yesterday in our AI news that matters. That's our weekly Monday wrap up. Livestream audience, do you guys catch it, or is is it boring to you guys? Let me know.
Jordan Wilson [00:40:50]:
But we talked about this yesterday, a Microsoft research paper that essentially somehow uncovered model sizes for some of the most popular proprietary models. Alright? So these proprietary models, for the most part, they're secret. Right? No one really knows how big they are, how many parameters they are. Think of parameters as a model size. So your open models, right, they they they say it. Right? Because you can download them. You can fork them. You can build off of them, etcetera.
Jordan Wilson [00:41:19]:
Right? So with meta. Right? Meta, you have your meta, what is it? 3.27b, 7,000,000,000 parameters, 11b, 11,000,000,000 parameters. Their 3.1 has a 405 b, 405,000,000 parameters. That's the size, how big the models are. Right? The the the weights, the training, everything that makes that model special. For the most part, we don't really know. All we've really known is the GPT 4 model was 1.7 or 1.8 trillion parameters. Giant.
Jordan Wilson [00:41:51]:
Right? So this new Microsoft research paper shed some light. So like I said, GPT 4 had 1.7 trillion parameters. And if we talk about its benchmarks, right, sorry, non dorks. Stick with me here for a second. 86.4 on the MMLU. GPT 4 o. Right? So the successor or the updated version of GPT 4, GPT 4, so the omni model, 200,000,000,000 parameters. What does that mean? One tenth the size, performance went up.
Jordan Wilson [00:42:29]:
Alright? Yeah. But you're still like, alright, Jordan. Well, you know, a 200,000,000,000 parameter model, you can't really run that locally. Well, yes, you can. Right? Not GPT 4 o because you can't download it. But you you might be saying, oh, that's a huge model. You can't run that locally. Well, look at what NVIDIA just literally announced.
Jordan Wilson [00:42:49]:
Right? You could run a 405,000,000,000 parameter. You can literally chain 2 of these, these new digits, project digits, chain 2 of them together, and you can run a 405,000,000,000 parameter model. Meadows 3.1, 405 b, you can run that locally, which is mind blowing. Right? If you don't follow this stuff, it's it's, it's I can't even explain it. Right? But the fact that you can run a model that big locally, huge. So GPT 4 o, a tenth of the size more powerful. Why does that matter? Well, look at their, quote, unquote, small model. Their small language model, GPT 4 o Mini, 8,000,000,000 parameters.
Jordan Wilson [00:43:40]:
That is tiny. Alright. The next iteration of smartphones in 1 year, smartphones would be able to hold an 8,000,000,000 parameter large language model. Right? Edge AI. Right now, usually, most Edge AI smartphone, kind of models are between 1,000,000,003,000,000 parameters. No one's doing this math since this study came out. Like, that's the first thing I saw. Maybe it's because I'm a dork, but I'm like, wait.
Jordan Wilson [00:44:09]:
GPT 4 o is only 8,000,000,000 parameters? It is still highly capable with an 82 on the MMLU. Right? Think of an MMLU as, you know, I know more people are looking at MMLU pro or other, benchmarks. I like MMLU. It's a nice standard that's been around for a long time. And you might think of it, like, okay, that's a big drop off. Right? To go from, you know, an 88.7 in GPT 4 o to an 82 with GPT 4 o. That is an 8,000,000,000 parameter model. That is tiny.
Jordan Wilson [00:44:42]:
Let's look at some of the other models that are in that same size, at least that we know the parameters and we have an MMLU score for. Llama, the, 3.211 b. So a bigger model, technically, 73 MMLU. Alright. Microsoft, 5 3. It's a 7,000,000,000 perimeter model. 65 MMLU. Alright.
Jordan Wilson [00:45:09]:
If you don't know anything about MMLU scores, right, they fight for a point one percentage. Right? Like, when you're getting into the 80 hs, the 80 nines, like, a point 1, point 2, point 3 improvement is is huge. OpenAI is silently crushing the small language model game. Why does that matter? 1, I told you, Edge AI, right, in theory, you would be able to run something like that locally. Who knows? Maybe OpenAI will allow that one day. Maybe that will lead to us actually having a state of the art model on our devices. Right? Who knows? Maybe, the iPhone 18 might have GPT 5 Mini on it running locally, which in terms of what that means for humans, what that means for society, what that means for work, is is crazy because then there's really zero reason, right, for anyone in the world to be like, nah. Our organization's not gonna do this AI thing.
Jordan Wilson [00:46:15]:
They're silently crushing the small language model game. No one is paying attention. Why else does that matter aside from Edge AI? Well, I believe in the future, we're going to be using thousands of small language models. I think your o ones, your o threes, these reasoning models, they're gonna take, let's just say, a GPT 5 o Mini. Let's just say let's just say there's a GPT 5, 5 o Mini. And let's say we have an o three. I believe the o three is going to start taking the place of that reinforcement learning with human feedback is gonna become reinforcement learning with reasoning feedback. You are gonna have these reasoning models fine tuning.
Jordan Wilson [00:46:57]:
Right? And this is when we step into that line between AGI and ASI. Right? But AI is gonna be creating thousands of versions of these smaller models. I think we're gonna have what's called a mixture of models. Make sure you tune in to our 2025 prediction show. In 2 weeks, I'm gonna be talking about that. Right? We we have this thing called mixture of experts, and we have for a couple of years. I I think we're gonna have something called mixture of models. I think we're actually gonna be using thousands of small language models.
Jordan Wilson [00:47:27]:
In all the large language model, the front model is gonna do is, congregate information and orchestrate the large language model to go out and do things. Alright. I got a little, I got a little dorky there at the end y'all, but, let me go ahead and end this this way. Alright? Because this was this was a lot long episode. Sorry. Sorry if you're still on the treadmill. I gave you three reasons why OpenAI might not win the small language model race. I gave you three reasons they might.
Jordan Wilson [00:47:58]:
I asked the audience, who do you think is gonna win? So So let me wrap it up by saying this. Yes. OpenAI is gonna win the large language model race in 2025. However, they actually have competition. Because if you look at the 24 months from November 2022, when Chatt GPT was released, until November 2024. Right? 24, 25 months. It was a one person race. It wasn't even close.
Jordan Wilson [00:48:33]:
Google, I think, had the best month in AI ever in December 2024. Not just from a large language model perspective, but generative AI, tons of features, that I think are gonna be useful and actually use. For the 1st 2 years, OpenAI was running by itself, yet they still innovated and they still, I'd say, dominated. Right? There's a reason Microsoft, number 1. Number 2, Apple. There's a reason they chose OpenAI to power the future of their devices, of their technology, of their software. Right? Apple and Microsoft are smart. They build their own models, yet they said, ah, we're gonna use OpenAI for, a big part of our future.
Jordan Wilson [00:49:28]:
OpenAI did that with they knew. If I'm Sam Altman, if I'm, in leadership at OpenAI, I knew it was a one pony race for 2 years. It's not anymore. So, yes, we're gonna see OpenAI go in different directions. Yes. They may get sidetracked going after AGI, ASI, their operator agents, all these other things, but they know now. Google is on their toes. Poor Claude.
Jordan Wilson [00:49:54]:
Poor Claude. I think Claude could be one of those sad stories in 10 years where everyone's like, oh, remember Claude? And I don't know. Maybe they get acquired by Amazon or aqua hired by Amazon, or maybe they just fade into oblivion. I think, you know, at least going back to our original three, I don't think Claude is in the race. I don't think they are. But I think OpenAI is going to win the race, but it's gonna be a lot closer than it was for the 1st 2 years. I hope this was helpful y'all. If so, please go to your everydayai.com.
Jordan Wilson [00:50:29]:
Sign up for our free daily newsletter. Also, on our website, there's a ton of information. Like I said, hundreds of episodes No matter what you care about. Do you care about HR? We have a category for that. Go learn from HR leaders. Do you care about marketing? We have a category for that. Do you care about enterprise technology? We've talked to the experts. Literally, our website, your everydayai.com, is your new best friend.
Jordan Wilson [00:50:53]:
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Jordan Wilson [00:51:14]:
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