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Artificial Intelligence Predictions for 2025: An Examination of Market Forces and Global Developments
Artificial intelligence (AI) continues to evolve at an increasingly rapid pace, unveiling new potentialities for businesses and consumers globally. 2025 looks poised to be a pivotal year for AI, with several significant trends and predictions already underway.
Surge in Open-Source Models
As AI understanding deepens, there has been a notable shift towards open-source models. These models offer a dynamic platform for innovation, allowing for public collaboration and improving upon existing protocols. Not only are they more secure thanks to on-premise system deployment, but they also offer faster performance and greater environmental sustainability due to lessened reliance on the cloud.
With their rapid growth and the burgeoning interest in collaborative tech development, open-source AI models are predicted to temporarily overtake proprietary models by 2025.
The Rise of Chinese AI: Dominance and Confusion
China’s influence on the global AI stage continues to expand, with expectations of dominating the top rankings across different benchmarks. Chinese companies are spearheading the production of remarkable AI technologies, including leading language models and cutting-edge robotics.
However, a surge in Chinese influence is predicted to cause confusion as well, especially around data privacy. Increased scrutiny over terms of service and privacy policies of Chinese AI entities is expected as their global reach expands.
The Fate of Perplexity: A Pivot or a Squash?
Innovation and progression are primary in the AI industry. When companies lose sight of these principles, survival becomes questionable. Companies that do not improve or expand their core product while venturing into new verticals may risk obsolescence. The focus seems to be shifting from what was once unique and specialized to what feels generic and widely available.
Further, as competition heightens in the AI space, companies that fail to innovate or diversify could risk being acquired, needing to pivot, or getting squashed by competitors.
The Plummeting of AI Prices
AI technology is projected to become more affordable, leading to widespread adoption. Improvements in hardware and an increase in open-source models mean that the cost of AI implementation could drop significantly.
Coupled with the innovations in AI chips enhancing performance while reducing power consumption and other costs, AI prices are predicted to drop dramatically. This will make the technology more accessible, democratising AI for businesses and consumers globally.
The Explosion of Embodied AI
Embodied AI, where AI systems interact with the physical world, such as humanoid robots, autonomous vehicles, drones, wearable AI, and more, is predicted to be an explosively growing sector. The novelty in this sector lies in the integration of large language model technology and advanced vision systems, transforming how AI interacts with our world.
With large-scale funding already being dedicated to robotics and drones, the uptake in embodied AI is predicted to accelerate rapidly, changing the face of daily commuting, manufacturing, and delivery systems.
In summary, 2025 will bear witness to significant growth and dynamic changes in AI, influencing individual lives and businesses globally. Those invested in AI must prepare for a year of rapid evolution, new opportunities, and revolutionary developments. As AI continues to adapt and evolve, one cannot underestimate its transformative potential and the power it holds to reshape industries, economies, and societies.
Topics Covered in This Episode
1. Prediction of Open Source Models
2. Chinese AI Influence
3. Future of Perplexity
4. Drop in API prices
5. Rise of Embodied AI
Podcast Transcript
Jordan Wilson [00:00:17]:
Thousands of hours of studying AI, hundreds of conversations for a couple dozen AI predictions for you. I get it. You don't have 3, 4, 10 hours a day to keep up with what's going in AI. There's probably a lot of uneasy feelings and saying like, hey. This is going way too fast. If only I had something to help me keep up and, to cut through the nonsense. Well, that's what you have in everyday AI. And today, we are bringing you a special edition, volume 2 of our 25 biggest and boldest AI predictions for 2025.
Jordan Wilson [00:01:09]:
And unlike last year, where I jammed them all into one episode that was entirely too long, this week, we are bringing them to you 5 at a time, 5 days, like I said. Hundreds of conversations that I had about generative AI in 2024. And, you know, going back to literally, I remember in March, when I partnered up with NVIDIA at their GTC conference. I was already writing notes for this very show, for this very series, so you can get ahead and grow your company and grow your career. That sounds like what you're trying to do? This series and this show is for you. Welcome. This is Everyday AI. My name is Jordan Wilson, and this thing's for you.
Jordan Wilson [00:01:54]:
It is a daily livestream podcast, free daily newsletter helping us all learn and leverage generative AI to grow our companies and career. This is unscripted, unedited. I'm just bringing it to you real. Alright. Everyone else is, you know, trying to tell you what you need to hear or what you think you want to hear. I am telling you what you need to hear when it comes to AI. Alright. Something else you need to hear, our website.
Jordan Wilson [00:02:17]:
You gotta go there. It's your everydayai.com. Sign up for the free daily newsletter. If you're looking for the daily news, technically, this one's prerecorded, because it's a lot of work. You know, it's technically like nighttime, but you're probably hearing it in the daytime. But livestream audience, I still wanna hear from you. And let me just answer this. Like, okay, Jordan, why are you doing this? Why are you doing predictions? Number 1.
Jordan Wilson [00:02:39]:
Number 2, why are you drawing it out? Well, couple of reasons. Number 1, why am I doing these predictions? People ask me all the time. Jordan, what's next? Jordan, you talk to, you know, people at Microsoft and IBM and Google and right? I I have great great, relationships and conversations with people. Those you know, I've interviewed hundreds of people in 2024, and I've had hundreds of conversations that you didn't hear. Right? Get things off the record, on the record, NDAs, non disclosures. Right? But now I can finally give it to you all in my predictions. And I did this last year, and I still had people reaching out to me, like, 10 months later being like, how did you know all that? Right? You were correct. I didn't say those things, but you can go listen to the old, 2024, episode out there and let me know for yourself.
Jordan Wilson [00:03:28]:
But without further ado, let's jump back into it. Like I said, this is volume 2 of a 5 volume series. Happy Tuesday if you're listening live. But you can go listen to yesterday's episode and join us in the coming days as we go through volumes 3, 4, and 5. But to quickly set today's stage, today we're gonna be covering a lot of different things. But I'm calling this group of 5 predictions, AI Market Forces Collide, Global Powers Prices and Problems. Yeah. You like that alliteration, don't you? Alright.
Jordan Wilson [00:04:02]:
So let's jump into it. But I'll give you a quick recap of yesterday's 5 predictions. If you wanna know more, go back, read, listen, whatever you wanna do. We recap them in our newsletter yesterday as well. So 25, agent orchestrators will be a growing position. 24, public companies will post job for AI agents. 23, company reasoning data collection. 22, high end professional services will go through a pricing crisis.
Jordan Wilson [00:04:31]:
And 21 UBI will become a household conversation. Alright. So today's volume 2, here's our 5 predictions. We're gonna dive in deep but go pretty quick. I'm challenging myself to do these episodes in 25 minutes. You know, branding, 25, predictions across 5 days, 5 predictions each for a total of 25. Trying to do these in 25 minutes. Alright.
Jordan Wilson [00:04:54]:
Here we go. Here's today's, and we're gonna dive into them. Ready? 20. Open source surges. Open LLMs will temporarily overtake proprietary models. 19, Chinese AI will dominate and cause confusion. 18, perplexity will either pivot, get acquired, or get squashed. Yeah.
Jordan Wilson [00:05:16]:
Hot takes. It's Tuesday, y'all. 17, API, API prices are gonna drop like they're hot. In 16, embodied AI will be an exploding sector. Alright. Livestream audience, like yesterday, I wanna know which one of these are the most likely and which one is the least likely. Right? I'm gonna revisit this in 6 months, but I wanna see. Do you know your stuff? Do you have a crystal ball? Right? Do you know what's going on? Let me know.
Jordan Wilson [00:05:46]:
You can even just put what the number and which one you think is most likely the number, what you think is least likely. Please go ahead and do that right now. I always love hearing from our livestream audience. Alright. Enough of the chitchat. Let's get into it and talk about our first one, open source models. Here's the reality. Open source models haven't been fully tapped into yet.
Jordan Wilson [00:06:15]:
They started to really trend, in the latter part of 2024. Alright. So there are fully open source models. Let me just get this piece out of the way right now. Right? There's fully open source models that you can essentially, there's an open source standard. You can download them. You can fork them. You you know, you can do anything.
Jordan Wilson [00:06:35]:
And then there's also Meta's llama models, which are not technically open source. Meta calls them open source. They aren't open source by the technical open source standard. Although what Meta is trying to do is, they're just trying to, redefine what open source is. But for a lot of intent and purposes, it is an open model, although not truly open source. But Meta has been a huge driver in the movement nonetheless because, y'all, you have big companies like NVIDIA, forking and building off Meta Llamas or or, sorry, Meta llama models. And and they they are topping not topping, but they are in the top, tier of of rankings and of these, charts that we'll be talking about. So why why the heck are open source models going to temporarily overtake proprietary? So I kinda told you what open source models are.
Jordan Wilson [00:07:32]:
You can, for the most part, download them if you have a powerful computer. You know, there's smaller, you know, small language models that you can download. There's a lot of reasons why they're becoming very popular. Well, one is they're, more secure. Right? You don't have to send any of your information. You don't have to send any of your data to the cloud. If you're working with a smaller, smaller model, right, maybe something that's only a 1,000,000,000 or 2 parameters, it's very fast. Right? Because you don't have that kind of, extra inference time that you're waiting on a cloud provider to, you know, go and crunch your prompt.
Jordan Wilson [00:08:11]:
So security, it's fast. It's better for the environment too. Right? So there's there's a lot of, you know, good, I I guess, kind of under the radar reasons that I think is good to root for open source models. Right? Proprietary models like OpenAI's GPT, Claude Anthropic. You know, there's, plenty of others. Right? Google Gemini, they're they're big models. Right? These big companies, they're trying to, obviously, right, they want to profit off their models. Everyone does.
Jordan Wilson [00:08:42]:
Right? So you can't download them and fork them and build off them and distill other models with them. You can't. You have to log on to their website or use their API on the back end and pay for it. Right? So not everything is open source, but I think open source in 2025. This is the year. I don't think an open source model is going to top the LM arena or the chatbot arena like we say. I don't think necessarily, that we are going to see an open source model with the highest, as an example, MMLU benchmark. So, you know, I like to say the and a lot of people say, but the the the MMLU is a benchmark.
Jordan Wilson [00:09:25]:
It's like the ACT or the SAT for large language models. So I don't think that it's, but, like, when I say it's going to temporarily overtake, I'm not saying it's going to be the number one model, for a certain benchmark or for Elo scores on the, chatbot arena. What I will say what I will say, right, I'm just gonna go ahead and put put these out put these out there. Right? I do think that more than half of the top 20 models, on the, chatbot arena leaderboard at some point in 2025, I'm gonna say more than half of them are gonna be open source. You might be saying, okay. Well, it sounds like there's only yeah. There's more than a 1000000, different open source models because people can download them, especially smaller ones. It's not terribly time consuming, right, to download one of these, fork them, do some fine tuning, you know, kinda make make a smaller model of your own, and that's what a lot of people do.
Jordan Wilson [00:10:29]:
And then they put it out there for everyone else to use. Proprietary models, not so much, but there are, like, I don't know, like, 10 different versions of Google Gemini. Right? There's there's, you know, o one preview, o one mini, o one full, o one pro. So there are dozens of very strong, very powerful proprietary models. So it's not crazy to think that, open source could take half of those. Also, recent study said 41% of enterprise companies plan to increase open source model usage. Companies know that there are huge benefits. I don't think that they were really paying attention in 2023 or the first part of 2024 until I do think Meta made that first big open splash and said, yo, look at us, Because their models at the time, 3.13.2, I mean, these were top 3 top 5 models.
Jordan Wilson [00:11:23]:
They were competing with proprietary models. So, that is something I think when you crowdsource these fixes. Right? Because if you put your model out there for everyone to to look at, for everyone to download, for everyone to improve upon, they're gonna find ways to optimize the models to make them better, right, to improve the output. So it's essentially when when you put your work out there and crowdsource people to to build it, to pick it apart, to tear it apart, it's gonna get better. And that compounding, kind of crowdsourcing of of compute. Right? We'll say that. Triple c. Right? The compounding crowdsourcing of compute.
Jordan Wilson [00:12:04]:
It's, the the rising sea lift all lifts all ships or whatever the saying is. Right? Alright. Number 19. Chinese AI will dominate and cause confusion. So speaking of, you you know, models on the leaderboard, let's look at the top ten. I do think at some point in 2025, 5 of those top ten models are going to be from China. Alright. So reportedly, Alibaba's Quen models have already been deployed by 90,000 enterprise customers.
Jordan Wilson [00:12:39]:
Alright. Also, something that, really started to cause a scene at the end of 2024, DeepSeqs V3 model. Alright. So so so so cheap. And here's the thing. I don't think it's just large language models when it comes to, you know, Chinese AI will dominate and cause confusion more on that part here in a second. But I think robotics, China is, their their, their humanoid and their robotic production. It's scary.
Jordan Wilson [00:13:13]:
We've shared some of the videos not like, oh, this is so cool. Look at this. It's nuttier than a squirrel on keto. No. It's scary. Right? It's it's warehouses of what looks like thousands of humanoid robots, that are embodied AI. Right? Yeah. It's, kind of scary.
Jordan Wilson [00:13:34]:
So I think it's not just large language models. It's not just prices. It's not just benchmarks. It's robotics. I think, we're gonna see other things. I do think, China has competed very well in the AI video, sector with with Cling and some others. But I also think that we're gonna see an AI audio competitor as well. Right? So China kind of silently.
Jordan Wilson [00:14:01]:
Right? So DeepSeq v 3, one of the cheapest models to use via the API. Cling, the AI video models, one of the best out there. I would say definitely top 3. You know, the Quinn models, and and, you know, Quinn has a reasoner model. They're great. They're competing all across the board. Also, here's why it might cause some confusion. There's some people rumbling about this on the Internet, and I'm not a conspiracy theorist.
Jordan Wilson [00:14:32]:
Don't think that about me, but I do think that there is an element of a kind of Trojan horse here. Right? So even with, you know, some of these models that are dirt cheap, you know, companies and and individuals, they just kinda close their eyes. Right? And they just assume like, oh, okay. It's like using Google. It's like using, you know, it's like using OpenAI. You're anthropic. It's not. You should probably start reading.
Jordan Wilson [00:14:58]:
Everyone out there, business owners, if you're a decision maker making, making a big choice on what, AI system to use. I'm not gonna name names. Read the terms of services. Read the privacy policies. Understand what happens with your data if you're uploading it to these companies. I'll tell you this. I've read them all. Yeah.
Jordan Wilson [00:15:19]:
I'm a dork. I actually read them. I read them, and I also have different AI systems help me read these terms and services. You don't wanna know. It's it's a Trojan horse. That's what it is. Right? It's everything's free. Everything's cheap.
Jordan Wilson [00:15:32]:
Everything's fast. Everything's great. And it's like, at what cost? Well, we might find out. And I do think that there's going to be I won't say an event, but I think there is going to be some mainstream media attention to this very fact, as, AI, I think, is also going to get very political, in 2025. And this is one of those things when we talk about geopolitical tensions, yeah, AI is gonna be a big part of that. Right? A lot of, restrictions on, you know, exporting, bans on exporting GPU chips to certain countries, you know, potential tariffs, all of these things. The AI scene is going to get very political, and keep an eye out, for stories. I would say probably midway through the year once the rest of the world kind of looks and understands what's going on.
Jordan Wilson [00:16:22]:
Because I think these models, they're very capable. They're very popular. They're very cheap. They're very fast. People are gonna use them. Businesses are gonna use them. And eventually, someone's gonna be like, wait. Should we have looked at this a little more closely? Alright.
Jordan Wilson [00:16:36]:
Number 18. Here's a spicy hot take for hot take Tuesday, volume 2 of our 2025 AI predictions. Per Perplexity, everyone's favorite answer engine, will either pivot, get acquired, or get squashed. Here's why. I think perplexity has lost its focus as a company. Right? They're going in so many different directions. They they they started making a daily podcast, and then, the CEO started talking about making hardware. Right? It started going in a lot of directions, but that's fine because all other companies are exploring other verticals.
Jordan Wilson [00:17:23]:
Yes. Perplexity is a little smaller than, you know, OpenAI, much smaller than obviously, you know, Google. Right? But here's the issue. When companies like OpenAI, they start competing in different spaces. Google, Claude, you know, Anthropic Claude. Their core product improves first. Right? That's one thing, especially the the the 2 startups, you know, that are building these models, Anthropic and OpenAI. Right? If if they start going in another direction, that means their core product, their core USP has improved.
Jordan Wilson [00:17:59]:
I'm not seeing that with perplexity. Sorry. Perplexity at its core, it's not a large language model. Right? You choose your model, although they have their sonar model. I don't really know anyone that uses that. You know, most people will, use, you know, GPT 4 o, Cloud Sonic 35 new or 351, whatever you wanna call it, 36. You know, that's not perplexity is not a large language model. It is an answers engine.
Jordan Wilson [00:18:26]:
It is a great product. However, the core functionality, I need to say this, it's actually gotten worse. It's gotten worse. I've showed it on the show before. What it's supposed to do is it's supposed to crawl out there, look at 10 to 20 different websites, and give you answers. It's not getting better at that. In my experience, it's actually gotten a little worse. And the answers engine space has very recently got very crowded.
Jordan Wilson [00:18:56]:
Alright. Very crowded. So, ChatGPTsearch, which has its flaws too. Right? I personally liked browse with Bing Better. ChatGPTsearch has some problems. I've talked about that on the show many times. But then you also have, these large language models are just getting better Internet connectivity. You also have Google deep research.
Jordan Wilson [00:19:17]:
Google is getting an AI mode. I mean, speaking of deep research, it's one of the most impressive AI tools I've ever used. Right? So ChatGPTsearch might look at, you know, 8 to 10 websites in a single prompt. Perplexity usually does more, maybe 12 to 20. Y'all Google deep research, it takes a little while. Right? Perplexity, you know, you you might ask it something. It might take, you know, 5 to 15, 20 seconds. Same thing with ChatGPT, maybe a little faster, because it doesn't go to to as many sources.
Jordan Wilson [00:19:48]:
Deep research, yeah, it might take 1 to 3 minutes, but I've had certain, deep researches that it looks at 1300 websites. But I routinely get it to look at usually 60 to 200 websites. That is an agentic researcher that works for you. Okay? So perplexity's gotta pivot. Because what they were doing, they didn't get better, and it's too crowded. They're not that special anymore. Right? 18 months ago, a year ago, they were still special. Not special anymore.
Jordan Wilson [00:20:23]:
Their core product is not getting better. The space is getting more crowded, and the interest, I don't think, is there. As an example, y'all know I always bring receipts. Search volume. Right? That talks about demand. Right now, there's, you might think I think we live in an AI bubble. So many of us out there, we might think, oh, you know, sure, ChatGPT is maybe a little bit more popular than perplexity. Maybe twice as popular 3 times.
Jordan Wilson [00:20:46]:
No. 66 times as popular, at least when we talk about search demand. Right? There's about 450,000 people a month searching for, perplexity and 30,000,000 people searching for ChatGPT. So perplexity, I think, has kind of lost its way. I don't use it as much as I have. I still subscribe to it. I I paid the, you know, the paid plan for every single model out there because I'm pushing them every single day. So I can tell you what's worth your time to grow your company and your career.
Jordan Wilson [00:21:15]:
Flexity might not be worth it very much anymore. Right? I have paid Google Gemini, so I get deep research. ChatGPT search for very certain things is very good. Perplexities doesn't have anymore. They could get acquired. I don't know. You you know, you might see something like an Amazon. I don't know.
Jordan Wilson [00:21:34]:
They might get aqua hired. They might pivot or they might fade into oblivion. Alright. 17. I gotta go fast now. I'm trying to keep these under 25 minutes. So large language model API prices are gonna drop like they're hot. This is not a surprise to anyone, but when I say drop, I'm saying they are going to drop.
Jordan Wilson [00:21:53]:
And one of the reasons why well, a couple of reasons why. Number 1 is open source. Right? If there's free alternatives, the paid alternatives, if they want to stay relevant and make 1,000,000,000 of dollars, they have to keep their prices low. Obviously, the hardware, the GPUs, the NPUs, the TPUs, Right? All these AI and data center chips are are are getting more powerful, more plentiful. I think more and more things are going to go edge AI, which takes a little, you you know, of that, some of those resources off of the cloud. But I think hardware is getting better. The AI chips are getting better. The open competitive the the open models are getting better.
Jordan Wilson [00:22:33]:
All those things drive costs down. Right? Inference time goes down. All these things. But I do see and it's crazy to think about. When GPT 4, was first released in the API so I'm talking about back end. These are for developers, not, you know, if you're paying $20 a month to use a product on the front end, that's all you're paying. Right? Or $200 a month if you're, you know, on, like, ChatGPT pro. But otherwise, you're paying an API price.
Jordan Wilson [00:22:58]:
Right? You're paying, you you know, a price per token. So when gbt 4, was first made available in the in the API, so for developer, for, I'm sure there's 100 of 1,000, if not millions, I don't know, maybe millions of businesses these companies don't say. But it was $60 per 1,000,000 tokens for output. Alright. So you get ChatGPT to spit out 60,000,000 tokens, or sorry, a a 1,000,000 tokens, $60. Now with GPT 4 o, a wildly more capable model, $2.50 went from $60 to $2.50 in about 19 months. Alright? I see in 2025 leading Frontier models going even cheaper. I think, you you know, for easy comparison, I think we're gonna break that 50¢ mark, less than 50¢ per 1000000 tokens for a leading state of the art model.
Jordan Wilson [00:23:59]:
Alright. 2 more here. Number 16, embodied AI is going to be an exploding sector. Alright. So what is embodied AI? Well, it's artificial intelligence systems that interact with the physical world, whether that's, you you know, robots, autonomous vehicles, drones, wearable AI, robo taxis. Right? It is, you know, we've we've had these things for a long time. Right? Those things I just mentioned, none of those are quote, unquote new. You know, humanoid robotics, autonomous vehicles, drones, wearable AI, etcetera.
Jordan Wilson [00:24:40]:
None of that's new. What's new is having generative AI in large language models on board. That changes everything. That's how now you have startups as an example, like Figure, that can go from obscurity and in 2 years turn into a multiple $1,000,000,000 company in, like, 2 years. You couldn't do that pre generative AI, because you had to build all that artificial intelligence. Now you can just use these companies' API, use the technology that's already there, and essentially start stuffing it in humanoid robots, in robo taxis, in drones, in wearables, and it changes how we interact with the world. I think I'm gonna blame Apple. Right? Apple came out with the, the Apple Vision Pro, and everyone's like, oh, this is gonna change the world.
Jordan Wilson [00:25:32]:
Literally before it came out, I'm like, this thing's gonna suck. No one wants it. Right? But I think some of these early, examples of embodied AI, especially wearable tech, they they were terrible. And just so you guys know, go back and listen. I was never bullish on any of these early wearables. I'm like, nope. Nope. Nope.
Jordan Wilson [00:25:52]:
That'll flop. No one wants it. I'm very bullish in 2025 on embodied AI. We're gonna see AI out and about just about everywhere. Right? It's it's it's gonna start in some of those, some of those areas that I just talked about. So even an example, in 2024, VC funding in robotics and drones soared by more than 40%. Another additional kind of hot take on top of this prediction. I do think in some major cities where the law allows it, I think probably more than 10 to 15% of ride share rides will happen with autonomous vehicles.
Jordan Wilson [00:26:35]:
Right? I don't think we're gonna get the the the Tesla, you know, whatever they're calling it, the robo taxi AIs. You know, they're always, you know, they're like, oh, this is coming out, you know, in 3 months, and it's gonna be $30,000. Then it comes out 8 years later for a $100,000 like, Cybertruck. So I I I don't expect Tesla to have anything in 2025, but I do think other companies, with this embodied AI bringing, essentially large language model technology, vision technology, I think it's gonna be fairly common. I do think in big cities, you know, 1 in every 10 rides potentially by the end of the year, we'll be in these type of vehicles. So embodied AI, is going to be huge. Alright. I made it.
Jordan Wilson [00:27:24]:
I made it. I didn't accidentally talk, for a couple of hours. So quick recap of the 5 bold AI predictions in this volume of our series. So open source searches, I think open source models will temporarily overtake proprietary models. I think Chinese AI will dominate and cause some confusion. I think perplexity will either pivot, get maybe acquired or aqua hired, or just get squashed. I think API prices are going to get ridiculously cheap. I think we're gonna see, like, less than 50¢ per million token for big models like through OpenAI and, Google Gemini.
Jordan Wilson [00:28:09]:
And then I think embodied AI is going to be in exploding sector. Alright. I hope that was helpful. Volume 2 in the books. If this is helpful for you, let me know. But probably you should go listen to yesterday's volume 1. It's gonna be in your show notes. Make sure to check it out.
Jordan Wilson [00:28:27]:
We talked about a lot of different things, but a lot of things on agents, and kind of the next steps in the workplace. So make sure you join us tomorrow for volume 3. We're gonna be talking a lot about the kind of, contents AI revolution, videos, streams, and stars. Hope to see you back tomorrow and everyday for more everyday AI. Thanks y'all.