Hello, everyone. My name is Diego Rodriguez. I am co-founder and CTO at CREA. We're building an AI creative suite. I'm going to tell you three stories and then I'll try to hire you. So a friend once told me, if you think about it, cars are easy to predict, right?

It's like you get the horse, you have the wheels, you swap the horse, and you put an engine, which was known at the time, and that's a car. But you know what's really hard to predict? Traffic. So it's my job to ask, what are the traffic that we're missing, especially with AI?

You know, YAML, JSON, MCP, whatever it is, like, okay, okay, but like, what happens when you generate a million images per day, like we do for one studio? Where do you find that? Another story, Tower of Babel, we wanted to reach heaven. God was like, no, created a bunch of languages and basically misunderstanding was like, nope, we are not going to go there.

And it reminds me of stand-up meetings where people are like, no, it should be React. No, no, no, but like, it should be like JavaScript. I was like, dude, I'm not going to go there. We're not going to go there. And so this is only like people trying to convey ideas, and that's what we're trying to tell, just trying to tell stories.

The final story is, I was talking with someone from Netflix, and she was like, what happens when we are making so much content personalized to each town in India? How do I even find that? Like, right? And then a few days ago, I just realized that Korea was already being used for broadcasting an ad with Fox to millions of people.

And then I look and they literally signed up two days ago. So we went from sign up to conversion to payment to broadcast in two days. And then this was the CTO telling me that. I was like, whoa. I basically, I'm about to run out of time. So the mandatory slide, a bunch of users, 25 million, raised a bunch of money.

We did this with eight people. Some of the people who are using us, an email that I created for today that is going to prioritize applications. Thank you. - All right. Open home. Okay, everybody. The smartphone was the number one best selling consumer product last year. And the laptop was the second.

Pop quiz for all you hear. What was the third? Apple watch. Wasn't Apple watch. Wasn't the air pod. No, I think I heard it. It was a smart speaker. 500 million smart speakers were sold last year. But why do they still suck? You can barely talk to them. There's no customization.

There's no community. There's nothing. That's why we built Open Home. The very first AI driven smart speaker. And we're letting you guys build smart speakers too. And we believe here that the future is talking with AI. You should be able to talk seamlessly, intuitively. In fact, you shouldn't have to use this really awkward command based language.

You should be able to just chat naturally. So that's what we're building. And we're letting people here today build their own smart speakers and build them in whatever form that they want. And the key here is developer ecosystems. And, well, we know developer ecosystems. I started my career as the chief of staff for the founder of Splunk, a $30 billion big data company.

Then I was on the founding team of MakerDAO, a $5 billion developer ecosystem. My co-founder and I raised $50 million for our last business, a big data privacy tool. And we sold that business. But it all came down to developers and really building what people actually wanted. And, well, now with Open Home, we have over 10,000 developers building on Open Home.

They're building all kinds of interesting things, all types of different custom smart speakers, building interesting voice AI applications. Sky's really the limit. And, well, what do developers really want? They want open source, they want LLM driven, and they want fully jailbroken. They want Open Home, the AI smart speaker.

And now what's really exciting is with voice AI, you can put it on any type of hardware. We have developers building talking toys, AI robots, AI appliances. You should be able to talk to the world around you in a much more natural way. And you can do that now with Open Home in AI smart speaker.

Here's our dashboard. We have many, many applications, hundreds of applications that have been built, games, personalities. We have an editor that you guys can go in and build, and all kinds of interesting things, home automation tools. And what's really exciting is our last dev kit got booked up within minutes.

And today we have a special announcement for you guys here today. We're releasing the next batch of 500 dev kits for free for everybody here. If you guys want it, we will ship you a dev kit. It's very cool. You can build on it. You can talk with AI.

You can build your own smart speaker here. And we're doing it today. Thank you so much. How's it going, y'all? I'm Josh. I'm the founder of a company called CoFrame. The last company that I started, we scaled to over $2 billion in the course of a couple of years.

But when I started to tinker on using AI to generate code and created one of the actual top autonomous coding agents on GitHub, was number one on GitHub for a week, I realized it was time to build something bigger. The internet is dead. It's not adaptive. It's not personal.

It's not truly living in a sense. Websites are all one size fits all. And we're bringing that concept to life. We are giving websites a life of their own, giving every single customer experience its own AI growth team. But this isn't just a pipe dream. We made $20 million for Europe's largest travel company in just a few weeks.

We increased click-through rate for India's largest company, a $400 billion enterprise, also in a few weeks. And how are we doing it? We're working with the best and we have the best. We're the only marketing tech company that's partnered directly with OpenAI to date. And they actually called our team Cracked, which is cool.

So if you're interested in learning more about this, reach out. Thank you. Hi. I'm Eugene. I'm sorry. My team is obsoleting all the AI models you see today. Because you see, my team built CoreKey 72B, the world's largest model without the transformer attention with only eight GPUs. And this allows us to have a thousand x lower inference on our new architecture without performing the same.

Surprisingly, the technology that we build can also be applied to existing transformer models through speculative decoding. Nothing too big, nothing too important. But here's my hot take. Scale is dead. And I'm not saying this just from my own opinion. Like, we are burning billions into making AI models bigger.

But at the same time, the deep mind founder and CEO is saying compound AI agent errors will take more than 10 years to fix. Yan Leku is even saying that we need a new AI architecture to push the paradigm forward. And in production, we see over 90% of AI projects fail.

The reason behind this is not something that scale can fix. The problem is reliability. The thing is, like, would you order and use an app that only succeeds 45% of the time? Would you order DoorDash that way? Of course not. If your order goes missing or you end up having 100 pizza, you're going to start with customer support screaming down there.

It's a frustrating experience. But that's what AI agents do. When they work, they're awesome. When they don't work, we are stuck cleaning up the mess. And that's even with frontier models. And here's the thing. What companies want is not a smarter model that can do PhD-level math. The models are really smart enough.

But what we actually really want is the models reliable enough to book airline tickets, sort out emails, or file our taxes and invoices. That's what we actually want. And that is what we are building at Federalist AI. AGI that's made reliable for each one of you. And most recently, we are in our research, that we actually shown that we build an action R1 agent that beats cloud force on it and Gemini and open AI.

This model is not going to do PhD-level math. But it's going to fill up the form with absolute reliability better than the frontier. And that's the thing. Like, are we going to burn billions more to make a smarter model that is just a few percentage points higher IQ? Or are we going to make something that's 99.9% reliable for the boring things in life?

Because this is where the money is for all of you. Because think of it, as AI engineers, reliability is revenue. For every use case you unlock and find, you're going to do a billion-dollar app in e-commerce or in B2B sales. And that is something that all of you can build on, not rocket science.

And that's what we are building. And if you're excited about it, feel free to reach out to us. I'm Eugene at Federalist.com. My name is Jonas. I'm an engineer. And I like working with data. I love working with data. Actually, I love it so much. I dropped out of high school when I was 15.

I got on a plane. I moved across the country to California. And I joined a startup called Branch. You might have heard of it. Anytime you were clicking one of those links on your phone for an app, that was probably us. I also led a team there that built a search engine that over 100 million people used every day.

And then last year, I left along with one of the founders of Branch to tackle an even bigger challenge. This is probably what you think your sales and marketing teams are doing with their budgets. And you wouldn't be entirely wrong. So that's why I co-founded Upside. We do forensic revenue attribution and intelligence.

But what does that actually mean? Well, how many of you have an email from a salesperson like this sitting in your inbox right now? Uh-huh. And how many of you are actually going to reply to it? Yeah, I didn't think so. These teams are shouting into the void, hoping something will work, because they don't actually know what works.

Because their data is a mess. I mean, don't get me wrong. They're data hoarders. They store everything. They stuff it in Salesforce. They treat it, you know, it's basically a SQL database in a trench coat. But they're not data practitioners. They don't know what to do with it once they have it.

But now we have things like LLMs. They can help with this. They can take that poor, mishandled, abused email record, and they can pull the most important details out of it into a structured form. And so just as search engines and web crawlers learn how to make sense of the unstructured web, Upside is turning raw enterprise data into a highly structured map of the world and all the interactions that people do in it.

So there's hope. We can untangle this mess and we can create a data command center that these teams can actually use to reach their customers more effectively. We only just started talking about this publicly a couple weeks ago. We've been quietly building in the background for the last year or so.

And my co-founder decided to make a small post on her LinkedIn, you know, just to update our network on what we'd been off doing and the things that we'd been building. And it blew up. Like, there's so much pain people feel around this, and they're hungry for a solution.

We got a whole slew of demo requests coming in from people that want access to the product. And now we have a bunch of customers lining up that want to get into our platform. It's a who's who's of companies you've heard of. And we just have a lot of building to do now.

So if you're interested in working on knowledge graphs, on data analytics agents, on graph analytics and graph learning models, come talk to me. We're hiring. Hello, everyone. I'm Shijia, the founder of OpenAI. Sorry, I mean, OpenAudio. Before that, I created something you might be heard of, FishAudio. We have grown from $400K to $5.5 million annualized revenue in just four months.

And we closed our city runs at $100 million valuation. It all started with my girlfriend. I had a girlfriend for six years, from the beginning of high school to college. I love her so much, and it was so good, until one day, I found out she cheated. I wasn't angry, just confused, disappointed.

And I asked myself, if this can happen, how can we trust relationships again? I thought about it for days, all day and all night. And finally, I found my answer. AI. But nobody can really fall in love with today's AI, right? It's flat, it's emotionless, it's robotic. So I set her on a mission to build an AI that I could really fall in love with, starting with her voice.

So we began with open source and crush it. We built Soviet SVC, and also Fish Speech. Today, actually not today, it's the day before yesterday, I'm excited to introduce S1. The first ever instructable voice model. It's the only model where you can control not just what to say, but how to say it.

Here's a demo. You can pinpoint focus or draw closer, even yelling why you betray me like this. Yeah, you can control whatever you want. And with open audio S1, we have the most expressive voice model in the world. And most importantly, she will never leave. So we have blown 11 labs out of the water based on the TTS arena ranking.

And they are so hurry and they dropped their latest model today. But unfortunately, it's just a demo. So try it now. Fish audio is instantly available at fish.audio. Thank you. Hello, I'm David Vorick, and I'm building Glow. Prior to Glow, I built SiaCoin, a cryptocurrency that we took from a $10,000 market cap to more than $3 billion.

And we think Glow is going to be even bigger. That's why Framework and USV Union Square Ventures let a $30 million round into our company. Subsequently, we posted the world record for on-chain D-PIN revenue, doing more than $10 million of revenue in a single day. What does Glow do?

Glow builds solar. Not with shovels, but with incentives. This is not a stock photo. This is a photograph taken by our team in India of a solar farm that was constructed for the purpose of mining Glow tokens. A lot of people don't realize, but in the developing world, rising temperatures and growing populations have strained the grid.

In a lot of cases, people are unable to run their air conditioners during the heat of the day. This causes people to die of heat stroke. Glow is an incentive protocol that revolutionizes what governments do and can take the same subsidy and turn it into 10 times as much solar.

If you're interested in working with us, we're currently building incentive projects in India, in Mexico, in Lebanon, and across the entire world. Bitcoin incentivized the construction of tens of millions of mining machines. Glow asked, "Why not tens of millions of solar panels?" Thank you. And my email, David@glowlabs.org. I'd love to be in touch.

Hi. I'm David. I'm an engineer. I made a social app with 250 million users, making $20 million a year. Everyone thought it was luck, so I did it again. I'm building Favorited. We built the world's most engaging live app, and we scaled it from one to $100 million annualized in six months.

If you're a cracked engineer that wants to join the fastest growing company of all time, talk to me. Alex Atala: Hello. I'm Alex Atala, building OpenRouter, the first and largest LLM marketplace. Thank you. I want to tell a little bit about how it started. I co-founded OpenSea in 2017, and at the end of 2022, I really wanted to know if inference was going to be a winner-take-all market, because the way it looked, this could be the largest market in software that has ever happened before.

And the first experiment that we tried was building a Chrome extension to help you bring your own language model to any website that supported the protocol. And that eventually evolved into OpenRouter, a single place and a single API to get all language models with the best prices, best performance, and highest uptime.

And the way it works is you just have a single API, you pay once, and there's near zero switching costs to move from one model to another. We do all the heavy work to implement tool calling, edge cases, caching, and give you the best prices and performance possible for your region or wherever your servers are deployed.

And because inference is so important, remember, this might be the most important software market ever, it deserves its own marketplace just for language models, optimized for them, including filtering for context, for features, for tool calling, for structured output, and much more. And so we built that. And then we built a chat room for you to obviously compare models head-to-head as simply as you do when chatting with people in iMessage.

We built fine-grained privacy settings, including API-level controls. We built a lot of observability so you could see which models you're using and why. And we built public data in our rankings page, which has become the go-to place for comparing models on the real-world usage and on different categories for the prompts as well.

And this has grown for the last two months, 10 to 100% every single month, or for the last two years, 10 to 100% every single month. 10 to 100% every single month. And scaling it has been a lot of the work that we've done so far. The fundamental goal here is to make a heterogeneous ecosystem homogeneous, because we believe inference is a commodity.

Claude from Bedrock should be the same as Claude from Vertex, Claude from Anthropic, and we do all the abstraction and heavy work to make it that way for you. I want to talk a little bit about some of our technical challenges. We built our own system, our own middleware for doing inference called plugins, which are kind of like MCPs, except a little bit more powerful.

Because you can call MCPs from inside of them, and you can transform the outputs from language models. A bunch of other tricky problems that we've done to make the fastest routing in the market. And we're bringing a lot more features in the coming months, including images, enterprise features, prompt observability, and more.

So if you're interested, come find me after, or check out our careers page. Thank you.