DeepSeek’s New Rival? Reflection AI Raises $2B in the U.S.

0:01Today on the AI chat podcast, we're talking about reflection AI, which has just raised$2 billion dollars. This is an insane amount of money, but they have a very big mission and vision. So today on the show, we're going to be breaking down what they're going to be spending that two billion dollars on, the open source projects they're involved with, why this is a big win for United States AI companies, what the vision and the pitch is that they're making here. And we're going to get into all of the interesting details and some of the drama. So buckle up, let's get into the podcast. Before we get in, I wanted to mention when Reflection AI launched their open source AI model, you're going to be able to find that over on AIbox.ai, along with over 40 different AI models.

0:45If you're someone that pays for$20 subscriptions to Claude and OpenAI and all of the other AI models, I'd love for you to try out my startup, AIbox.ai, where for$20 a month, you can get access to all of the top text models. You get a whole bunch of amazing image models, including OpenAI, Ideogram, Black Forest Labs. That's Flux that Grok uses. is. You also can get text to speech, 11 labs, audio, image, all the top, you know, anthropic, open AI, Google, deep seek, all of them for text models as well. So go check it out. AI box.ai. You can try out all the different AI models, test them side by side.

1:22I would love for you to try out the platform. The link's in the description. All right, let's talk about reflection AI. So they just tweeted and they said, you know, that they're, you know, building their next phase of reflection. They said, we're building frontier open intelligence accessible to all. Really, it feels not really like a dig at OpenAI, but basically it feels like Reflection AI is taking up what OpenAI was supposed to do. It's kind of interesting because Elon Musk, you know, was quite vocal about roasting OpenAI, about not being an OpenAI company, but XAI also is not open source.

1:53And so a lot of people kind of thought maybe he would be building the open source AI company, which he's not doing. And it feels like the torch in America, at least, has been passed to Reflection because globally we have Quen and DeepSeek in China that are doing that. So it feels like Reflection AI is the American response to this. So they've raised$2 billion to build. Basically, they're going to be creating LLM models. They said technology and scientific progress is driven by values of openness and collaboration. the internet linux and the protocols and standards that underpin modern computing are all open this isn't a coincidence open software is what gets forked customized and embedded into systems worldwide it's what universities teach what startups build on and what enterprises deploy so i think they're making a really compelling case here um you know we've seen that obviously open ai has gotten like an insane amount of bad pr for being an open source company getting a bunch of donations that were tax-free for their open source foundation and then turn it into a for-profit company you know taking 10 billion dollars from microsoft all of the drama that came with open ai and then trying to switch into now a for-profit organization and sam altman you know insisted it was the only way for him to be able to raise money and for him to be able to basically create uh agi or or like a good outcome for um the company now it would appear that reflection just raised two billion dollars.

3:17This is an incredible amount of money. We've seen other big companies or other AI LLMs, usually with top tier talent, the co-founders of OpenAI have all gone on to raise at billion dollar valuations or billion dollar rounds of funding. Two billion dollars is really impressive and it's also considering there is no AI model. Reflection has not put anything out yet. They're planning on their next model, but they don't have anything put out. So this$2 billion here is raised without basically the product that they're promising. Now they're promising a frontier model that's going to compete with open AI.

3:54It's going to be this open source model. That's amazing. This is what they said on their X post. They said, quote, open science enables others to learn from the results, be inspired by them, interrogate them and build upon them in order to push the frontier of human knowledge and scientific advancement. AI got to where it is today through scaling ideas. self-attention, next token prediction, reinforcement learning that were shared and published openly. So again, they're just kind of pushing this, uh, they're trying to push this idea that a lot of the technology we have today, and I'm not saying this is wrong.

4:27I'm just saying this is, this is their, like their argument. Their point is that a lot of what we have today is because of open source and because of the collaboration, like all of these different people and willing to give their time and energy to something that's open source and that they can build on top of. And I think building on top of it is a huge point, right? Like when you think about these open source models, who's the target audience? It's countries that want to build their own AI models for their whole country or huge organizations that don't want to be paying open AI absorbent amounts of money.

4:56They want to be able to customize it the way that they want. So there's a lot of resources that can go into these. They also cover kind of what they've built. So they said, over the last year, we've been preparing for this mission. We've assembled a team who's pioneered breakthroughs, including Palm, Gemini, AlphaGo, AlphaCode, AlphaProof. and contributed to ChatGPT and Character AI, among others. They have a really strong team that is backed from Google DeepMind, is where a lot of their researchers are coming from. TechCrunch did a whole article on this, and they talked basically, the thing that's interesting that I guess I haven't mentioned yet, is that, so they raised this$2 billion.

5:30They did this at an$8 billion valuation, and that is a 15x leap from their valuation just seven months ago. So they had a$545 million valuation seven months ago, and now an$8 billion valuation. So originally when they launched, I know a lot of people are asking, like, how did they even get started? How were they even raising this much money? They were just focusing on coding agents, autonomous coding agents. And I think they very quickly realized they have the, like, in order to build an autonomous coding agent, they basically have the talent to be able to build an LLM that could go and compete head-to-head with OpenAI, theoretically.

6:07The most famous coding agent and product on the market is Claude Code right now. and so if they're competing with that like Claude Code is just backed by Claude which is a direct competitor OpenAI and is competing at a very high level so I think this is really interesting this is going to be an open source alternative to OpenAI and Anthropic for sure but also Chinese firms like DeepSeek that are doing this open source they're going to be competing directly open source so So this is actually started just last year in March by Misha Laskin, who was working, he was doing reward modeling for DeepSeek's Gemini project.

6:45And so this is a really, really powerful team. They only have about 60 people currently that are working for them. Most of those are researchers and engineers. You can imagine the team after raising$2 billion is probably going to scale out to a lot of different areas like go to market and other areas now that they have enough money. But what's interesting here is their CEO, who is Laskin, said that they have secured enough compute clusters and that they hope to release a frontier language model next year that's trained on, quote, tens of trillions of tokens. So they're really trying to build something big.

7:20He also said, quote, we built something once thought possible only inside of the world's top labs, a large-scale LLM and reinforcement learning platform capable of training massive mixture of experts or MOEs models at frontier scale. So I think what's really interesting here, actually, I'll finish that quote, and then let's talk about mixture of experts. But he said, we saw the effectiveness of our approach firsthand when we applied it to the critical domain of autonomous coding. With this milestone unlocked, we're now bringing these methods to the general agentic reasoning. Yeah, basically, like if you can do coding, they chose one of the hardest problems.

7:53And once they realized they could crack that, they're like, well, actually, the technology could just be used as a general purpose LLM. Coding is a really good one because it's like thinking, it's logic, it's putting a lot of complex math and things together. And all of a sudden, if you can really crack autonomous coding, you're like, okay, well, I guess it's also just an LLM. I think that's what they realized. MOE that they're doing is specifically kind of the big breakthrough that DeepSeek had, which was followed by Quen and Kimi. Those are other models from China, but it's this mixture of experts.

8:22So basically you ask the model a question and it has these experts inside of the model. I think OpenAI has like 16 and it basically picks which of these 16 experts, maybe a coding expert, maybe a PhD in psychology expert, right? Like you can imagine these different experts and it will, the model will pick which of these experts are the best at, you know, fine-tuned and answering those questions. And so it seems like they've done that. And this is kind of what really enables these models to think much better. The benchmark Mark's scores started scoring quite high once DeepSeek cracked this. OpenAI, Grok, all of them are now doing this.

8:57So what he specifically said, though, is that DeepSeek and Quinn and all these models are a wake-up call because if we don't do anything about it, then effectively the global standard of intelligence will be built by someone else. It won't be built by America. So a really big part of their pitch is that in the United States, we are falling behind on open source, basically because OpenAI abandoned it. Now, is it true? OpenAI did not completely abandon it. They did recently release a really powerful OpenAI model. But I think a lot of people are worried that these are far and few, you know, these are few and far in between.

9:27Like OpenAI releases one and then like two or three years later, they might release another one because everyone's kind of harassing them and they want to get some goodwill. That's the way it feels. I don't know if this is accurate, but I'm just telling you how it feels. And so if there's a company that's exclusively focusing on it and this is their mission, I think that a lot of people will be willing to support them and back this. And in addition to this, it puts the U.S. and all of our allies at a disadvantage because right now enterprises in sovereign states, they're not going to use the Chinese models due to a lot of different legal repercussions.

9:58And so if we're not using those, we need an alternative. And so this is kind of their pitch to become the alternative. And specifically, he said, quote, so you can either choose to live at a competitive disadvantage or rise to the occasion. So sets himself up as this. So what are people saying about this, I guess, is the next point. David Sachs, who is a host on the All In podcast, he's also the White House AI and Crypto Czar, he posted on X recently talking about this, and he said, it's great to see more American open source AI projects. A meaningful statement of the global market. We'll prefer the cost, customability, and control that open source offers.

10:34We want the U.S. to win this category too. I think this is true. Obviously, you know, we have Anthropic, we have OpenAI, we have Google Gemini, so we have like, and we have Grok, so we have like the top four AI models that are closed source, great, but the top open source models are not in the United States. They're in China, they're in France with Mistral, and so like we really want to win that as well. So I'm excited to see that Reflection AI is able to raise so much money and is able to push such a big company here. Clem DeLang, who's the co-founder and CEO of Hugging Faces, which is kind of an open source collaboration platform for AI builders, he was talking to TechCrunch about all of this, and he said, quote, this is indeed great news for American open source AI.

11:17Now the change will be to show high velocity of sharing of open AI models and data sets similar to what we're seeing from the labs dominating in open source AI. So I think there's a lot of hope here. People are really excited about what's going on. and overall this is going to be, I mean, this is a massive amount of money. So as far as who's actually investing and putting money in, they have NVIDIA, of course. Why would NVIDIA not put money into a$2 billion, you know, an$8 billion company that's taken in$2 billion that inevitably is going to have to spend most of that on NVIDIA GPU chips. So great move by NVIDIA.

11:50It's also being invested in by Disrupt, DST, 1789, B Capital, Lightspeed, GIC, Eric Wang, Eric Schmidt, City, Sequoia, CRV, and others. So basically all of the big, all the big players that have been invested in all the big AI companies are jumping on this, this really high signal. And obviously has a very impressive team that is putting this together. Laskin is a legend. And so I think he's able to raise that kind of legendary money. He's also built an impressive, you know, he's focused on an impressive area with the coding and the AI agents. And so he's kind of shown that he's capable of pulling this off.

12:26So overall, really excited about this. I'll keep you guys up to date on what Reflection is actually able to release when they come out with their next model. And as always, if you want to try all of the top AI models for only$20 a month, you don't want to pay subscriptions to every single AI platform in the world, make sure to go check out AIbox.ai to get access to all of the top AI models in one place for$20 a month. This is literally a no brainer. or even if you have a favorite AI model like OpenAI that you use most of the time, anytime that you wanna go use 11 labs and it's gonna cost you 50 bucks to go sign up and run a bunch of tokens and generate some things, just go get a subscription to AI Box, save yourself the pain, 20 bucks, and you get everything.

13:06All right, thanks so much, everyone, and I hope you all have a fantastic rest of your day.