david benitez

Reflection is partnering with Shinsegae Group to build a 250-megawatt sovereign AI factory for the Republic of Korea. Open intelligence. Built on trust between allies. Owned by the nations that need it most. The future of sovereign AI. Read more in the @WSJ.

American AI companies and open-source models can truly empower partner nations in their pursuit of meaningful AI sovereignty. Huge announcement by @reflection_ai and Shinsegae Group in the Republic of Korea. The American AI Export Program is rolling out 🇺🇸🇺🇸🇺🇸

i mean alcaraz is playing the best tennis ever right now it’s hilarious

zverev and unplayable don’t even belong in the same dictionary…

ATP 🎾 Alexander Zverev ML (+450) (1%) This is just simply too wide with Carlos Alcaraz. When Zverev is playing confident tennis, he’s unplayable. He will challenge and play toe-to-toe with Alcaraz from the baseline. He’s too dominant in these conditions. This is not an easy task that the market makes it out to be. We’ve seen the unplayable level this week at the Australian Open from Zverev. These are the moments I can always count on Zverev to be at his best and he’s yet to let me down so far. Zverev has such a reliable and dominant first serve that he’s landed 72% of the time here at the AO. The first serve is so critical in these conditions, especially against Alcaraz. Zverev has won 77% of the points when he’s landed the first serve over the last three matches. He’s coming off basically three strong performances, with unplayable outings against Cerundolo and Tien. There is no better spot to back Zverev than right here, especially at Alcaraz’s weakest event/surface. Alcaraz has yet to drop a set, but his opponents have been pretty bad. Not a single opponent Alcaraz played has been able to command the serve at a consistent rate like Zverev will. When opponents are feeding Alcaraz second serves out the ass, then of course he’s going to be able to establish rhythm. That’s why the first serve is so critical in these faster conditions, in which Zverev will effectively pound. It’ll set up the baseline game, in which Zverev should control, and ultimately force Alcaraz to rush and develop unbalance. The backhand is elite and the combination of consistent power in rallies should fare well for Zverev. From what I’ve seen from Zverev this week, there’s no doubt in my mind that he’ll control the pace of this match. The last time these two met at the AO, Zverev dominated this match. Alcaraz failed to compete with Zverev in these conditions. Zverev took home 73% of the points off his first serve, similar to his unplayable level right now, and ultimately crumbled Alcaraz from the baseline and suffocated any hope he had. Expect Zverev to force Alcaraz to rush his game and expect errors from Carlos. Zverev is too strong and will be a tough opponent for Alcaraz to get over his AO hump. Again, this price is too wide. The head to head is too competitive with Zverev being the more dominant player on these courts and conditions. 36 wins for Zverev on these courts with 3 SF appearances and a Finals appearance last year. At this price, I’m backing my fucking goat.

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outlandish statement to say Bublik is World 3?… and on a hot aussie day World 2!?!?!

lol

What do you notice about the Top 15 highest Total QBR games in NFL history

Today Groq entered into a non-exclusive licensing agreement with Nvidia for Groq’s inference technology. Along with other members of the Groq team, I’ll be joining Nvidia to help integrate the licensed technology. GroqCloud will continue to operate without interruption. Learn more here: groq.com/newsroom/groq-…

Exclusive: Nvidia buying AI chip startup Groq for about $20 billion in its largest acquisition on record cnb.cx/3Ng5BU1

If you asked Zay Flowers to drive north from Florida to New York he would go to Oklahoma first

most importantly a HC

YAMAMOTOOOOOOO

@Lj_era8 It’s time to tweet Johnny.

Why is poker so hard

lol

Today we're sharing the next phase of Reflection. We're building frontier open intelligence accessible to all. We've assembled an extraordinary AI team, built a frontier LLM training stack, and raised $2 billion. Why Open Intelligence Matters Technological 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, what enterprises deploy. 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 (e.g. self-attention, next token prediction, reinforcement learning) that were shared and published openly. Now AI is becoming the technology layer that everything else runs on top of. The systems that accelerate scientific research, enhance education, optimize energy usage, supercharge medical diagnoses, and run supply chains will all be built on AI infrastructure. But the frontier is currently concentrated in closed labs. If this continues, a handful of entities will control the capital, compute, and talent required to build AI, creating a runaway dynamic that locks everyone else out. There's a narrow window to change this trajectory. We need to build open models so capable that they become the obvious choice for users and developers worldwide, ensuring the foundation of intelligence remains open and accessible rather than controlled by a few. What We've Built Over the last year, we've been preparing for this mission. We’ve assembled a team who have pioneered breakthroughs including PaLM, Gemini, AlphaGo, AlphaCode, AlphaProof, and contributed to ChatGPT and Character AI, among many others. We built something once thought possible only inside the world’s top labs: a large-scale LLM and reinforcement learning platform capable of training massive Mixture-of-Experts (MoEs) models at frontier scale. We saw the effectiveness of our approach first-hand when we applied it to the critical domain of autonomous coding. With this milestone unlocked, we're now bringing these methods to general agentic reasoning. We've raised significant capital and identified a scalable commercial model that aligns with our open intelligence strategy, ensuring we can continue building and releasing frontier models sustainably. We are now scaling up to build open models that bring together large-scale pretraining and advanced reinforcement learning from the ground up. Safety and Responsibility Open intelligence also changes how we think about safety. It enables the broader community to participate in safety research and discourse, rather than leaving critical decisions to a few closed labs. Transparency allows independent researchers to identify risks, develop mitigations, and hold systems accountable in ways that closed development cannot. But openness also requires confronting the challenges of capable models being widely accessible. We're investing in evaluations to assess capabilities and risks before release, security research to protect against misuse, and responsible deployment standards. We believe the answer to AI safety is not “security through obscurity” but rigorous science conducted in the open, where the global research community can contribute to solutions rather than a handful of companies making decisions behind closed doors. Join Us There is a window of opportunity today to build frontier open intelligence, but it is closing and this may be the last. If this mission resonates, join us.

Excited to be working with the leader of frontier open intelligence!

so sick … #ToTheMoon