Next Friday night, join us for an evening of drinks, good vibes, and networking @CVPR 2026! πΊπΈ
βAs the sessions wrap up for the day, itβs time to wind down. Hosted by @Sky9Capital and co-hosted by @ZZZZZPotentials , we are thrilled to bring together AI researchers, founders, builders, and partners for a relaxed evening of conversation.
Spots are limited. RSVPπ₯
https://t.co/9rwFJhDHYg
#CVPR2026
Today Reactor is coming out of stealth. Weβve raised $59M in Seed and Series A funding, led by @lightspeedvp, with participation from @AmplifyPartners, @wndrco, @Sky9Capital, and @FPVventures.
Reactor is the platform for building in the World Model era: the infrastructure that lets developers build with them at global scale for the first time. Stream from a frontier World Model to your app, in real time, all in under 10 lines of code.
World Models represent the next major shift in AI: pixels, audio and actions are generated on the fly, in real-time, in response to user inputs, and to the environment. Every time computing has made a shift from passive to interactive, entire industries appeared that didn't exist before. We're standing in front of such moment again.
Over the last 6 months, weβve assembled an all-star team with alumni from Apple, Meta, Google, Luma AI, Netflix, and Replicate. We're already partnering with some of the biggest names and labs in the world, and hundreds of developers are already building on Reactor.
The World Model era starts now.
Agents can browse, think, and plan. But the moment they need to pay β they stop.
Introducing Anyway - the first financial OS for agents.
One integration. No more babysitting of your money.
More at https://t.co/0hAOd3dnvG
Today, we are thrilled to officially launch RadixArk with $100M in Seed funding at a $400M valuation. The round was led by @Accel and co-led by @sparkcapital.
RadixArk exists to make frontier AI infrastructure open and accessible to everyone. Today, the systems behind the most capable AI models are concentrated in a small number of companies. As a result, most AI teams are forced to rebuild training and inference stacks from scratch, duplicating the same infrastructure work instead of focusing on new models, products, and ideas.
RadixArk was founded to change that. We are building an AI platform that makes it easier for teams to train and serve the best models at scale.
RadixArk comes from the open-source community. We started with SGLang, where many of us are core developers and maintainers, and expanded our work to Miles for large-scale RL and post-training. We will continue contributing to both projects and working with the community to make them the strongest open-source infrastructure foundations for frontier AI.
We would like to thank our long-term partners, contributors, and the broader SGLang community for believing in this mission. We're also grateful to @Accel and @sparkcapital, NVentures (Venture capital arm of @nvidia), Salience Capital, A&E Investment, @HOFCapital, @walden_catalyst, @AMD, LDVP, WTT Fubon Family, @MediaTek, Vocal Ventures, @Sky9Capital and our angel investors @ibab, @LipBuTan1, Hock Tan, @johnschulman2, @soumithchintala, @lilianweng, @oliveur, @Thom_Wolf, @LiamFedus, @robertnishihara, @ericzelikman, @OfficialLoganK, and @multiply_matrix among others.
Thanks for the exclusive interview with @MeghanBobrowsky at @WSJ about our vision.
Introducing π¨ππππππππ πΉππππ ππππ: Rethinking depth-wise aggregation.
Residual connections have long relied on fixed, uniform accumulation. Inspired by the duality of time and depth, we introduce Attention Residuals, replacing standard depth-wise recurrence with learned, input-dependent attention over preceding layers.
πΉ Enables networks to selectively retrieve past representations, naturally mitigating dilution and hidden-state growth.
πΉ Introduces Block AttnRes, partitioning layers into compressed blocks to make cross-layer attention practical at scale.
πΉ Serves as an efficient drop-in replacement, demonstrating a 1.25x compute advantage with negligible (<2%) inference latency overhead.
πΉ Validated on the Kimi Linear architecture (48B total, 3B activated parameters), delivering consistent downstream performance gains.
πFull report:
https://t.co/u3EHICG05h
It started with the silly idea of generating images and turning them into music. We didnβt know if it would work, and we didnβt care if anyone used it. We were building it for ourselves.
As musicians, we marveled at how this instrument could inspire and challenge us. A lot has changed since then, but that sense of wonder has remained.
Couldnβt be more excited to continue the journey as part of @GoogleLabs
On Sep 12 in SF, we are throwing a hype night with @ZZZZZPotentials featuring our portfolio founders and all 3 cohorts Sky9 Fellows. Enjoy an evening of:
π€Networking with DOPE AI founders, VC investors, and fellow innovators
π‘Insights of cutting-edge trends in agents, models, robotics, bio, etc
π΄ Bites & drinks (on us!)
Grab your spot β https://t.co/O2RnlyI7C0
#AI #SanFrancisco #VC #Startups
This Fri we had the incredible opportunity to bring together 700+ passionate fellas from AI community for a night of inspiration and celebration. Thanks again to our co-host @MindsDB, amazing speakers @litanlitudan , Jorge Torres, @changhiskhan, @sethforsgren & @BenHolfeld π₯
Who will you make a song for?
Create music by simply entering lyrics and a sound prompt on the new https://t.co/8r3MmEzMJu
Whether you're a musician like @TheChainsmokers (our advisors!), or just making βgood morning!β riffs for a friend, we hope youβll come make music with us
Are you team dog or team cat? Weβve got an Xbox for either!
Follow & RT withΒ #PartyAnimalsSweepstakes for a chance to win this Party Animals Xbox Series S consoles and controller bundle!Β
Ages 18+. Ends 9/20/23. Rules: https://t.co/FYtMwsk2gn
Can't wait to see a cage fight between Elon and Mark? π¨πΌββ€οΈβπβπ¨πΌ
Join our AI-powered game on Discord to watch or craft the duel you've been imagining!πΎ
https://t.co/6uSPjQAtEl
#CageMatch#Elonmuskvsmarkzuckerberg#ElonMvsMarkZ#cagefight#GPT
We @litanlitudan@solsticestone just open-sourced a weekend project which implements the memory, planing, and reflection mechanism from Stanfordβs Generative Agent paper .The reaction of the AI bots are quite human appealing.
Check out our project :https://t.co/ZFfAdWCrL9