Introducing Ricursive Intelligence, a frontier AI lab enabling a recursive self-improvement loop between AI and the chips that fuel it. Learn more at ricursive.com

Great to see our vision of end-to-end chip design featured in @eetimes. Thanks to @sallywf for the excellent profile. Traditional chip design costs too much time and money. By changing that, we're enabling truly transformative applications of AI that were previously impossible. eetimes.com/startup-ricursiv…

The task: rapidly design highly performant chips. The vision: serve intelligence at a price and capability impossible to match. Our co-founder and CEO @annadgoldie sat down with @FounderCoHo to break down the recursive self-improvement loop at the heart of Ricursive's work. The task and vision are ambitious, but so are we. Full conversation: youtube.com/watch?v=kcll9IgW…

Transforming chip development requires not only the best researchers, but also the dedicated compute and unwavering focus that pushing the boundaries of AI demands. That's why we started Ricursive. Grateful to be featured in @Bloomberg by @byJuliaLove alongside other daring founders. bloomberg.com/news/articles/…

Chips are the fuel for AI. By using AI to design, optimize, and automate chip design, we can close the recursive self-improving loop between AI and its physical substrate. Our co-founders @annadgoldie and @Azaliamirh took the stage at @sequoia AI Ascent 2026 to share more about Ricursive’s vision to accelerate and democratize chip design. Proud of the progress our world-class team has already made. And we’re just getting started!

Thanks to @NicolSchwarzK and @CNBC for spotlighting our work. The core AlphaChip team is back together and we're laser focused on the most consequential loop in technology today: AI for chip design and chip design for AI. cnbc.com/2026/04/28/meta-goo…

Building the future of silicon requires the best talent in the world. That's why we’re excited to welcome Mark Lee to the team. Mark is a titan in the chip industry: he led physical design for the iPhone and iPad, helped technically scope Apple's revolutionary M1 chip, and directed RTL-to-GDS efforts for Tenstorrent's leading Ascalon processor. Mark has spent decades pushing the limits of what silicon can do. We’re thrilled to have his expertise as we together reinvent chip design.

Honored to be named to the inaugural @Forbes AI 50 Brink List. With a brilliant team and the backing of incredible investors, we're reducing the chip design cycle from years to days. AI can design better chips. Better chips can train better AI. Join us: ricursive.com/careers. Full list: forbes.com/sites/sofiachierc…

It’s been a true pleasure working with the wonderful @guruchahal and @ravi_lsvp at @lightspeedvp, who led this round. We are also proud to be backed by an incredible group of investors, including DST (@saurabhsgupta and @yurimilner), NVentures (@ChaseOverlie), Felicis (Michelle Delcambre, @DetweilerJames), Radical (@_RobToews), 49Palms (Madhavan Ramanujam, Joshua Bloom), and @Sequoia (@stephzhan).

Thrilled to share that @annadgoldie and I are launching @RicursiveAI, a frontier lab enabling recursive self-improvement through AIs that design their own chips. Our vision for transforming chip design began with AlphaChip, an AI for layout optimization used to design four generations of TPUs, data center CPUs, and smartphones. AlphaChip offered a glimpse into a future where AI designs the silicon that fuels it. Ricursive extends this vision to the entire chip stack, building AI that architects, verifies, and implements silicon, enabling models and chips to co-evolve in a tight loop. We sat down with WSJ’s @berber_jin1 to discuss Ricursive: wsj.com/tech/this-ai-startup…

Excited to announce that @Azaliamirh and I are launching @RicursiveAI, a frontier AI lab creating a recursive self-improving loop between AI and the hardware that fuels it. Today, chip design takes 2-3 years and requires thousands of human experts. We will reduce that to weeks. This will be incredibly hard. For context: Go has a search space of 10^360. A simplified version of chip placement—only one part of the design process—has a search space of 10^9000. But we are the right team to solve it. We co-founded the Machine Learning for Systems team at Google Brain. There, we built AlphaChip—an RL agent for chip placement. AlphaChip has been used to design four generations of TPUs, data center CPUs, autonomous vehicle chips, and mobile phone chips. These chips are running in data centers and devices all over the world. Our immediate goal is to dramatically accelerate chip design. Next, we plan to design chips end-to-end given an ML workload, unlocking a Cambrian explosion of custom silicon. Finally, we will close the recursive loop. We will build our own chips, train our own models, and co-evolve them on the path to superintelligence. AI designs better chips 🔄chips train better AI We sat down with @WSJ’s @Berber_Jin1 to discuss Ricursive: wsj.com/tech/this-ai-startup…