How is AI accelerating scientific progress? On October 7, I'm moderating a conversation with three founders and leaders working on that question: • Michelle Lee, CEO of @medra_ai • Andy Beam, CTO of @LilaSciences • Gleb Kuznetsov, CEO of @ManifoldBio @AnthropicAI and @nvidia are bringing together founders, researchers, and builders at Claude Founder House during #SFTechWeek to talk about AI for science and drug discovery. We’ll start with a short panel, then continue the conversation over drinks. If you’re building in this space, we’d love to see you there. October 7 · 5–7:30pm PDT · San Francisco Request to join: luma.com/claude-ai-for-scien…

Excited to announce Volantis's $88M Series A. We are solving Al's memory bottleneck by using optics, enabling chips with huge amounts of fast & cheap memory. By boosting both the memory bandwidth and capacity per chip by orders of magnitude, we enable ultra-fast inference (up to 10,000 tps/user) for large models (>10T) - with low $/tok to boot. Initially, this will enable insanely fast agents - think coding agents that finish in minutes or even seconds instead of hours. More excitingly, optics is a fundamentally scalable way to increase memory systems. Not 2X/year, but by orders of magnitude across new generations. This will enable a structurally new Al industry, including restarting scaling laws, holding entire repos in context windows & more. Our team has pioneered many core semiconductor technologies: the 1st CoWoS product, early HBM, the 1st silicon photonics CPO systems, the 1st high volume tunable VCSELs, the 1st processors to directly communicate using light & more. We’ve already sent data >10× farther than equally tiny electrical wires inside a chip package. Our next iteration is already taped out and targets world-record bandwidth density over relevant distances, read more: volantissemi.ai/news-insight…

A nice small example of AI acceleration in biology happening in real time: Last week, as part of our announcement of mBER-2, @ManifoldBio’s latest protein design model, we shared that we expanded design to 50 compact protein formats from nature, just 10-45 amino acids long. We called them “microbinders.” Just one week later, “protein microbinders” are already an official category in the Anthropic × Adaptyv protein design competition. Google protein "microbinders” and the AI Overview already describes the category, citing our announcement. Excited to see the community expand into these formats!

At FutureHouse, we focused on scientific discovery. However, if we want to actually accelerate progress in medicine, we need to work across the entire R&D stack. We are now deploying specialized Kosmos agents for Clinical Protocol Design and Regulatory Authoring to several of our partners, which can cut months off the amount of time needed to get molecules into the clinic, save companies tens of millions of dollars, and dramatically reduce the likelihood that submissions get stuck at the FDA. Super excited to be able to share this story now, thanks to our work with Population Health Partners, one of the best drug developers in the world and a fantastic development partner for us. The AI-native pharma stack is here now, and the future of medicine is around the corner. Read more: x.lingyaoai.com/EdisonSci/status/21053…

At Hot Chips, d-Matrix stole the show with Raptor, the first 3D-stacked DRAM accelerator. They didn't waste any time building on the momentum by announcing that Raptor has been designed into NVIDIA's MGX rack as an NVLink Fusion partner. The rack features 144 XPUs, 2.3 TB of 3D-DRAM at 7.2 PB/s per rack, targeting ~1,000 tok/s/user on 3T models at 1M context. NVIDIA already has Groq 3 LPX with its 128 GB of rack-level SRAM. Raptor brings 18x the capacity for the frontier models SRAM can't fit. NVIDIA's decode portfolio now spans the model size spectrum with Vera CPUs, NVLink, and Spectrum-X attaching either way. NVIDIA just validated the 3D-DRAM bet two years before first revenue. d-Matrix proved it's going to scale.

Excited to work with NVIDIA to bring Raptor to NVIDIA MGX with NVLink Fusion. Building the next generation of AI infrastructure together.

Big news for d-Matrix and AI inference. We’re collaborating with NVIDIA to bring our next-gen Raptor inference XPUs into NVIDIA's MGX rack-scale infrastructure with NVIDIA NVLink scale-up interconnect. Ultra-low latency inference. Premium-level token services. Built to scale. Read the full announcement: d-matrix.ai/announcements/d-… #NVLinkFusion #AIInfrastructure #AgenticAI #dMatrix