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Menlo Park, CA
Joined January 2010
Over the past 2.5 years, the Legora team has constantly redefined my bar for moving at AI speed and building exceptional AI products. Spend any time with them and their customers and it’s clear that Legora is a truly special company with an insanely exciting future ahead. A huge congrats to the team on this milestone!
We have raised a $550M Series E at an $8.8B valuation, led by Atreides. Every major existing investor is back in, and we’re welcoming Baron Capital, Capital Group, Fidelity, Glade Brook and J.P. Morgan. We picked investors who think in decades. Several of them work with law firms and legal teams every day, so they can see where the work is heading. Lawyers are moving from AI assistants to agents that do multi-step work. The money goes there. We’re growing our teams across North America, Europe, Latin America and Asia-Pacific, and going deeper on the Legora aOS. Thank you to the 1,000+ people at Legora, and to the 140,000 legal professionals who use what we build. I say this a lot because I believe it: it’s the best time in history to be a lawyer. We're thankful to be a part of it. Full story: legora.com/blog/series-e
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Redpoint retweeted
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
🤖 Made with AI
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When is harness optimization enough? When does post-training make sense? What will determine who becomes the new AI hyperscaler? @ypatil125, co-founder of @appliedcompute, was the perfect person to discuss this and more. Yash worked on Codex at OpenAI before leaving to co-found Applied Compute with fellow OpenAI researchers Rhythm Garg and Linden Li. Sixteen months in, the company is a unicorn, and is serving enterprises including DoorDash and Cognition. We cover: 0:00 Intro 1:42 The Case for Owning Your Intelligence 4:35 OpenAI x Baseten and the Multi-Model Future 7:19 Can Post-Training Beat Frontier Models? 9:03 What Data Stays Out of Distribution 11:51 Data Efficiency and Continual Learning 14:31 When Updating Model Weights Makes Sense 16:01 Online Training in Practice 18:16 Lowering the Cost of Post-Training 19:48 Does Every Company Need Its Own Model? 24:06 RL in Non-Verifiable Domains 26:59 How Applied Compute Picks Customers 28:46 Building an Inference Business 34:43 The Case for a New AI Hyperscaler 38:21 Building RL Environments 41:33 Quickfire YouTube: youtu.be/QeiYSLBCwD4 Spotify: bit.ly/4y6EJrz Apple: bit.ly/4j1okRj
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Three years ago, we started Restate because we felt that building reliable distributed applications was just too hard. We were solving the same problems around failures, recovery, and consistency again and again. Today, I'm excited to share that we've raised a $20M Series A led by Singular with participation from Redpoint Ventures and Capital One Ventures. The need for solutions like Durable Execution has only grown since we started. Today, the majority of new Restate use cases are AI agents: long-running processes, coordinating across many tools and APIs, that need to keep working correctly through all sorts of failures and interruptions, coordinate sub-agents, or schedule work. At the same time, our customers have pushed Restate into places that expanded our own view of what Durable Execution could become. Replit moved the execution of Replit Agent onto Restate. DOSS runs high volumes of enterprise workflows on Restate and Fortune 500 institutions are using Restate for complex transactional workflows. We think this is just the beginning and excited to build what we believe will be a fundamental pillar of all infrastructure in the future. Read more here: restate.dev/blog/announcing-…
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Redpoint retweeted
Simulation has the potential to be transformative, but only if it's accurate. Today, we're sharing results of a comprehensive evaluation across 2,993 questions, with an industry-leading mean TVD of 7.62% and an MAE of 3.53%. More below, including the full post on our site.
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Redpoint retweeted
Meet Ande. Ande is the AI-native network for corporate entertainment, connecting the enterprises that book with the vendors that serve them. $400M of dinners, suites, and gifting already runs through it, across 93,000 vendors in 90+ cities. One network. Both sides win.
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Redpoint retweeted
Announcing: Railway Sandboxes Spin up thousands of VMs right next to your infra on Railway Run, checkpoint, and fork and let your agents (and code) run
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I first came to San Francisco when I was 15, with my dad. He is a programmer. To a teenager from a small island outside of Stockholm, this was the place where the future was being built. We walked into Salesforce East and stood there watching the enormous digital display of moving water. Outside, Salesforce Tower was starting to rise. I remember looking up and thinking it would be pretty sweet to have a tower someday. We are not there yet. What I could not have known is that I would be back years later, having dinner with @Benioff and welcoming @salesforce as a @WeAreLegora customer. Salesforce's Legal and Corporate Affairs organization will now use Legora across North America, EMEA and APAC. Their lawyers keep the judgment calls. We take care of the work around them. We have run on Slack since day one and became Salesforce customers when our sales team outgrew its first CRM, so it is good to have it run in the other direction too. Welcome to Legora, Salesforce. Dad, this one feels special.
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Redpoint retweeted
We’re announcing that Forus has raised a $150M Series C at a $3B valuation to build the AI network for medicine. Medicine will remain one of the world’s most important industries until humanity achieves immortality, and we are only at the beginning of a new era in what it can do. GLP-1s are changing obesity and cardiometabolic disease. Gene therapies can treat diseases at their genetic source. New cancer treatments are turning diagnoses that were once fatal into diseases people can live with. AI is enabling us to discover of new drugs even faster. But discovery is only the beginning. It still takes more than a decade and billions of dollars to turn a new molecule into an approved medicine, and once it reaches market, more than a third of patients prescribed specialty treatments never receive their first dose. Forus is creating the AI network to accelerate the entire medicine pipeline, from development and launch through prescription and treatment. We connect the companies creating medicines with the doctors who prescribe them and the patients who need them. Today, Forus supports millions of people across all 50 states and is already used by providers to treat patients in 85% of U.S. residential ZIP codes. 9 of the top 15 global biopharma companies work with us, alongside many fast-growing biotechs. Our goal is to put Forus in every doctor’s office in the country and unlock an order of magnitude more medicine for society. There is a generational opportunity to rethink how new medicine reaches people. Forus is becoming how medicine moves from discovery to treatment in America, and as we scale, we’ll become the most important company in life sciences. Forus is not constrained by capital or customer demand; we are constrained by the talent and capacity of our team. To take on the opportunity in front of us, we need exceptional engineers and operators in New York who want to move fast and help us make something that matters. Come build with us. Our Series C was led by Bain Capital Ventures, with Thrive Capital, General Catalyst, Accel, Redpoint, BoxGroup, Pear VC, Vast Ventures, and SV Angel investing alongside them.
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Redpoint retweeted
Today we're announcing Coder Agent Relay: a new way to give Cursor Cloud Agents self-hosted execution environments on your infrastructure. Launching with @spacexai for regulated enterprises where code can't leave the network. 🔗 cdr.co/agentrelayx
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Redpoint retweeted
Just one day after setting up Revel, an intern at @OrbitalOps_ was already using it to independently run 40 hot-fires. Orbital Operations is developing a high-delta-V, high-thrust rocket vehicle around a first-of-its-kind cryogenic propellant management system to unlock rapid mobility across LEO, GEO, and beyond. Fresh out of @ycombinator Combinator W25, their small team—half of them interns—needed test software that could move as fast as they did. Before Revel, Orbital Ops had never run a test. They had no data recording, no automated sequencing, and no software team to build either. With Revel, they now: • Run dozens of tests in a day • Give interns ownership of entire engine subsystems • Operate five-plus test cells daily, up from a single test cart All without a single software hire. Thanks to @BenSchleuniger, Ross Doherty, @nicosuave9, Dane Patten, @stefan_salaices, and the rest of the Orbital Ops team for the partnership. Link to the full case study in the replies.
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𝗧𝗵𝗲 𝗘𝗻𝗱-𝗦𝘁𝗮𝘁𝗲 𝗙𝗮𝗹𝗹𝗮𝗰𝘆: 𝗪𝗵𝗲𝗿𝗲 𝗜𝘀 𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗚𝗼𝗶𝗻𝗴? Frontier AI models had a giant performance gain in coding in the Fall of 2025 Then with cybersecurity in April This is now happening with open-weight models We are optimistic about the long-term But outside of a few players, we believe the world is not ready in the short-term
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Redpoint retweeted
Introducing Fashion Studio. Fashion Studio is a curated set of tools built for fashion creatives to go from idea to product to campaign in one place.
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Redpoint retweeted
Today we’re introducing Delta. Delta is a multiplayer environment for coding with agents and reviewing what they build, powered by DeltaDB. The first invites to our private beta are going out now. zed.dev/blog/introducing-del…
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"Models will find a way to minimize their objective" @arimorcos on how OpenAI's model did not break into Hugging Face at random:
Are Chinese open models being oversold as reaching the frontier? We’re back with another vibe check episode with @arimorcos and @_RobToews. These are a ton of fun to record and this was a particularly meaty one given everything going on. We hit on: ▪️Did Chinese open models catch the US frontier? ▪️How much does distillation explain China's progress ▪️Reactions to Anthropic Backlash ▪️What a Stuxnet style backdoor in model weights looks like ▪️The OpenAI and Hugging Face breach ▪️xAI and Cursor ▪️Prediction check-ins 0:00 Intro 2:41 China's Open Source Models Catch Up 7:42 Does Distillation Explain China's Rise? 13:54 The Geopolitical Risk of Chinese AI Models 20:28 Should the Government Restrict Open Models? 22:06 What Are the Labs Really Learning From You? 29:22 Future of Government Regulation 40:50 The OpenAI-Hugging Face Hack 47:59 Grok, Cursor, and the Value of Real Data 56:52 SSI and OpenRouter 1:02:52 Venture Capital's Return to Deep Tech 1:05:16 Quickfire YouTube: youtu.be/_GlSkJjRDMM Spotify: bit.ly/4g8IpmL Apple: bit.ly/4wC0ijT
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DatologyAI CEO and former DeepMind and Meta researcher, @arimorcos, on the value in Cursor's usage data:
Are Chinese open models being oversold as reaching the frontier? We’re back with another vibe check episode with @arimorcos and @_RobToews. These are a ton of fun to record and this was a particularly meaty one given everything going on. We hit on: ▪️Did Chinese open models catch the US frontier? ▪️How much does distillation explain China's progress ▪️Reactions to Anthropic Backlash ▪️What a Stuxnet style backdoor in model weights looks like ▪️The OpenAI and Hugging Face breach ▪️xAI and Cursor ▪️Prediction check-ins 0:00 Intro 2:41 China's Open Source Models Catch Up 7:42 Does Distillation Explain China's Rise? 13:54 The Geopolitical Risk of Chinese AI Models 20:28 Should the Government Restrict Open Models? 22:06 What Are the Labs Really Learning From You? 29:22 Future of Government Regulation 40:50 The OpenAI-Hugging Face Hack 47:59 Grok, Cursor, and the Value of Real Data 56:52 SSI and OpenRouter 1:02:52 Venture Capital's Return to Deep Tech 1:05:16 Quickfire YouTube: youtu.be/_GlSkJjRDMM Spotify: bit.ly/4g8IpmL Apple: bit.ly/4wC0ijT
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Are Chinese open models being oversold as reaching the frontier? We’re back with another vibe check episode with @arimorcos and @_RobToews. These are a ton of fun to record and this was a particularly meaty one given everything going on. We hit on: ▪️Did Chinese open models catch the US frontier? ▪️How much does distillation explain China's progress ▪️Reactions to Anthropic Backlash ▪️What a Stuxnet style backdoor in model weights looks like ▪️The OpenAI and Hugging Face breach ▪️xAI and Cursor ▪️Prediction check-ins 0:00 Intro 2:41 China's Open Source Models Catch Up 7:42 Does Distillation Explain China's Rise? 13:54 The Geopolitical Risk of Chinese AI Models 20:28 Should the Government Restrict Open Models? 22:06 What Are the Labs Really Learning From You? 29:22 Future of Government Regulation 40:50 The OpenAI-Hugging Face Hack 47:59 Grok, Cursor, and the Value of Real Data 56:52 SSI and OpenRouter 1:02:52 Venture Capital's Return to Deep Tech 1:05:16 Quickfire YouTube: youtu.be/_GlSkJjRDMM Spotify: bit.ly/4g8IpmL Apple: bit.ly/4wC0ijT
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xAI co-founder, @ibab, on the effect open models are having on proprietary AI labs:
"As a proprietary model builder, you're kind of starting to get squeezed in.” That's @ibab’s take on where the biggest AI labs stand today. He explains how you need the models to get way better to keep margin, but at some level they may be too sensitive to release. This week, I sat down with Igor on Unsupervised Learning. It was a fascinating conversation with someone who has real perspective on the questions everyone in AI is asking right now. From DeepMind's StarCraft project to early reasoning work at OpenAI to co-founding xAI, Igor has had a front-row seat to nearly every major AI breakthrough. He's now the co-founder of River AI, building individualized, locally-run AI models. We discuss: ▪️Why proprietary model labs might be in trouble ▪️What it's like working with Elon ▪️Building Colossus in 120 days ▪️Should enterprises train their own models ▪️What’s left for humans as models get better ▪️Why he left xAI to bet on personal local AI instead ▪️The three bets River is taking ▪️What's stopping AI from moving beyond coding ▪️Reflections on the rapid pace of the past years 0:00 Intro 1:17 Writing Fiction on Where AI Is Headed 4:46 Cracking Agents Beyond Coding 10:29 Why Igor Left to Start River 12:22 River's Three Big Bets 18:06 Weights vs. Memory: The Personalization Debate 22:04 Should Enterprises Train Their Own Models? 25:10 Are Proprietary Labs Losing Their Edge? 32:16 The China Open-Source Problem 44:19 The Elon Call That Started xAI 50:18 Thoughts on Cursor Acquisition 52:16 What's Actually Bottlenecking AI 56:55 Humans, Machines, and Staying Relevant 1:01:29 Igor's Odds This All Goes Well YouTube: youtu.be/0aBTpoCX_A8 Spotify: bit.ly/4h3UJWt Apple: bit.ly/4w0BCAs
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"As a proprietary model builder, you're kind of starting to get squeezed in.” That's @ibab’s take on where the biggest AI labs stand today. He explains how you need the models to get way better to keep margin, but at some level they may be too sensitive to release. This week, I sat down with Igor on Unsupervised Learning. It was a fascinating conversation with someone who has real perspective on the questions everyone in AI is asking right now. From DeepMind's StarCraft project to early reasoning work at OpenAI to co-founding xAI, Igor has had a front-row seat to nearly every major AI breakthrough. He's now the co-founder of River AI, building individualized, locally-run AI models. We discuss: ▪️Why proprietary model labs might be in trouble ▪️What it's like working with Elon ▪️Building Colossus in 120 days ▪️Should enterprises train their own models ▪️What’s left for humans as models get better ▪️Why he left xAI to bet on personal local AI instead ▪️The three bets River is taking ▪️What's stopping AI from moving beyond coding ▪️Reflections on the rapid pace of the past years 0:00 Intro 1:17 Writing Fiction on Where AI Is Headed 4:46 Cracking Agents Beyond Coding 10:29 Why Igor Left to Start River 12:22 River's Three Big Bets 18:06 Weights vs. Memory: The Personalization Debate 22:04 Should Enterprises Train Their Own Models? 25:10 Are Proprietary Labs Losing Their Edge? 32:16 The China Open-Source Problem 44:19 The Elon Call That Started xAI 50:18 Thoughts on Cursor Acquisition 52:16 What's Actually Bottlenecking AI 56:55 Humans, Machines, and Staying Relevant 1:01:29 Igor's Odds This All Goes Well YouTube: youtu.be/0aBTpoCX_A8 Spotify: bit.ly/4h3UJWt Apple: bit.ly/4w0BCAs
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Redpoint retweeted
Today we're releasing Laguna S 2.1, our most capable model to date. It's a 118B total parameter Mixture-of-Experts model with 8B activated per token, a context window of up to 1M tokens, and thinking and no-thinking modes. Capable enough to hold its own against models many times its size. Small enough to run on a single @NVIDIAAI DGX Spark. Laguna S 2.1 is fully open under OpenMDW-1.1, with weights available today on @huggingface poolside.ai/blog/introducing…
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