Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.

Greptile has raised a $50M Series B led by Menlo Ventures. The round values the company at $750M. Greptile reviews and tests more than 1% of all PRs opened on GitHub every day. Thousands of engineering teams including Nvidia, Coinbase, Decagon, and Vanta use Greptile as their independent and central validation layer. Fewer than 50 people, we are a small, talent-dense team of engineers and researchers in a quiet corner of San Francisco. If you’re interested in joining us, we’d love to hear from you.

Three weeks until Deepgram Speak. On October 29, 500 developers, researchers, and technical leaders are coming together in San Francisco to build, test, and push voice AI forward. Hear from leaders across @ToastTab, @cresta, @Qualcomm, @LangChain, @doximity, @covaldev, @twilio, and @Vapi_AI on what it takes to build voice AI for the real world, from latency and interruptions to multilingual agents, contact centers, and production scale. And so you can put it all into practice, everyone who registers with a business email and attends will get $500 in Deepgram credits. 📍 San Francisco 🗓️ October 29 🎟️ Free to attend. Only 500 seats. Register today: deepgram.com/speak

Robotics has a distribution problem. Today, Ultra is announcing $62M in funding to solve it, including a $50M Series A led by @hiFramework. We believe that deployment is the bottleneck in robotics. It’s relatively easy to make a robot look impressive in a controlled environment. It’s much harder to put a robot into the open world, make it useful, keep it running, earn the trust of the people working alongside it, and do that over and over and over again. So that’s what we’re focusing on.

At scale, failures are routine. Losing the work has been routine too. Not anymore. LinkedIn runs Clockwork.io in production. Together.ai is bringing TorchPass to its GPU cluster customers. SemiAnalysis measured the payback: goodput loss cut from 14% to under 3%. Today we're launching an industry first, in preview: TorchPass Snapshots in addition to Asynchronous Application checkpoints. And announcing $31M in new funding. 🔹 TorchPass Snapshots: save a whole running training job, across every node, with no code changes. Free the GPUs now. Resume later. Nothing lost. Platform teams stop waiting for application owners to add checkpointing. 🔹 Async Application Checkpoints: checkpoint while you train, not instead of training. Save more often, lose less when something breaks, and get fresh weights to Reinforcement Learning rollouts sooner. Our AI fault tolerance is already proven in production: ✅ LinkedIn runs Clockwork.io LinkPass across its AI infrastructure fleet. "In aggregate, Clockwork.io prevents tens of thousands of GPU-hours of downtime per month across our fleet." Raghu Hiremagalur, SVP, CTO Infrastructure, LinkedIn. ✅ @togethercompute is bringing TorchPass to market as a service on its GPU Clusters. "Our customers grade us on goodput, the share of their GPU-hours that actually move the model forward." Pavneet Singh Ahluwalia Ahluwalia, Product Lead, Together.ai ✅ WhiteFiber is expanding Clockwork.io across its global GPU footprint. "We bring clusters up faster, and a customer's first training run lands on a fabric validated end-to-end, not just powered on." Tom Sanfilippo, CTO, WhiteFiber. Quantifiable payback: "In our ClusterMAX, TorchPass cuts training goodput loss from 14% to under 3% for a gold-rated neocloud." Dylan Patel, @SemiAnalysis_ , @dylan522p. More than 11 points of GPU capacity back, measured independently. New funding: $31M with @PremjiInvest, @Wing_VC, Seligman Ventures, New Enterprise Associates (@NEA), @etisalatandae Pressure tested at scale with some of the world’s largest enterprises, neoclouds and hyperscalers. The job never stops. Stop paying for job restarts. Preview access opens today, and we'll kill a GPU and a link live at PyTorch Conference with Together.ai. Schedule a demo and preview access in the first comment 👇 #AIInfrastructure #FaultTolerance #DistributedTraining #GPU #PyTorch