Say "robotics research" and most people picture someone in a lab — a whiteboard, a benchmark, a paper. Far from the reality of a hotel laundry room, a restaurant kitchen, or a factory floor. That's not how we think about it at Dyna. We build general-purpose robots, and our mission is to bring embodied AI out of the lab and into the real world — every real world, not just one. Which means research that never meets an actual physical environment isn't finished. It's a hypothesis. So we don't treat foundation research and applied research as two separate tracks. They're one loop: what we build in the lab shapes what we try in the field, and what breaks in the field — the failures, the drift, the corrections — is what actually tells us if the model generalizes. Ask anyone who has actually shipped a physical product as a commercial company — phones, drones, automotive, semiconductors — and they'll tell you: you can't defer the reckoning between the lab and the field. A robot doesn't get a grace period — gravity, clutter, and wear don't show up in a training curve, they show up as a failure at a customer site, on day one. Pull lab and field apart and you get a model that's great on a benchmark and fragile everywhere it actually needs to work. We're hiring for both halves of that loop: → Research Engineer / Scientist — architects the frontier: robot learning algorithms (RL, imitation learning, diffusion), VLA and WAM models, and generative video architectures, owned end-to-end from research to real hardware. → Applied Researcher, Deployment Intelligence & Continuous Learning — lives inside deployment: continuous learning from live fleet data, RL from real-world feedback, fleet-wide monitoring, and closing generalization gaps as we roll out to new sites. Multiple roles open. If you'd rather build the system that keeps getting better after it ships than polish an ablation table, we want to talk. #Robotics# #EmbodiedAI# #AppliedResearch# #Hiring#

This latest investment in California’s shipbuilding industry will help: • Strengthen maritime innovation  • Expand workforce development  • Support applied research  • Prepare students and workers for careers in shipbuilding, maritime manufacturing, engineering, and emerging technologies.

The Learning Loop in SF on September 2nd: Hear from: - Jake Broekhuizen, Labs Engineer, LangChain - Will Brown, Head of Applied Research, @PrimeIntellect - Charlie O'Neill, Co-Head of Model Training, @baseten for an evening exploring continual learning, what it means to own your own intelligence, and how to build systems that learn and improve over time. After the talks, we’ll head to the patio where you can meet the LangSmith Engine team, enjoy food, drinks, slot car racing, an AI photo booth, and more. Spots are limited.

i'm not satoshi, but I was early in laser focus on the positive societal implications of cryptography, online privacy and electronic cash, hence my ~1992 onwards active interest in applied research on ecash, privacy tech on cypherpunks list which led to hashcash and other ideas.

We sat down with the team at @elise_ai to talk about why they're betting on specialized, post-trained models, how to evaluate them, and what it takes to run them in production. We're doing round two at SF Tech Week on October 7th. @oneill_c, our Co-Head of Training, is doing a fireside chat with Mario Martone, who leads applied research at EliseAI, on fine-tuning and continuous retraining for housing and healthcare. Join us for drinks and Mario Kart afterward! RSVP here: