Avery Haskell

Generalist is an AI robotics company building general intelligence for the physical world and making it useful to everyone. The founding team includes engineers from OpenAI, Google DeepMind, and Boston Dynamics. The company embraces both large-scale AI and robotics as core to its DNA.

AI for humans

Were building the worlds most automated AI lab. Our objective is to build systems that optimize and automate work, starting with research itself. We dont think the next step change in AI will come from scaling the current recipe: larger models, more data, static deployment. Were pursuing new learning algorithms that supersede large-scale pretraining and reinforcement learning, and architectures that scale better than transformers. — We think the next wave of frontier research will come from small teams with highly capable agents. Were building the lab around that bet from day one. We start by automating our own work. That makes room for more ambitious and creative work, which reveals the next thing to automate. What we learn feeds back into the research. — If were right, small teams with powerful AI systems will take on work that once required entire organizations. Much of the current conversation around AI assumes it will mostly help existing institutions operate more efficiently. Were excited by the larger shift: a world where far more people can pursue ambitious work without first building an organization or raising capital. A corner store with the logistical capabilities of a multinational corporation. A small workshop with demand from around the world. A project that starts in a group chat and grows far beyond its origins. Were building the research, systems, and operating model to make this possible for more people. — Our team brings together people who have helped build frontier models, state-of-the-art optimization methods, influential architectures, multimodal agents, and the low-level systems those advances depend on. Were building a small lab with the range to rethink neural network architecture from scratch – the kind of bet that gets harder to make the more you have to scale – and the systems engineering depth to prove it out.

Varda is building the infrastructure for a thriving orbital economy, from in-orbit pharmaceutical processing to reliable and economical reentry capsules. From new, life-saving pharmaceuticals to more powerful fiber optic cables, there is a world of products used to benefit life on Earth that can only be manufactured in space. Our mission is to expand the economic bounds of humankind.

True Anomaly is the only defense technology company focused exclusively on space defense. Founded in 2022 by ex-U.S. Space Force members, True Anomaly designs and builds advanced systems for space superiority: agile and powerful spacecraft platforms, mission software engineered for unmatched command and control, and payloads tailored for precision sensing and effects. We are headquartered in Centennial, Colorado, with regional offices in Colorado Springs, Colorado, Long Beach, California, and Washington, D.C. We are hiring and seeking exceptional talent to join True Anomaly, from any technical industry or background, to bring unique talents, perspective, and solutions. If you embrace complexity, demonstrate relentless ownership, have the resiliency and persistence to overcome challenges. If you’re like us and want your work to carry purpose and shape the future of space, visit www.WhyAreYouHere.com.

TransAstra is developing game-changing technologies in the areas of orbital logistics and space resources to enable massive growth to existing and entirely new space industries. These resources include water and other valuable materials to be found on asteroids and lunar poles. We lead the world in cislunar supply chain solutions to service commercial satellite manufacturers, space-tech makers, and the rapidly evolving space tourism market.

Early stage VC firm investing in disruptive web3 and blockchain technology companies.

DHVC, a venture capital firm based in Palo Alto, California

Generalist is an AI robotics company building general intelligence for the physical world and making it useful to everyone. The founding team includes engineers from OpenAI, Google DeepMind, and Boston Dynamics. The company embraces both large-scale AI and robotics as core to its DNA.

AI for humans

Were building the worlds most automated AI lab. Our objective is to build systems that optimize and automate work, starting with research itself. We dont think the next step change in AI will come from scaling the current recipe: larger models, more data, static deployment. Were pursuing new learning algorithms that supersede large-scale pretraining and reinforcement learning, and architectures that scale better than transformers. — We think the next wave of frontier research will come from small teams with highly capable agents. Were building the lab around that bet from day one. We start by automating our own work. That makes room for more ambitious and creative work, which reveals the next thing to automate. What we learn feeds back into the research. — If were right, small teams with powerful AI systems will take on work that once required entire organizations. Much of the current conversation around AI assumes it will mostly help existing institutions operate more efficiently. Were excited by the larger shift: a world where far more people can pursue ambitious work without first building an organization or raising capital. A corner store with the logistical capabilities of a multinational corporation. A small workshop with demand from around the world. A project that starts in a group chat and grows far beyond its origins. Were building the research, systems, and operating model to make this possible for more people. — Our team brings together people who have helped build frontier models, state-of-the-art optimization methods, influential architectures, multimodal agents, and the low-level systems those advances depend on. Were building a small lab with the range to rethink neural network architecture from scratch – the kind of bet that gets harder to make the more you have to scale – and the systems engineering depth to prove it out.