Mei Z.

Customers rely on Modal for instant GPU access, sub-second container starts, and native storage, so its simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. Every era of computing came with new workloads that previous infrastructure couldnt serve: mainframes, databases, the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice. The window to build is open right now.

The helpful home robot company

Phinity gives AI the training grounds it needs to master the engineering skills that reshape civilization. We distill expert engineering workflows into RL environments, focusing on the engineering disciplines across hardware, AI, mechanics, and manufacturing.

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.

Mesa is the fastest way to review, debug, optimize, maintain, and ship enterprise software as a large team.

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.

Research lab and product company building the platform for continual learning.

OBSESSIVE GRINDERS WANTED! For a high-stakes mission: low pay, high equity, long hours, relentless effort, uncharted path, extreme difficulty. Save lives, shape history, and attain honor and recognition in case of success. missionaries@conquestlabs.com

HealthLeaps AI screening platform supports clinicians in identifying, treating, and billing patients who are often missed by manual tools.

AI for humans

Noah is building the essential payment infrastructure for seamless global money movement via stablecoin. Its platform offers accessible API, low-code, and no-code integrations for a wide range of use cases and enterprise clients. Noah is dedicated to revolutionising international money transfers and catalysing the widespread adoption of stablecoins.

AGI, Inc. is building the next interface for computing.

We build safe, steerable physics foundation models to understand, predict, and shape weather conditions.

Customers rely on Modal for instant GPU access, sub-second container starts, and native storage, so its simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. Every era of computing came with new workloads that previous infrastructure couldnt serve: mainframes, databases, the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice. The window to build is open right now.

The helpful home robot company

Phinity gives AI the training grounds it needs to master the engineering skills that reshape civilization. We distill expert engineering workflows into RL environments, focusing on the engineering disciplines across hardware, AI, mechanics, and manufacturing.

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.