AI applications will change the world as we know it. AI apps are some of the fastest growing apps in history. AI Infrastructure is currently cost prohibitive. While much value in AI may flow to incumbents due to data concentration, we believe there is opportunity to disrupt them. Just as the infrastructure of the dotcom era was displaced by open source software and commodity hardware, AI infrastructure will be replaced and improved.
Seed
2022
Vast.ai is a cloud computing, matchmaking, and aggregation service focused on lowering the price of compute-intensive workloads. Vast.ai allows anyone to easily become a host by renting out their hardware and allows users to quickly find the best deals for compute according to their specific requirements. Airbnb for GPU.
Seed
2022
Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.
Seed
2022
Distributed provable compute.
Seed
2023
NEBRA aims to revolutionize Ethereum by launching a proof aggregation service with their Universal ZK-ZK Proof Aggregation technique, targeting scalability and cost reduction in zero-knowledge proof (ZKP) verification. This initiative seeks to enhance blockchain efficiency by supporting various applications and facilitating ZKP composition from multiple parties, aligning with their vision of improving blockchain coordination for societal benefit.
Seed
2023
LayerLens is developing Atlas, an on-demand, no-code tool designed to benchmark and evaluate foundational AI models. Currently in private beta, Atlas aims to assist data scientists, engineers, and founders in selecting appropriate generative AI models for specific use cases. The platform supports over 200 generative AI models and more than 50 evaluation datasets across various categories. Evaluations are conducted without manual code execution or library management, with results displayed on a comprehensive leaderboard. LayerLens also plans to introduce use-case-specific evaluations and an enterprise experience for integrating proprietary datasets and private models.