TL;DR
- Nous Research raised $50 million in a Series A round led by Paradigm, valuing its unreleased token at $1 billion.
- The startup uses Solana to coordinate global computing resources, powering open and decentralized AI models.
- It plans to launch the Psyche network, a Solana-based infrastructure for collaboratively training censorship-resistant language models.
Nous Research has secured a $50 million investment in a Series A round led by venture capital firm Paradigm, reaching a $1 billion valuation for its yet-to-be-released token. The financial backing will be used to strengthen its computing infrastructure and expand its research team.
Founded in 2022 by a group of artificial intelligence researchers, Nous Research focuses on developing open-source language models through a decentralized network. It uses the Solana blockchain to coordinate distributed computing resources globally, allowing users to contribute their idle processing power in exchange for tokenized incentives. This strategy aims to democratize AI model training, moving away from costly centralized data centers.
The Nous team has developed the Hermes model series, which has earned recognition within the open-source community. Additionally, they have collaborated with Diederik P. Kingma, co-founder of OpenAI, on research into distributed language model training using non-colocated GPUs.
Paradigm’s Largest AI Bet
Paradigm, known for its investments in the crypto industry, considers this funding round its largest bet in the field of artificial intelligence since the collapse of FTX in 2022. The firm aims to explore the intersection of blockchain and AI, emphasizing the potential of open, decentralized models over the closed solutions of traditional AI labs.
Nous Research Prepares the Launch of the Psyche Network
With this investment, Nous Research plans to launch the Psyche network on Solana, an open infrastructure that connects diverse GPU hardware to collaboratively train censorship-resistant, fault-tolerant models.
This approach offers an alternative to cloud-based AI systems, promoting transparency and energy efficiency in artificial intelligence development.
