River AI, a startup co-founded by Igor Babuschkin, a former AI researcher at DeepMind and OpenAI, has raised $1.1 billion in a seed/Series A funding round led by General Catalyst and AMP PBC. The round also included participation from Nvidia, AMD Ventures, Y Combinator, and Temasek. The funding comes as the company emerged from stealth mode in June with a vision to rebuild AI from the ground up, focusing on training models and creating personalized assistants.
Babuschkin aims to shift the focus of AI development from replacing human workers to creating agents that are trained by individuals and work on their behalf. He envisions a future where agents are like personal assistants, deeply integrated into users' lives and tailored to their needs. River’s first product is an API that allows developers to use reinforcement learning and low-rank adaptation fine-tuning on open models, offering a way to train models that are truly owned by users. The API is billed per 1 million tokens, with rates depending on the open model used.
The funding round highlights the growing interest in AI startups that offer alternatives to closed-source models, as enterprises seek greater control over their AI systems. River’s neocloud offering promises to enable complex reinforcement learning runs in 15 to 20 minutes without requiring an infrastructure team, at two to four times the cost savings compared to closed-source alternatives. While the company’s long-term vision remains to be realized, the substantial funding provides a strong foundation for its ambitions.
Source: techcrunch
