Inception, an artificial intelligence startup founded by Stanford professor Stefano Ermon, has raised $50 million in seed funding to develop a new generation of large language models built on diffusion technology.
The round was led by Menlo Ventures with participation from Microsoft’s M12, NVentures (Nvidia’s venture arm), Snowflake Ventures, Databricks Investment, and Mayfield. Angel investors Andrew Ng and Andrej Karpathy also joined the round. Inception’s goal is to create diffusion-based models for text, code, and voice generation, offering faster and more efficient performance than existing systems.
Ermon, known for his research on probabilistic modeling and generative systems, is taking diffusion models beyond image generation into the domains of text, code, and voice. Inception claims that its models can produce over 1,000 tokens per second, offering significantly faster generation than conventional systems. “These diffusion-based LLMs are much faster and much more efficient than what everybody else is building today,” Ermon said.
