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AI Startup Humans& Raises $480M Seed at $4.48B Valuation, Backed by Nvidia and Jeff Bezos



By admin | Jan 20, 2026 | 2 min read


AI Startup Humans& Raises $480M Seed at $4.48B Valuation, Backed by Nvidia and Jeff Bezos

Humans&, a new company built on the belief that artificial intelligence should enhance human capabilities rather than displace them, has secured $480 million in seed financing, achieving a valuation of $4.48 billion. The investment round attracted notable backers such as chip manufacturer Nvidia, Amazon founder Jeff Bezos, and venture capital firms SV Angel, Google Ventures, and Emerson Collective, founded by Laurene Powell Jobs.

This substantial funding for a firm just three months old reflects a broader pattern of investors eagerly supporting startups launched by former members of leading AI research labs. The founding team at Humans& includes Andi Peng, previously a researcher at Anthropic where she focused on reinforcement learning and the post-training phases for models like Claude 3.5 through 4.5; Georges Harik, an early Google employee instrumental in developing its inaugural advertising systems; former xAI researchers Eric Zelikman and Yuchen He, who contributed to the creation of the Grok chatbot; and Noah Goodman, a professor specializing in psychology and computer science at Stanford.

The startup’s approximately 20 employees also bring experience from prominent organizations including OpenAI, Meta, Reflection, AI2, and MIT. Humans& is developing software designed to facilitate human collaboration, envisioning a platform akin to an AI-powered instant messaging application. A key objective involves applying established AI methodologies in novel ways to train systems, such as programming chatbots to proactively ask users for information and retain that data for future interactions.

Aligned with its mission to create AI that acts as “a deeper connective tissue that strengthens organizations and communities,” the company aims to fundamentally reconsider “how we train models at scale and how people interact with AI.” To achieve this, Humans& has identified a pressing need for breakthroughs in areas like “long-horizon and multi-agent reinforcement learning, memory, and user understanding,” emphasizing a closely integrated approach that combines scientific research with product development.




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