Economy & Markets
6 min read
Humans& AI Startup Secures $480M Seed Funding for Human-Centric AI
TechCrunch
January 20, 2026•2 days ago

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Humans&, a new AI startup focused on human empowerment, has secured $480 million in seed funding. The company, founded by former researchers from Anthropic, xAI, and Google, aims to develop AI that enhances collaboration. Key investors include Nvidia and Jeff Bezos. The substantial funding highlights investor confidence in AI startups founded by experienced professionals.
Humans&, a startup with a philosophy that AI should empower people rather than replace them, has raised $480 million in seed funding at a $4.48 billion valuation, reports The New York Times. Investors in the round include chipmaker Nvidia, Amazon founder Jeff Bezos, and VC firms SV Angel, Google Ventures, and Laurene Powell Jobs’ firm Emerson Collective.
The megadeal for the three-month-old company follows a trend of investors throwing money at startups founded by breakaways of major AI labs. Humans&’s founders include Andi Peng, a former Anthropic researcher who worked on reinforcement learning and post-training of Claude 3.5 through 4.5; Georges Harik, Google’s seventh employee, who helped build its first advertising systems; Eric Zelikman and Yuchen He, two former xAI researchers who helped develop the Grok chatbot; and Noah Goodman, a Stanford professor of psychology and computer science.
Humans&’s 20-odd employees also come from OpenAI, Meta, Reflection, AI2, and MIT, according to the company. The startup aims to use software to help people collaborate with each other — think an AI version of an instant messaging app. One of their goals is to use existing AI techniques to train AI in new ways, like programming chatbots to request information from the user and store it for later use.
In order to build AI that serves “as a deeper connective tissue that strengthens organizations and communities,” Humans& hopes to rethink “how we train models at scale and how people interact with AI,” per the company’s web page. The startup cited a need for innovations in “long-horizon and multi-agent reinforcement learning, memory, and user understanding,” as well as a tightly integrated focus on both science and product development.
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