AI Startup Humans& Raises $480 Million in Seed Funding, Valuing Company at $4.48 Billion
Humans&, a nascent startup advocating for AI’s role in empowering human collaboration rather than replacing it, has successfully secured $480 million in seed funding, achieving a valuation of $4.48 billion, according to The New York Times. Key investors in this significant round include renowned chipmaker Nvidia, Amazon founder Jeff Bezos, and prominent venture capital firms such as SV Angel, Google Ventures, and Emerson Collective, led by Laurene Powell Jobs.
This notable funding comes just three months after the company’s inception, reflecting a growing trend of heavy investment in startups that emerge from leading AI research labs. Among Humans&’s founders are notable industry figures like Andi Peng, a former researcher at Anthropic, who played a pivotal role in the development of reinforcement learning for the advanced Claude 3.5 through 4.5 models; Georges Harik, Google’s seventh employee instrumental in creating its original advertising systems; and Yuchen He along with Eric Zelikman, ex-researchers from xAI involved in the Grok chatbot’s development. Additionally, Noah Goodman, a distinguished professor in psychology and computer science at Stanford, contributes to the team’s diverse expertise.
The startup’s workforce, comprised of around 20 employees, includes talent from esteemed organizations such as OpenAI, Meta, Reflection, AI2, and MIT. Humans& aims to pioneer innovative software solutions that facilitate enhanced human collaboration, envisioning an AI-driven platform similar to an instant messaging app.
Their ambition extends beyond current capabilities as they propose to employ novel AI training methods, such as enabling chatbots to effectively solicit and retain information from users. Through their vision of AI serving as a fundamental connective tissue for organizations and communities, Humans& seeks to transform the paradigms of model training and human-AI interaction. The startup underscores the necessity for advancements in long-term, multi-agent reinforcement learning, memory retention, and user comprehension, with a strong focus on integrating scientific principles into product development.
