FutureHouse, a nonprofit backed by former Google CEO Eric Schmidt, has launched a new AI tool called Finch designed to aid scientific research in biology. The announcement follows closely on the heels of FutureHouse releasing its broader AI science platform and API. With a long-term goal of building an “AI scientist” within the next decade, Finch represents the nonprofit’s first major step toward AI-driven scientific discovery.
Finch works by processing biological research data—mostly academic papers—and using a user prompt to run code, generate visuals, and interpret findings. For instance, users might ask, “What are the molecular drivers of cancer metastasis?” and receive data-backed visual results and explanations. Sam Rodriques, FutureHouse co-founder and CEO, described Finch as being like a “first-year grad student” with an impressive speed advantage.
“Being able to do all of this in minutes is a superpower,” Rodriques wrote on X (formerly Twitter). “For our own internal projects, we’ve found Finch to be pretty awesome.”
AI’s Role in Scientific Research: Promise and Pitfalls
Finch is part of a growing effort to use artificial intelligence to automate scientific processes, including drug discovery, genetic analysis, and disease modeling. This ambition is shared by major players in AI, such as OpenAI and Anthropic, who are increasingly investing in science-focused initiatives. Sam Altman of OpenAI has predicted that superintelligent AI could revolutionize discovery, while Anthropic recently launched its own “AI for science” initiative.
However, many researchers remain skeptical. While the potential is immense, the reality so far has been mixed. Finch itself is still in closed beta testing, and Rodriques admits the tool makes “silly mistakes.” To refine its performance, FutureHouse is hiring bioinformaticians and computational biologists who can help assess Finch’s accuracy and contribute to its training.
Despite high expectations, no groundbreaking discoveries have yet been attributed to FutureHouse’s tools. In fact, the broader AI-for-science space has seen some notable setbacks. Drug discovery firms like Exscientia and BenevolentAI, which rely heavily on AI models, have experienced clinical trial failures, and even DeepMind’s much-lauded AlphaFold 3 has faced scrutiny over inconsistent accuracy.
High Stakes in a Growing Market
Still, the stakes and rewards in this sector are high. According to Precedence Research, the global AI in biology market was valued at $65.88 billion in 2024 and is projected to hit $160.31 billion by 2034. This growing market continues to attract innovators hoping to use AI to speed up the often painstaking process of scientific discovery.
Finch is FutureHouse’s attempt to bridge that gap. While it’s far from perfect, the company believes it marks a key step toward the long-term vision of automating scientific insight. Whether that promise will turn into measurable breakthroughs remains to be seen—but Finch is now in the hands of early testers and poised to shape what comes next.
