Anthropic has launched a scientific AI initiative aimed at supporting researchers working on "high-impact" scientific projects, with a particular focus on applications in biology and life sciences.

The program, announced on Monday, will provide "eligible" researchers with up to $20,000 worth of Anthropic API credits over a six-month period. Researchers will be selected based on their contributions to science, the potential impact of their proposed research, and the ability of AI to accelerate their work. Awardees will gain access to Anthropic's standard suite of AI models, including all publicly available models from the Claude series.

"Advanced AI reasoning and language capabilities can assist researchers in analyzing complex scientific data, generating hypotheses, designing experiments, and communicating research findings more effectively," Anthropic wrote in a blog post. "We are particularly interested in supporting AI applications that accelerate the understanding of complex biological systems, analyze genetic data, expedite drug discovery (especially for diseases with a high global burden), and enhance agricultural productivity."

Anthropic is one of several AI companies optimistic about the role of AI in science. Earlier this year, Google introduced an "AI Co-Scientist," which the tech giant claims can help scientists formulate hypotheses and research plans. Anthropic, along with its main competitor OpenAI and companies like FutureHouse and Lilia Sciences, asserts that AI tools can significantly speed up scientific discoveries, especially in the medical field.

However, many researchers remain skeptical about the current utility of AI in guiding the scientific process, primarily due to its unreliability.

One of the challenges in developing an "AI scientist" lies in accounting for countless confounding factors. While AI may prove useful in areas requiring extensive exploration, such as narrowing down a vast range of possibilities, it remains unclear whether it can achieve the kind of innovative problem-solving that leads to groundbreaking discoveries.

To date, the outcomes of AI systems designed for scientific purposes have been largely disappointing. In 2023, Google reported that its AI, GNoME, helped synthesize around 40 new materials. However, external analysis revealed that none of the synthesized materials were actually novel.

Undoubtedly, Anthropic hopes its efforts will yield better results than previous attempts.