Shelly Fan in Singularity Hub:
Uncovering nature’s secrets is no easy task. The daily life of a scientist is often grueling, frustrating, and—perhaps surprisingly—boring as they repeat experiments over and over. Here’s where AI could lend a hand. This week, two studies offer a glimpse into a future where AI and scientists bounce ideas off each other and collaborate on projects to benefit humanity. Both systems rely on large language models in end-to-end scientific discovery. They read through existing literature, generate hypotheses, suggest relevant experiments, and analyze and interpret the data for scientists to evaluate. The researchers then give the AI feedback, and the cycle begins again.
One of the systems, called Robin, was instructed to find drugs for a common eye condition. Developed by FutureHouse, a non-profit that builds AI systems to automate research in biology and other scientific fields, Robin quickly homed in on candidates. According to the team, the AI slashed research time 200-fold compared to scientists working alone. The other system is Google DeepMind’s Co-Scientist. With human guidance, Co-Scientist found already approved drugs that could be repurposed for a type of leukemia within hours. It also surfaced promising targets for liver scarring.
More here.
Enjoying the content on 3QD? Help keep us going by donating now.