October 21, 2024 (Hyeonji Time) – In a recent interview released by Sam Altman, the CEO of OpenAI, he predicted that machine‑learning‑based models will bring a revolution to new drug and material discovery. “Machine‑learning‑based models can be applied in biology and materials science just as existing mathematical problem‑solving methods,” he emphasized, stating that this technology is expected to play a major role in finding disease‑treatment candidates.
His assertion about research and development stems from the fact that using complex mathematical models increases the likelihood of discovering new drugs and materials. “When machine‑learning‑based models combine biological data with computational resources, we can quickly identify candidate molecules or novel therapies for treating diseases,” he explained. He also noted that bringing a drug to market requires further steps such as FDA review in the United States, acknowledging that even after a discovery there is room for improvement.
Altman said that when these scientific achievements are publicized, some basic science knowledge should become publicly available worldwide. “As the model’s power improves, it will be possible to discover new materials based on abundant computational resources and real‑world data,” he projected, stressing that researchers and scientists must use machine‑learning‑based models for their work.
Finally, he added that “Machine‑learning‑based models can solve hard problems while also enabling people to achieve some sense of accomplishment” and that finding a disease‑treatment method would mean more than spending another few decades on existing approaches, hoping for new research methods and breakthroughs. Such outlook appears to illuminate the potential of machine‑learning‑based models for both scientists and industry alike.