Jorge Colindres, cofounder of Radical.ai, says most AI startups waste talent on trivial problems like calendar apps when they should tackle cancer. His team read over 200 research papers on high-entropy alloys and validated hundreds of compositions in months. Their material survived 3,000°C in testing, outperforming materials unchanged since the 1960s.
Chapters
Have you ever felt truly vulnerable as a founder? Every day. Trying to go after a problem as big as the one that Radical.ai is pursuing is one of the most painful endeavors I have ever undertaken. I became frustrated because I believe that machine learning was this incredibly powerful technology. Yet I kept seeing companies doing calendar optimization or better email copy. As I went down the rabbit hole and I started reading research papers, probably read north of 200 research papers because I wanted to get to a root. I turned to my co-founder Joseph, who happened to sit next to me, and said, Why are we not solving cancer with machine learning? Academia validated about 3,500 or so HEA compositions. At Radical, in just the last couple of months, we have validated a few hundred HEA compositions. We don't have a choice. You have an obligation almost at the purest of levels as a human being to try to make an improvement for the rest of humanity. A couple of weeks ago, we did a torch test on one of our materials for 3,000 degrees. We discovered that our materials are actually outperforming industry standard materials that have been around since the '60s.