Having laid to the waste to the Atari Classics, and reached the superhuman performance in the chess and the Chinese board game, GO, Google DeepMind outfit has turned out to be that its Artificial Intelligence on one of the toughest problems in the science.
The result perhaps was so much predictable. AT an international conference in Cancun on Sunday, organizers announced that the DeepMind latest Artificial Intelligence program, AlphaFold had beaten all comers at a particularly fiendish task: predicting the 3D shapes of proteins, the fundamental molecule of life.
The arcane nature of “protein folding,” a mind blogging form of molecular form of molecular origami, is rarely discussed outside scientific circles, but it is a problem of profound the essential. The machinery of biology is built from proteins and it a protein shape defines its function. Understand how proteins fold up, and researchers could usher in a new era of scientific and some of the medical progress.
“For us, this is a really key moment,” said Demis Hassabis, co-founder and CEO of DeepMind. “This is a lighthouse project, our first major investment in terms of people and resources into a fundamental, very important, real-world scientific problem.”
DeepMind set its sights on the protein folding after its AlphaGo program famously beat Lee Sedol, a champion Go Player in 2016. While games have proved to be a good testing ground for the group of Artificial Intelligence programs, highs cores are not their ultimate goal. “It’s never been about cracking Go or Atari, it’s about developing algorithms for problems exactly like protein folding,” Hassabis said.
Liam McGuffin, a researcher at Reading University, led the highest-scoring UK academic group in the competition. “DeepMind appear to have pushed the bar higher this year and I’m intrigued to find out more about their methods,” he said. “We are not as well resourced, but we can still be very competitive.”