For context, Go is a board game previously thought to require too much human intuition for a computer to succeed in, and as a result, it was a North Star for AI. Centuries ago, scientists and doctors operated largely in the dark when attempting to cure diseases and had to rely solely on their intuition. Many current and past approaches in the field relied on a single researcher or academic group's intuition for prioritizing which genes to test edit. Recently, with advances in high-throughput single-cell CRISPR sequencing methods, we are nearing the possibility of simply testing all genes simultaneously on equal footing and in various experimental scenarios. In fact, we predict that in the next 10 years, we will have an equivalent of a Move 37 against cancer: a therapy that at first may seem counterintuitive (and at which human intuition alone would not arrive) but that in the end, shocks us all and wins the game for patients.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. For context, Go is a board game previously thought to require too much human intuition for a computer to succeed in, and as a result, it was a North Star for AI. For years, researchers tried and failed to create an AI system that could beat humans in the game. In 2016, AlphaGo, an AI system created by Google's DeepMind, not only beat its champion human counterpart (Lee Sedol); it demonstrated that machines could find playing strategies that no human would come up with. AlphaGo shocked the world when it performed its unimaginable move #37.

A cure for cancer has been brought one step closer after scientists used artificial intelligence to develop a new technique that can predict how the disease can evolve – and therefore intervene earlier before a patient's cancer becomes drug resistant. The technique, known as Revolver (Repeated evolution of cancer), picks out patterns in DNA mutation within cancers and uses the information to forecast future genetic changes. It could help doctors design the most effective treatment for each patient and boost their chances of survival. The research team, led by the Institute of Cancer Research London (ICR) and the University of Edinburgh, also found a link between certain sequences of repeated tumour mutations and survival outcome. This suggests that repeating patterns of DNA mutations could be used as an indicator of prognosis, helping to shape future treatment.

Nancy Brinker is a cancer advocate, a global consultant and founder of Susan G. Komen. Her opinions expressed in this article are her own. Elad Gil, Ph.D. is the chairman and co-founder of Color Genomics. The complexity of seeking a cure for cancer has vexed researchers for decades. While they've made remarkable progress, they are still waging a battle uphill as cancer remains one of the leading causes of death worldwide.