Years of Upheaval.
One amino acid.
1. Henry Kissinger (1923-2023):
Leaders who have not had an experience of catastrophe or the edge of catastrophe sometimes believe that they have more options than they really do. That is characteristic of our time. (Source: bloomberg.com)
2. The world’s largest collection of full human genomes has just gone live. The UK Biobank — a repository of health, genomic and other biological data — today released complete genome sequences from every one of the 500,000 British volunteers in the database. Researchers around the world can apply for access to the data, which lack identifiable details, and use them to probe the genetic basis for health and disease. “Scientists are looking at this like Google Maps,” Rory Collins, the UK Biobank’s chief executive, said at a press briefing. “When they want to know what are the pathways from lifestyle, environment, genetics to disease, they don’t go Google, they go to UK Biobank.” (Source: nature.com)
3. Google DeepMind:
Modern technologies from computer chips and batteries to solar panels rely on inorganic crystals. To enable new technologies, crystals must be stable otherwise they can decompose, and behind each new, stable crystal can be months of painstaking experimentation.
Today, in a paper published in Nature, we share the discovery of 2.2 million new crystals – equivalent to nearly 800 years’ worth of knowledge. We introduce Graph Networks for Materials Exploration (GNoME), our new deep learning tool that dramatically increases the speed and efficiency of discovery by predicting the stability of new materials.
With GNoME, we’ve multiplied the number of technologically viable materials known to humanity. Of its 2.2 million predictions, 380,000 are the most stable, making them promising candidates for experimental synthesis. Among these candidates are materials that have the potential to develop future transformative technologies ranging from superconductors, powering supercomputers, and next-generation batteries to boost the efficiency of electric vehicles.
GNoME shows the potential of using AI to discover and develop new materials at scale. External researchers in labs around the world have independently created 736 of these new structures experimentally in concurrent work. In partnership with Google DeepMind, a team of researchers at the Lawrence Berkeley National Laboratory has also published a second paper in Nature that shows how our AI predictions can be leveraged for autonomous material synthesis. (Sources: deepmind.google, nature.com)