WIM no. 17 Spring 2020

מכון ויצמן למדע intelligence was previously considered a prerequisite. In the simplest cases, intelligent-like behavior can be achieved by simple a well-defined computer programs. But more challenging tasks require AI systems to gather complex data, reveal patterns, and make independent decisions. Much like the human brain, successful AI systems comprise sensors, experiences, and the ability to process remembered data to make decisions. In AI, sensors are used to gather complex data, for instance, visual images, or, in biomedical applications, genetic and molecular data. Next, the systemmust be exposed to large data sets—for example, in facial recognition, or cancer prediction—for which a solution is already known. Finally, AI must be powered by an algorithm—programming code that enables the computer to discover patterns and make decisions based on the sensors and past experiences. Given these components, and if the tasks for which the AI system is designed have been defined correctly, it will do something quite astonishing: it will learn. Ever-more powerful computers are expected to expand AI capabilities. New algorithmic approaches, such as “deep neural network” techniques inspired by the human brain, will join with emerging multi-sensor systems capable of accumulating data sets of unprecedented size. These developments point toward an exciting future, in which AI will push past the limits of the imagination, and realize its potential as a “thought partner” for its human creators. AI at Weizmann Home to some of the world’s most prominent experts in computer science and neurobiology, Weizmann Institute researchers are developing AI-based methods for everything from drug discovery and personalized medicine, to climate modeling and environmental protection. The application of AI to fields historically considered non- computational—such as archaeology and education—is demonstrating the power of such systems to “flag” significant patterns that, because of their enormous complexity, would be overlooked by even the most brilliant human scientist. Among the many Weizmann investigators who use AI, three of them—Prof. Amos Tanay, Prof. Ilan Koren, and Prof. Eilam Gross— demonstrate how emerging AI tools are helping the scientific community achieve world-changing discoveries. AI and health What could we learn if we had detailed health data, relating to an entire population over decades, at our fingertips? This is what Prof. Amos Tanay—who holds appointments in both the Department of Biological Regulation and the Department of Computer Science and Mathematics— aims to find out. The advent of Electronic Health Records as a replacement for traditional, handwritten medical charts has helped standardize how patient data is recorded, making it easier to share and use clinically important information. Prof. Tanay is taking this to the next level, by developing software for data g Prof. Ilan Koren g Prof. Amos Tanay Science Feature Weizmann MAGAZINE 46–47 S P R I N G 2 0 2 0