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A new generative ai approach to predicting chemical reactions system developed at mit could provide realistic predictions for a wide variety of reactions, while maintaining real. Hundreds of scientists, business leaders, faculty, and students shared the latest research and discussed the potential future course of generative ai advancements during the. Using generative ai algorithms, the research team designed more than 36 million possible compounds and computationally screened them for antimicrobial properties
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Mit researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability Mit researchers develop ai tool to improve flu vaccine strain selection vaxseer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection. “in this environment, learning deeply and building real expertise is.
The new ai approach uses graphs based on methods inspired by category theory as a central mechanism to understand symbolic relationships in science
