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IBM Launches Free AI Tool in the Cloud for Predicting Chemical Reactions


For more than 200 years, the synthesis of organic molecules has remained one of the most important tasks in organic chemistry. The work of chemists has scientific and commercial implications that range from the production of Aspirin to that of Nylon. Yet, little has been done to change age-old practices dramatically and allow a new era of productivity based on pioneering artificial intelligence (AI) science and technologies. The challenge for organic chemists in fields such as chemistry, materials science, oil and gas, and life sciences is that there are hundreds of thousands of reactions and, while it is manageable to remember a few dozen in a narrow specialist's field, it's impossible to be an expert generalist. To address this, we asked ourselves, can we use deep learning and artificial intelligence to predict reactions of organic compounds?

Artificial Intelligence Predicts Outcomes of Chemical Reactions

IEEE Spectrum Robotics

By thinking of atoms as letters and molecules as words, artificial intelligence software from IBM is now employing the same methods computers use to translate languages to predict outcomes of organic chemical reactions, which could speed the development of new drugs.

AI translates chemistry to predict reaction outcomes


IBM researchers have developed a program that can predict the products of organic chemistry reactions.1 Modelled on the latest language translation systems – like Google's artificial neural network – the AI picked the right product 80% of the time despite not having been taught any organic chemistry rules.

IBM's AI learns how to predict the outcomes of chemical reactions


By thinking of atoms as letters and molecules as words an Artificial Intelligence (AI) from IBM is now using the same neural network techniques that other AI's use to translate between different languages to predict the outcomes of organic chemical reactions, and the breakthrough could help speed up the development of new drugs.

Enantioselective C(sp3)-H bond activation by chiral transition metal catalysts


The ultimate goal of synthetic chemistry is the efficient assembly of molecules from readily available starting materials with minimal waste generation. The synthesis of organic molecules--compounds containing multiple carbon-hydrogen (C–H) and carbon-heteroatom (such as oxygen or nitrogen) bonds--has greatly improved our quality of life. Pharmaceuticals that can treat disease, agrochemicals that enhance crop yields, and materials used in computer engineering are but three illustrative examples. And yet more often than not, the syntheses of these substances have proved challenging because of restrictions on how molecules can be constructed.