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1) RXNMapper: Unsupervised attention-guided atom-mapping Explore the attentions of a Transformer model that has learned to solve the NP hard problem of how atoms rearrange in chemical reactions on its own, with no supervision or human guidance.

2) AI Explainability 360 (AIX360) AIX360 is an open-source Python toolkit for explaining data and machine learning models in diverse and state-of-the-art ways to address the needs of different stakeholders. This demo provides a glimpse of its capabilities, algorithms, and industry domains.

3) Command Line AI (CLAI) Explore and interact with the future of the Command Line with CLAI - Command Line AI. CLAI is an open-source project from IBM Research that brings the latest in AI and ML technologies to the command line as “skills”, and seeks to make the command line user’s daily life more efficient and productive.

4) COVID-19 Molecule Explorer The traditional drug discovery pipeline is time and cost intensive. To deal with new viral outbreaks and epidemics, such as COVID-19, we need more rapid drug discovery processes. We have developed robust generative frameworks that can overcome the inherent challenges to create novel peptides, proteins, drug candidates, and materials. We are working with several partners on validating the AI-generated molecules by using in-silico simulations and wet lab experiments, and will include those validation results into the exploration tool as they arrive.

Presenters: Ben Hoover, Hendrik Strobelt, Teodoro Laino, Vijay Arya, Amit Dhurandhar, Tathagata Chakraborti, Kartik Talamadupula, Mayank Agarwal, Payel Das, Enara Vijil

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