By Alisher Abdulkhaev Issue #17: November 2020 AlphaFold: a solution to a 50-year-old grand challenge in biology The latest version of AlphaFold (AlphaFold-2) has been recognised as a solution to one of biology's grand challenges - the “protein folding problem”.It was validated at CASP14, the biennial Critical Assessment of protein Structure PredictionWe’re excited about the potential impact … Continue reading AI DIGEST #NOVEMBER20
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KPMG IGNITION TOKYO、MLTとのパートナーシップを締結
KPMG Ignition Tokyoは、オープンエデュケーション、オープンソース、オープンサイエンスを通じた機械学習と人工知能の民主化に取り組む一般社団法人Machine Learning Tokyo とパートナーシップ契約を締結しました。MLTとのパートナーシップを通じて、テクノロジーコミュニティのさらなる成長と発展に貢献することを目指しています。
AI DIGEST #JULY20
What happened in AI, Machine Learning and Deep Learning this month, at a glance.
10 COOL GPT-3 DEMOS
Since OpenAI kicked off the GPT-3 API access for selected users, many demos have been created that showcased the impressive capabilities of the massive-scale language model. Here are 10 cool demos based on GPT-3 that appeared on Twitter.
AI DIGEST #JUNE20
AI, Machine Learning and Deep Learning this month, at a glance.
DLPOTW: DISCOVERING SYMBOLIC MODELS FROM DEEP LEARNING WITH INDUCTIVE BIASES
🚀 DEEP LEARNING PAPER OF THE WEEK Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, Shirley Ho Abstract "We develop a general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases. We focus on Graph Neural Networks (GNNs). The technique works as follows: we first encourage sparse latent representations when we train … Continue reading DLPOTW: DISCOVERING SYMBOLIC MODELS FROM DEEP LEARNING WITH INDUCTIVE BIASES