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
Free annotation tools for Deep Learning, Computer Vision and Natural Language Processing tasks.
Deep Learning paper of the week.
We created a small repository linking to open Deep Learning and Reinforcement Learning lectures provided by MIT, Stanford University and UC Berkeley. ⚪ MIT 6.S191: Introduction to Deep Learning | 2020⚪ CS231n: CNNs for Visual Recognition, Stanford | Spring 2019⚪ CS224n: NLP with Deep Learning, Stanford | Winter 2019⚪ CS285: Deep Reinforcement Learning, UC Berkeley | … Continue reading AI CURRICULUM
MLT is presenting 2 workshop papers at the NeurIPS 2019 conference in Vancouver, Canada. Meet Asir Saeed at the poster session at the NeurIPS Workshop Machine Learning for Creativity and Design. Creative GANs for generating poems, lyrics, and metaphors Asir Saeed, Suzana Ilić, Eva Zangerle Generative models for text have substantially contributed to tasks like machine translation … Continue reading MLT AT NEURIPS 2019 IN VANCOUVER
Keith Stevens (Google Japan) gave an insightful talk about Neural Machine Translation at Google, from Sequence to Sequence Models to Transformers and Hybrids, and an excellent overview of the latest research. He also presented a sample of unsolved problems: Pushing the limits of model size Working with non-ideal data Translating on the fly Using models … Continue reading TALK: GOOGLE TRANSLATE