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We're excited to turn our focus to Machine Learning in production environments with a workshop by Adam Gibson, Co-Founder and CTO of Skymind, a SF/Tokyo-based AI Startup specialized in production-level Machine Learning and Deep Learning for industry. This workshop covered the first steps of deploying machine learning models to production, with a strong focus on … Continue reading WORKSHOP: MACHINE LEARNING IN PRODUCTION
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
Machine Learning Tokyo, the Digital Nature Group at the University of Tsukuba and ON-1 Tokyo are organizing a Deep Perception 2-day Hackathon to combine Deep Learning with interactive AR/VR/MR environments. The goal is to explore both fields and find novel ways of synthesis and interaction. We'll have teams of 3-5 people with different technical and … Continue reading DEEP PERCEPTION HACKATHON
150 people joined us for our Women in Machine Learning event on August 10 at Mercari. This event was organized in collaboration with Women Who Code Tokyo, a local chapter of the global nonprofit Women Who Code, an initiative that is supporting women to excel in tech careers. We heard two fantastic talks by Shreya … Continue reading WOMEN IN MACHINE LEARNING
Recently scientists at Elon Musk's Neuralink presented their impressive work on Brain-Machine-Interfaces. (Read the white paper) There are many labs and research groups all over the world working on Neural Interfaces. One of those labs is at UPCT Span. On July 31 we welcomed Antonio Lozano for a talk at ELSI. With a group of … Continue reading BRAIN-MACHINE INTERFACES, TALK & DISCUSSION
We finally kicked off our MLT Reinforcement Learning sessions with an "Intro to RL" study group at the Tokyo Metropolitan Library. Anugraha Sinha walked us through the following: Theory Introduction to RL Important elements of an RL problem Description of Markov Decision Process (MDP) and and Markov Assumption. Importance of parametrization of State, Action, Reward … Continue reading INTRO TO REINFORCEMENT LEARNING