What we’re about
Machine Learning Tokyo (MLT) is an award-winning nonprofit organization 一般社団法人 based in Japan, operating globally and remotely. MLT is dedicated to democratizing Machine Learning through open education, open source and open science. We support a research- and engineering community of 10,000 members.
Open Education – MLT held more than 300 AI workshops, study sessions, talks and hackathons with thousands of participants in Tokyo and with remote participants from all over the world. Our events are inclusive and with an open education mindset, individuals can attend all events free of charge.
Open Source – Several volunteer teams within the MLT community are working on Machine Learning, Deep Learning, Reinforcement Learning and Robotics projects, including substantial work that has been done in the field of AI for Social Good. All projects are hosted on the public Machine Learning Tokyo GitHub Organization; code bases and repositories are published as open source projects.
Open Science – MLT teams have published research papers at international ML conference workshops and we’re continuously collaborating with Universities and Research Institutes in Japan to support open science and researchers with diverse academic backgrounds, including the University of Tokyo, Tokyo Institute of Technology and RIKEN CBS. We organized lectures, bootcamps and workshops on Machine Learning, Deep Learning and Data Science.
Find more information about MLT:
Website: https://www.mlt.ai/
Twitter: https://twitter.com/MLT
LinkedIn: https://www.linkedin.com/company/mltokyo/
● FIND MLT TALKS & VIDEOS ●
Youtube: https://www.youtube.com/MLTOKYO
● LOOKING FOR A NEW CAREER OPPORTUNITY? ●
Sign up and join the AI Career Network: https://forms.gle/KGz5P7JyhnVQCssv8
● CODE OF CONDUCT
MLT promotes an inclusive environment that values integrity, openness and respect. https://github.com/Machine-Learning-Tokyo/MLT_starterkit
● AI TOOLS WE LOVE & USE (AFFILIATE LINKS)
Upcoming events
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•OnlineShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution
OnlineWe're incredibly excited to welcome Robert Tjarko Lange (Founding Research Scientist at Sakana.AI) for a talk on ShinkaEvolve, a new open-source framework leveraging large language models to advance scientific discovery with state-of-the-art performance and unprecedented efficiency.
ABSTRACT
Recent advances in scaling inference time compute of LLMs have enabled significant progress in generalized scientific discovery. These approaches rely on evolutionary agentic harnesses that leverage LLMs as mutation operators to generate candidate solutions. However, current code evolution methods suffer from critical limitations: they are sample inefficient, requiring thousands of samples to identify effective solutions, and remain closed-source, hindering broad adoption and extension. ShinkaEvolve addresses these limitations, introducing three key innovations: a parent sampling technique balancing exploration and exploitation, code novelty rejection-sampling for efficient search space exploration, and a bandit-based LLM ensemble selection strategy. We evaluate ShinkaEvolve across diverse tasks, demonstrating consistent improvements in sample efficiency and solution quality. ShinkaEvolve discovers a new state-of-the-art circle packing solution using only 150 samples, designs high-performing agentic harnesses for AIME mathematical reasoning tasks, identifies improvements to ALE-Bench competitive programming solutions, and discovers novel mixture-of-expert load balancing loss functions that illuminate the space of optimization strategies. Our results demonstrate that ShinkaEvolve achieves broad applicability with exceptional sample efficiency. Finally, ShinkaEvolve recently was able to support human programmers (team Unagi) in winning the 2025 ICFP Competitive Programming Contest by automatically optimizing SAT solver encodings.
Paper: https://arxiv.org/abs/2509.19349
Blog Post — Release: https://sakana.ai/shinka-evolve/
Blog Post — ICFP 25: https://sakana.ai/icfp-2025/
Code: https://github.com/SakanaAI/ShinkaEvolve
Tweet: https://x.com/SakanaAILabs/status/1971081557210489039
SPEAKER BIO
Rob is a Founding Research Scientist at Sakana.AI. Furthermore, he is a final-year PhD student working on Evolutionary Meta-Learning at the Technical University Berlin. Previously, he completed a MSc in Computing at Imperial College London, a Data Science MSc at Universitat Pompeu Fabra and an Economics undergraduate at University of Cologne. He worked at Google DeepMind with the Tokyo team as a full-time student researcher and interned at Legacy DeepMind (Discovery team) & Accenture and maintains a set of open source tools: evosax (JAX-based Evolution Strategies) and gymnax (JAX-based Reinforcement Learning Environments).
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