Tokyo Tech - A curated list of startup and technology events around Tokyo

by Shane Reustle

Tokyo Tech

A curated list of startup and technology events around Tokyo

Thu, May 8th
[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materials

[ai alliance materials] matexpert, a generative ai agent for inorganic materials **external registration** https://44725920.hs-sites.com/ai-alliance-material-chemistry-webinar-51-0 ——— **matexpert: decomposing materials discovery by mimicking human experts** for accelerated inorganic materials design, a framework capable of ai-driven exploration of the vast materials spaces across the periodic table is required. in this talk, i will introduce matagent, a generative ai agent for inorganic materials design mimicking the reasoning process of human experts. it combines tool-assisted llm-driven reasoning for material composition proposals with a generative model for crystal structure estimation and a predictive model for material property prediction, enabling feedback-driven targeted materials generation in an interpretable manner. **speaker** qianggang ding, currently completing my ph.d. in computer science at the university of montreal and mila, with a focus on topics of ai for science. **research publication** [https://arxiv.org/abs/2410.21317](https://arxiv.org/abs/2410.21317) **about the ai alliance** the [ai alliance](https://thealliance.ai) is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the ai technology landscape to accelerate progress, improve safety, security and trust in ai, and maximize benefits to people and society everywhere. members of the ai alliance believe that open innovation is essential to develop and achieve safe and responsible ai that benefit society rather than benefit a select few big players.

14:00

Data, Cloud and AI in Tokyo
[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale

[ai alliance] gneissweb: preparing high quality data for llms at scale **details** ibm recently released gneissweb, a large dataset yielding around 10 trillion tokens that caters to the data quality and quantity requirements of training large language models. in this talk i will do a deep dive on the philosophy behind this dataset, where it stands w.r.t the other datasets out there, how to recreate it based on the tools ibm has open sourced and some performance figures with it. this talk will be a followup of the talk given by shahrokh daijavad of ibm in the month of march. **prerequisites** this is a follow up to our march 6, 2025 session “introducing gneissweb - a state-of-the-art llm pre-training dataset“: * check the [github show notes](https://github.com/the-ai-alliance/community/blob/main/events/office-hours/2025-03-06__gneissweb.md) * re-watch on [youtube](https://www.youtube.com/watch?v=o3bocouv5hs&list=plx3ipy60uz16yyajzvdoufjnjv3mu3rmy&index=2) **about the presenter** bishwaranjan bhattacharjee ([linkedin](https://www.linkedin.com/in/bishwaranjan-bhattacharjee-7460855)), senior technical staff member and master inventor, ibm research **about the ai alliance** the [ai alliance](https://thealliance.ai) is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the ai technology landscape to accelerate progress, improve safety, security and trust in ai, and maximize benefits to people and society everywhere. members of the ai alliance believe that open innovation is essential to develop and achieve safe and responsible ai that benefit society rather than benefit a select few big players.

16:00

Data, Cloud and AI in Tokyo

Fri, May 30th
Tokyo Fail Club #03

tokyo fail club #03 tokyo fail club #03

09:30

Tokyo Fail Club