🚀 @SBERLOGASCI webinar on mathematics and data science: 👨‍🔬 Sergei Gukov "What makes math problems hard for reinforcement learning: a case study" ⌚️ 19 September, Thursday 19.00 Moscow time Add to Google Calendar Can AI solve hard and interesting research-level math problems? While there is no mathematical definition of what makes a mathematical problem hard or interesting, we can provisionally define such problems as those that are well known to an average professional mathematician and have remained open for N years. The larger the value of N, the harder the problem. Using examples from combinatorial group theory and low-dimensional topology, in this talk I will explain that solving such hard long-standing math problems holds enormous potential for AI algorithm development, providing a natural path toward Artificial General Intelligence (AGI). The talk is based on a recent paper: https://arxiv.org/abs/2408.15332 О докладчике: Сергей Гуков - профессор КалТех, выпускник МФТИ и Принстона, один из наиболее известных специалистов по теории струн и математической физике, в последние годы занимающийся применением методов Reinforcement Leaning к задачам математики и физики. Zoom link will be in @sberlogabig just before start. Video records: https://www.youtube.com/c/SciBerloga and in telegram: https://t.center/sberlogasci/19688 - subscribe ! Анонс на твиттер: https://x.com/sberloga/status/1835702457260765359 Ваши лайки и репосты - очень welcome !