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Lazy Dynamics - Reactive Bayesian AI - Your Engine for Next Generation AI

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Manage episode 416223734 series 3435244
Content provided by Gareth Thomas. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Gareth Thomas or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, Albert recounts his journey from Nakhodka Russia to the CEO of a Dutch company Lazy Dynamics. He describes his academic trajectory from studying in St. Petersburg. To earning scholarship and master programs in Kyoto, Japan. There he focused on , developing driving aids for elderly drivers, but face challenges with system performances, leading him to pursue a PhD in Bayesian Inference. Albert explains Bayesian inference as a method for updating beliefs, about uncertain quantities based on new evidence. He discusses its applications and addressing uncertainty in complex systems like personalized. Just hearing it, the conversation touches on the differences between patient AI and reinforcement learning, I'll but also introduces RxInfer and for an open source toolbox programmed in Julia designed to automate Bayesian Inference through reactive message passing. He emphasizes RxInfer and its efficiency in handling computational resources by processing information only when necessary.

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17 episodes

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Manage episode 416223734 series 3435244
Content provided by Gareth Thomas. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Gareth Thomas or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, Albert recounts his journey from Nakhodka Russia to the CEO of a Dutch company Lazy Dynamics. He describes his academic trajectory from studying in St. Petersburg. To earning scholarship and master programs in Kyoto, Japan. There he focused on , developing driving aids for elderly drivers, but face challenges with system performances, leading him to pursue a PhD in Bayesian Inference. Albert explains Bayesian inference as a method for updating beliefs, about uncertain quantities based on new evidence. He discusses its applications and addressing uncertainty in complex systems like personalized. Just hearing it, the conversation touches on the differences between patient AI and reinforcement learning, I'll but also introduces RxInfer and for an open source toolbox programmed in Julia designed to automate Bayesian Inference through reactive message passing. He emphasizes RxInfer and its efficiency in handling computational resources by processing information only when necessary.

Support the Show.

Subscribe to mailing list here.

  continue reading

17 episodes

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