Inspiring Computing
The Inspiring Computing podcast is where computing meets the real world. This podcast aims to trigger your curiosity by talking to proficient and advanced users of MATLAB, Python, Julia who use these tools to deepen their understanding of the world, simulate, explore trade-offs and gain insights that help companies add more value. In addition to proficient users we will also talk with the product marketing, toolbox authors, package developers and library maintainers to see what drives the development and what issues they are solving for others to benefit from.
Inspiring Computing
Lazy Dynamics - Reactive Bayesian AI - Your Engine for Next Generation AI
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.
