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116 - Harvesting randomness, HAIbrid algorithms and safe AI with Dr. Siddhartha Sen

116 - Harvesting randomness, HAIbrid algorithms and safe AI with Dr. Siddhartha Sen

In this podcast episode, Dr. Siddhartha Sen, a Principal Researcher at Microsoft's New York City lab, discusses his research interests which include optimal decision-making, universal data structures, and verifiably safe AI. Using reinforcement learning and HAIbrid algorithms, Dr. Sen aims to develop AI that is both minimally disruptive and synergistic with human solutions.

The concept of HAIbrid algorithms brings together the best of both human and machine intelligence, enabling AI to work in harmony with human solutions. Dr. Sen believes that this approach will lead to the development of safer AI with fewer errors.

Throughout the podcast, Dr. Sen highlights the importance of verifiably safe AI. He emphasizes that AI systems must be built with safety in mind to prevent unintended consequences that could harm individuals or society as a whole.

If you're interested in the future of AI and how it can be designed to work in harmony with humans, this podcast is a must-listen.

The podcast episode, "116 - Harvesting Randomness, HAIbrid Algorithms and Safe AI with Dr. Siddhartha Sen," is available on Spotify.

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Microsoft Research Podcast
Microsoft Research Podcast

An ongoing series of conversations bringing you right up to the cutting edge of Microsoft Research.

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