Today we are joined by Karim Beguir, Co-Founder and CEO of InstaDeep.
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InstaDeep, based in Tunisia, Africa, is focused on building advanced decision-making systems for the enterprise. Karim’s goal is to show that advanced AI and Deep Learning is taking place in Africa, solving real-world problems and building a new generation of talent in the AI industry. With offices around the world, InstaDeep works with large companies in multiple industries with this episode focusing on logistical challenges, like ride-sharing and container shipping. These problems require decision-making in complex environments with a large number of choices.
Appropriately, this is where deep reinforcement learning comes into play. Discussing the InstaDeep process and mindset, Karim explains where they get their data sets, the efficiency of DRL for these types of problems, his take on heuristic vs learnability approaches and how explainability fits into the model. Full of relevant examples, research publications, and books on the subject, this episode doesn’t disappoint.
From the Interview
- Paper: Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization
- Thinking, Fast and Slow by Daniel Kahneman
- Game Changer: AlphaZero’s Groundbreaking Chess Strategies and the Promise of AI
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“More On That Later” by Lee Rosevere licensed under CC By 4.0