Today we are joined by Karim Beguir, Co-Founder and CEO of InstaDeep, a company in Tunisia, Africa focusing on building advanced decision-making systems for the enterprise. In this episode, we discuss where his and InstaDeep’s journey began in Tunisia, Africa (00:27), the challenges that enterprise companies are seeing in logistics that can be solved by deep learning and machine learning (05:43), how InstaDeep is applying DL and RL to real world problems (09:45), and what are the data sets used to train these models and the application of transfer learning between similar data sets (13:00). Additionally, we go over ‘Rank Rewards’, a paper Karim published last year, in which adversarial self-play in two-player games has delivered impressive results when used with reinforcement learning algorithms (22:40), the overall efficiency of RL for logistical problems (23:05), and details on the InstaDeep process (35:37). The complete show notes for this episode can be found at twimlai.com/talk/302.