It has been over three decades since the statistical revolution overtook AI by a storm and over two decades since deep learning (DL) helped usher the latest resurgence of artificial intelligence (AI). However, the disappointing progress in conversational agents, NLU, and self-driving cars, has made it clear that progress has not lived up to the promise of these empirical and data-driven methods. DARPA has suggested that it is time for a third wave in AI, one that would be characterized by hybrid models – models that combine knowledge-based approaches with data-driven machine learning techniques. Joining us on this panel discussion is polymath and linguist Walid Saba – Co-founder ONTOLOGIK.AI, Gadi Singer – VP & Director, Cognitive Computing Research, Intel Labs and J. Mark Bishop – Professor of Cognitive Computing (Emeritus), Goldsmiths, University of London and Scientific Adviser to FACT360. Moderated by Dr. Keith Duggar and Dr. Tim Scarfe Pod version:—Dr–Walid-Saba–Gadi-Singer–Prof–J–Mark-Bishop-Panel-discussion-e145bt0 Introduction [00:00:00] Bishop Intro: [00:03:09] Gadi Intro [00:05:06] Walid Intro [00:06:37] Gadi Opening Statement [00:08:30] Bishop opening statement [00:12:21] Walid Opening Statement [00:16:08] Round Robin Kickoff [00:18:49] Self-supervised categories as vectors [00:25:57] The context of understanding electric sheep? [00:28:12] Most unique human knowledge is not learnable [00:37:16] Two modes of learning: by observation and by deduction [00:41:09] Hybrid directions [00:46:24] Monte Carlo tree search and discrete overlays [00:51:44] What’s missing from artificial neural networks? [00:54:40] Closing Statement: Bishop [01:02:45] Closing Statement: Gadi [01:06:09] Closing Statement: Walid [01:08:48] Rapid Round: When will we have AGI? [01:10:55] #machinelearning [More]