#56 – Dr. Walid Saba, Gadi Singer, Prof. J. Mark Bishop (Panel discussion)
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: https://anchor.fm/machinelearningstreettalk/episodes/56---Dr--Walid-Saba--Gadi-Singer--Prof--J--Mark-Bishop-Panel-discussion-e145bt0
https://www.linkedin.com/in/gadi-singer/
https://www.linkedin.com/in/walidsaba/
https://www.linkedin.com/in/profjmarkbishop/
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 #artificialintelligence
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: https://anchor.fm/machinelearningstreettalk/episodes/56—Dr–Walid-Saba–Gadi-Singer–Prof–J–Mark-Bishop-Panel-discussion-e145bt0
https://www.linkedin.com/in/gadi-singer/
https://www.linkedin.com/in/walidsaba/
https://www.linkedin.com/in/profjmarkbishop/
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 #artificialintelligence
