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Presentation . 2024
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2024
License: CC BY
Data sources: Datacite
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Phase transitions - A Forrest Gump-like account on AI 1984-2024 - Valedictory lecture - March 8th, 2024 - Lambert Schomaker

Authors: Schomaker, Lambert;

Phase transitions - A Forrest Gump-like account on AI 1984-2024 - Valedictory lecture - March 8th, 2024 - Lambert Schomaker

Abstract

Valedictory lecture of prof. dr. Lambert Schomaker, in the Doopsgezinde Kerk, Groningen, on March 8th, 2024. Video recording with English subtitles, accompanying slides as Powerpoint and PDF file. Afternoon program (presentations by colleagues and PhD students were in the morning session). 00:00:00 Opening by prof. Raffaella Carloni00:00:36 prof. Niels Taatgen, director of the Bernoulli Institute and colleague in the AI department [Liber Amicorum]00:04:56 prof. Rineke Verbrugge, colleague in the AI department [Academy Plaque]00:09:11 Valedictory lecture by prof. Lambert Schomaker Phase transitions - A Forrest Gump-like account on AI 1984-2024 00:09:24 Slide #2 00:10:16 Slide #4 Electronics & Cybernetics00:11:19 Slide #5 VAX/VMS, Fortran, Lisp, Margaret Boden, Grey Walter, Carlo de Luca (machines, AI,brain)00:13:49 Slide #7 Symbolic AI00:14:38 Slide #8 EU Esprit projects on handwriting recognition, failures of symbolic paradigm00:16:10 Slide #9 Rumelhart & McClelland00:17:07 Slide #10 Elman already did it (neural language model)00:19:17 Slide #11 Dissertation: recurrent and spiking NNs00:21:29 Slide #12 Yann LeCun/Montreal00:24:05 Slide #13 Isabelle Guyon/SVMs00:26:19 Slide #14 Neural network winter00:27:24 Slide #15 Administration00:30:01 Slide #16 HMM ==> LSTM, Demise of HMMs ('a scientific urban legend')00:33:07 Slide #18 Divergence in HMM training00:35:16 Slide #19 LSTM ==> Transformers00:35:53 Slide #20 PhD students, overview00:36:42 Slide #2100:37:00 Slide #22 Current PhD students00:37:43 Slide #23 Hinge00:38:24 Slide #25 DeepOtsu00:38:33 Slide #26 BiNet, Isaiah Scrolls00:38:48 Slide #27 Curriculum learning in reinforcement learning00:40:22 Slide #28 Generative Adversarial Networks00:45:58 Slide #31 Latest LLM: Claude 3 by Anthropic00:48:50 Slide #33 HAICu (digital humanities) and CogniGron (neuromorphic computing)00:51:11 Slide #3400:53:01 Slide #35 Valuation of the current state in brains00:54:39 Slide #36 the most dangerous creature around will be the human00:55:46 Slide #37 When will AI be dangerous?00:57:17 Slide #38 AI (RL) helping to control nuclear fusion00:58:27 Slide #40 Words of thanks01:06:44 End

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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