{"id":11561,"date":"2024-06-20T06:27:46","date_gmt":"2024-06-20T06:27:46","guid":{"rendered":"https:\/\/incose.nl\/incose-nl-workshop-2024\/eric-postma\/"},"modified":"2024-06-20T09:25:05","modified_gmt":"2024-06-20T09:25:05","slug":"eric-postma","status":"publish","type":"page","link":"https:\/\/incose.nl\/en\/incose-nl-workshop-2024\/eric-postma\/","title":{"rendered":"Eric Postma"},"content":{"rendered":"
\"INCOSE-NL<\/div><\/div><\/div><\/div><\/div><\/div><\/section>
\"Eric<\/div><\/div>

Eric Postma<\/h2>\n<\/div><\/div>

F<\/span>ull professor Artificial Intelligence<\/span> Tilburg University<\/span><\/span>\u00a0<\/span><\/em><\/p>\n<\/div><\/div><\/div><\/div>

Keynote: The unreasonable effectiveness of overparameterization<\/span><\/span>\u00a0<\/span><\/h2>\n

9:00 – 10:00<\/p>\n<\/div><\/div>

<\/div>

Abstract
\n<\/strong>The recent developments in deep learning and generative AI have led to many breakthroughs across many application domains. <\/span><\/span>In <\/span>the<\/span> presentation<\/span>, a brief review of <\/span>the<\/span> history<\/span> of <\/span>artificial<\/span> intelligence <\/span>will<\/span> be<\/span> followed<\/span> by<\/span> an<\/span> explanation<\/span> of <\/span>the<\/span> basic <\/span>principles<\/span> of <\/span>deep<\/span> learning<\/span> and<\/span> generative<\/span> AI. It <\/span>will<\/span> be<\/span> shown<\/span> how<\/span> a <\/span>departure<\/span> from<\/span> the<\/span> scientific<\/span> adagio <\/span>to<\/span> keep <\/span>models<\/span> as <\/span>simple<\/span> as <\/span>possible<\/span> (<\/span>known<\/span> as “<\/span>Occam’s<\/span> razor<\/span>“) \u202fled<\/span> to<\/span> the<\/span> current<\/span> AI <\/span>revolution<\/span> characterized<\/span> by<\/span> highly<\/span> successful<\/span> neural<\/span> network<\/span> models<\/span> with<\/span> far <\/span>too<\/span> many<\/span> parameters. The <\/span>similarities<\/span> and<\/span> dissimilarities<\/span> of <\/span>artificial<\/span> intelligence <\/span>and<\/span> natural<\/span> intelligence <\/span>will<\/span> be<\/span> outlined<\/span> to<\/span> debunk<\/span> many<\/span> false<\/span> claims <\/span>about<\/span> artificial<\/span> ihtelligence<\/span>. <\/span>Finally<\/span>, <\/span>the<\/span> current<\/span> developments<\/span> will<\/span> be<\/span> described<\/span> in a down-to-earth way <\/span>to<\/span> facilitate<\/span> a hype-<\/span>resistant<\/span> assessment of <\/span>near-future<\/span> developments<\/span>. \u202f<\/span><\/span><\/p>\n

Bio Eric Postma
\n<\/em><\/strong>Eric Postma is a full professor Artificial Intelligence at the Cognitive Science & AI department of Tilburg University and at the <\/span>Jheronimus<\/span> Academy of Data Science in ‘s-Hertogenbosch of Tilburg University and Eindhoven University of Technology. Eric has worked on neural networks throughout his career. His research tries to unravel the pattern recognition abilities of machines by studying the latest neural architectures. He has worked on computer vision and signal processing tasks across many application domains such as visual arts, health, sustainable development goals, astronomy, and human behavior.<\/span><\/em><\/p>\n<\/div><\/div>

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