LINGUIST List 29.3700

Wed Sep 26 2018

Confs: Cognitive Science/France

Editor for this issue: Everett Green <everettlinguistlist.org>


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Date: 24-Sep-2018
From: Tobias Scheer <scheerunice.fr>
Subject: Artificial Intelligence and Cognition
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Artificial Intelligence and Cognition

Date: 08-Nov-2018 - 08-Nov-2018
Location: Nice (Sophia Antipolis), France
Contact: Tobias Scheer
Contact Email: < click here to access email >
Meeting URL: http://sophia-summit.fr/sophia2018/en#modals-10

Linguistic Field(s): Cognitive Science

Meeting Description:

Artificial Neural Networks – artefacts or natural objects in the guise of a machine?

There will be a conference on Artificial Intelligence in Nice / France (or more specifically in Sophia Antipolis next to Nice) on November 6-8, called SophIA: http://sophia-summit.fr/sophia2018/en#.W6jG6cSYTDd
The academic venue (there are also sessions directed to general and corporate audiences) falls into a number of thematic sessions: AI & Vision, AI & Health, AI & Society, AI & Economy, AI & Education etc. One of these sessions will be on AI & Cognition (organized by me).

AI & Cognition
http://sophia-summit.fr/sophia2018/en#modals-10
Registration on this page.

8 November 2:00 pm - 5:00 pm

Speakers:

1. Paul Smolensky (Johns Hopkins), cognitive science, linguistics
2. José Luis Bermúdez (U Texas A&M), philosophy of mind
3. Xavier Vasques (IBM France), neuroscience, computer science

The issue addressed is this:

Artificial neural networks – artefacts or natural objects in the guise of a machine?

In the mid-1980s, connectionism introduced the idea of a more ''brain-style'' computation into Cognitive Science. As a result, artificial neural networks implemented in machines tried to reproduce certain properties known from the workings of biological neurons, namely connection weight and activation threshold. Today, what is called Artificial Intelligence and especially Deep Learning are based on this architecture and have produced spectacular results offering a wide array of applications.

The purpose of this session is to assess to what extent exactly the promise of bio-inspired technology has been fulfilled :

- are current machines running efficiency-hunting artefacts that have sacrificed the mimicking of biological workings, or are they still on the biological track?
- what direction is being taken by the next generation of machines that are currently being made in research labs? Are they only after output-oriented efficiency, or is increased bio-inspiration a promise for the future, even if this comes at the cost of losing efficiency?
- what (if anything) does ''brain-style'' computation tell us about the (human) cognitive system? Is what was advertised as being ''brain-style'' truly close to how computation works in the brain? And in any case do we expect the workings of the cognitive system to be in any way similar or identical to what the brain does? If not, how and where exactly do the brain and the mind meet?





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