29.3700, Confs: Cognitive Science/France

[The LINGUIST List]

LINGUIST List: Vol-29-3700. Wed Sep 26 2018. ISSN: 1069 - 4875.

Subject: 29.3700, Confs: Cognitive Science/France

Moderator: linguist at linguistlist.org (Malgorzata E. Cavar)
Reviews: reviews at linguistlist.org (Helen Aristar-Dry, Robert Coté)
Homepage: https://linguistlist.org

Please support the LL editors and operation with a donation at:
           https://funddrive.linguistlist.org/donate/

Editor for this issue: Everett Green <everett at linguistlist.org>
================================================================


Date: Wed, 26 Sep 2018 03:07:46
From: Tobias Scheer [scheer at unice.fr]
Subject: Artificial Intelligence and Cognition

 
Artificial Intelligence and Cognition 

Date: 08-Nov-2018 - 08-Nov-2018 
Location: Nice (Sophia Antipolis), France 
Contact: Tobias Scheer 
Contact Email: scheer at unice.fr 
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?
 






------------------------------------------------------------------------------

*****************    LINGUIST List Support    *****************
Please support the LL editors and operation with a donation at:

              The IU Foundation Crowd Funding site:
       https://iufoundation.fundly.com/the-linguist-list

               The LINGUIST List FundDrive Page:
            https://funddrive.linguistlist.org/donate/
 


----------------------------------------------------------
LINGUIST List: Vol-29-3700	
----------------------------------------------------------