AI Conference

Discussion of anything and everything relating to chess playing software and machines.

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chrisw
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Full name: Christopher Whittington

AI Conference

Post by chrisw »

Quite a lineup of famous names, day one focuses partly on intersection AI models and neuroscience, which I guess is relevant to some at least in computer chess.

You can get at some of the content free, via YouTube, X et al, so buying a ticket to attend is not compulsory!

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mclane
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Re: AI Conference

Post by mclane »

Dr James Whittington
Chief Scientific Officer & Research Scientist

Thinking About Thinking

Stanford & Oxford

?
What seems like a fairy tale today may be reality tomorrow.
Here we have a fairy tale of the day after tomorrow....
chrisw
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Re: AI Conference

Post by chrisw »

mclane wrote: Wed Oct 15, 2025 6:59 am Dr James Whittington
Chief Scientific Officer & Research Scientist

Thinking About Thinking

Stanford & Oxford

?
We don’t do personal. You should know that.
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Ras
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Re: AI Conference

Post by Ras »

chrisw wrote: Wed Oct 15, 2025 10:59 amWe don’t do personal. You should know that.
What's personal? That's one of those who present at the summit? And the info comes from the website itself, so it's public.
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Peter Berger
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Re: AI Conference

Post by Peter Berger »

Ras wrote: Wed Oct 15, 2025 2:06 pm
chrisw wrote: Wed Oct 15, 2025 10:59 amWe don’t do personal. You should know that.
What's personal? That's one of those who present at the summit? And the info comes from the website itself, so it's public.
This thread may actually be a good example on what this Mr Whittington ( not ours) thinks the human mind does with what he calls "sparse data" compared to current AIs :).
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towforce
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Re: AI Conference

Post by towforce »

Peter Berger wrote: Fri Oct 17, 2025 4:49 pmThis thread may actually be a good example on what this Mr Whittington ( not ours) thinks the human mind does with what he calls "sparse data" compared to current AIs :).

Sparse Networks: not all neurons in one layer are connected to all the neurons in the next layer. Many neurons in layer 1 are not connected to many of the neurons in layer 2. The advantage of this is that computing costs are reduced. No idea how much of this there is in the human brain - sorry.

Sparse Data: most of the data is missing. Example - you're a doctor, and patient John Doe walks in complaining of dizziness. There are 100 tests you could do - but you just take his blood pressure. In your mind, he would then be "John Doe with dizziness and low blood pressure", not "John Doe with dizziness and low blood pressure and no information about..." [each of the items 2 to 100 on the test list mentioned separately]
Human chess is partly about tactics and strategy, but mostly about memory