Understanding Ourselves in the Age of AI
Churchill College Science Society
bits/min | billions | 2,000 |
billion calculations/s |
~100 | a billion |
embodiment | 20 minutes | 5 billion years |
bits/min | billions | 2,000 |
billion calculations/s |
~100 | a billion |
embodiment | 20 minutes | 5 billion years |
There are three types of lies: lies, damned lies and statistics
??
There are three types of lies: lies, damned lies and statistics
Arthur Balfour 1848-1930
There are three types of lies: lies, damned lies and statistics
Arthur Balfour 1848-1930
There are three types of lies: lies, damned lies and ‘big data’
Neil Lawrence 1972-?
There is a lot of evidence that probabilities aren’t interpretable.
See e.g. Thompson (1989)
LLMs are already being used for robot planning Huang et al. (2023)
Ambiguities are reduced when the machine has had large scale access to human cultural understanding.
Later in the 1940’s, when I was doing my Ph.D. work, there was much talk of the brain as a computer and of the early digital computers that were just making the headlines as “electronic brains.” As an analogue computer man I felt strongly convinced that the brain, whatever it was, was not a digital computer. I didn’t think it was an analogue computer either in the conventional sense.
A human-analogue machine is a machine that has created a feature space that is analagous to the “feature space” our brain uses to reason.
The latest generation of LLMs are exhibiting this charateristic, giving them ability to converse.
But if correctly done, the machine can be appropriately “psychologically represented”
This might allow us to deal with the challenge of intellectual debt where we create machines we cannot explain.
One thing is I can live with is doubt, and uncertainty and not knowing. I think it’s much more interesting to live with not knowing than to have an answer that might be wrong.
Richard P. Feynmann in the The Pleasure of Finding Things Out 1981.
twitter: @lawrennd
podcast: The Talking Machines
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