A talk by Peter Cochrane from University of Hertfordshire.
This session covers Quantifying AI and What Comes Next!
It should be no surprise that AI is treading a similar path to computing which began with single purpose machines tasked for payroll calculations, banking transactions, or weapons targeting et al, but nothing more! It took decades for General Purpose Computing to emerge in the form of the now ubiquitous PC. Today, AI is still in single purpose/task specific phase, and we have no general purpose platforms, but there emergence is only a matter of time! Recent AI progress has seen a repeat of the media debate and alarmist warnings for our computing past, compounded by consequential advances in robotics. In turn, this has promoted numerous attempts to draw biological equivalences defining the time when machines will overtake humans. But without any workable definitions or framework these tend to little more than un/educated guesses. Recourse to IQ measures and the Touring test have proved to be irrelevant, and without a reference framework or formal characterisation, continued discussion and debate remains futile We therefore approach this AI problem from the bottom up by defining the simplest of machines and lifeforms to derive clues, pointers and basic boundary conditions . This sees a fundamental Entropic description emerge that is applicable to both machine and lifeforms. This presentation is suitable for professionals and public alike, and comes fully illustrated by high quality graphics, animations and movies. Inevitably, it contains some mathematical that non-practitioners will have to take on trust, but the focus is on defining the key characteristics, parameters, and important features of AI, our total dependence, and the future!
Technical Level: Introductory level/students (some technical knowledge needed)
This session was part of the Data Science Festival MayDay event 2024. Find out more at datasciencefestival.com/event...
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