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Paul McCartney on playing guitar with Paul Mescal: 'He knew it better than I did!'

BBC News

Paul McCartney on playing guitar with Paul Mescal: 'He knew it better than I did!' Hey, I know you! exclaims Paul McCartney, gripping my hand as we walk into his office in central London. And while I'm realistic enough to know he doesn't really hold treasured memories of our previous encounters, I'm impressed by his ability to defuse the tension of Meeting A Beatle. We gather in Soho at lunchtime. Instead of Wild Honey Pie or Savoy Truffle, McCartney has opted for a simple bagel (topping: a terrifying blend of Marmite and hummus), which he prepared in a kitchenette next to his assistant's desk. As he eats, he scans a printed list of film titles - mainly vintage comedies - looking for something to play at his family movie night.


Why is "Learning" so Misunderstood?

#artificialintelligence

I have written a few posts where I make the point that most of the important knowledge that is needed to build intelligent agents is not learned --because it cannot be learned differently, and it cannot be susceptible for incremental, approximate and individual learning from observations. I have written about this topic first in "Learning is Overrated: Machine Learning vs. Knowledge Acquisition" where I discuss the difference between "knowing how" and "knowing that". Recently, I wrote a post where I explain "Why Commonsense Knowledge is not (and can not be) Learned". In comments and (mostly private) messages I keep getting remarks like "but why can't that be learned?" It seems that the'folk' meaning of learning has taken over even the most rational of people that the techncial point I'm trying to get across is still not appreciated.


Implant lets paralysed man 'play guitar'

BBC News

In a world first, a quadriplegic man can once again move his fingers after a chip was implanted in his brain. Ian Burkhart from Ohio in the US can even move individual fingers to play a guitar-based computer game. The chip reads brain signals, which are interpreted by a computer. It then precisely stimulates his muscles with electricity to restore movement. The researchers hope the technology will eventually help millions of people with paralysis, stroke or brain damage.