The state of AI in 2019

Experts refer to this specific instance of AI as artificial general intelligence, and if we do ever create something like this, it’ll likely to be a long way in the future.

No one is helped by exaggerating the intelligence or capabilities of AI systems.

It’s better to talk about “Machine learning” rather than AI. This is a subfield of artificial intelligence, and one that encompasses pretty much all the methods having the biggest impact on the world right now.

How does machine learning work? Over the past few years, I’ve read and watched dozens of explanations, and the distinction I’ve found most useful is right there in the name: machine learning is all about enabling computers to learn on their own.

Teaching computers to learn for themselves is a brilliant shortcut – and like all shortcuts, it involves cutting corners Teaching computers to learn for themselves is a brilliant shortcut.

There’s intelligence in AI systems, if you want to call it that.

Kai-Fu Lee, a venture capitalist and former AI research, describes the current moment as the “Age of implementation” – one where the technology starts “Spilling out of the lab and into the world.” Benedict Evans, another VC strategist, compares machine learning to relational databases, a type of enterprise software that made fortunes in the ’90s and revolutionized whole industries, but that’s so mundane your eyes probably glazed over just reading those two words.

This article was summarized automatically with AI / Article-Σ ™/ BuildR BOT™.

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