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If I didn't read past the concept and the date I would've accepted it as real without a blink of an eye
> We will offer a free (rate-limited) service that everyone can use, once we have sorted out the legal issues regarding the possibility of mixing code snippets originating from open-source projects with different licenses (e.g., GPL-licensed tests will simply refuse to pass BSD-licensed code snippets).

Well, looks like they sorted em out!

We aren't really far off from that, perhaps.
> We once saw a comment in the generated code that said "I need some coffee".
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To put things into perspective: DeepMind was founded in 2010, bought by goog in 2014, the year of this "prank". 11 years later and ... here we are.

Also, a look at how our expectations / goalposts are moving. In 2010, one of the first "presentations" given at Deepmind by Hassabis, had a few slides on AGI (from the movie/documentary "The Thinking Game"):

Quote from Shane Legg: "Our mission was to build an AGI - an artificial general intelligence, and so that means that we need a system which is general - it doesn't learn to do one specific thing. That's really key part of human intelligence, learn to do many many things".

Quote from Hassabis: "So, what is our mission? We summarise it as <Build the world's first general learning machine>. So we always stress the word general and learning here the key things."

And the key slide (that I think cements the difference between what AGI stood for then, vs. now):

AI - one task vs. AGI - many tasks

at human level intelligence.

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I'm pretty sure that if we go by that definition, we're already there. I wish I'd have a magic time traveling machine, to see Legg and Hassabis in front of gemini2.5/o3/whatever top model today, trained on "next token prediction" and performing on so many different levels - gold at IMO, gold at IoI, playing chess, writing code, debugging code, "solving" NLP, etc. I'm curious if they'd think the same.

But having a slow ramp up, seeing small models get bigger, getting to play with gpt2, then gpt3, then chatgpt, I think it has changed our expectations and our views on what is truly AGI. And there's a bit of that famous quote "AI is everything that hasn't been done before"...

They knew the future in 2014 and somehow wasted 10 years
This nowadays sounds more like a product announcement than a joke.

Coding tests (if done correctly) is basically defining the behaviour of a black box API using running code. So it is easy to imagine an AI generating the black box from the tests/behaviour spec.