I hope their jaw is alright
Here, the video the article is talking about. Save you from reading the author’s life story.
Here is an alternative Piped link(s):
https://piped.video/zQMKfuWZRdA
Piped is a privacy-respecting open-source alternative frontend to YouTube.
I’m open-source; check me out at GitHub.
While the link is useful, the smug takedown is uncalled for. Humans relate way more through personal stories like this. Without the story, the video is not impressive at all, as most will have now idea how difficult this achievement is. There is also something to be said about adding some flourish and passion in the story, instead of coldly presenting facts.
It’s just like those shitty recipe sites that tell you their grandma’s life story for hours before giving the recipe. Get to the point, who cares about the anecdotes of some writer?
I don’t want to connect with everyone always everywhere. It’s just like small talk, which may be acceptable or even essential in some cultures, while considering rude and wasteful where I’m from.
I get that, some people prefer to have some personal story mixed in the article, but personally i’d like to have my time respected, more than 2 paragraphs of that and i’m out. With that bloated life story and a baitest of the clickbait headline, it deserved to be call out.
I didn’t find the story bloated. I found the whole article quite insightful. Not everyone is processing things the same way.
The point of journalism is to get the facts across and inform viewers. I don’t care about the journalist other than them being impartial and reporting on the facts.
Man, you sound like those gamers who complain that game journalisst should only report on the technical specifications of the game.
I’m ASD and I’m also human, gimme the cold hard facts so I can absorb them like I do everything else without having to strip the clutter. Everything else is useless to me.
It’s cool but my question is (I did not see this addressed in the article nor video but might have missed it) did it learn to win the game in general terms or only this one example? I mean, if the layout of the board was changed, would it still solve it?
They don’t discuss it here, but it’s most likely a reinforcement model that operates different generations of learned behavior to decide if it’s improving or not.
It would know that the ball going in the hole is “bad”, and then try to avoid that happening. Each move that is "good’ is then kept in a list of moves it should perform in the next generation of its plan to avoid the “bad” things. Loop -> fail -> logic build -> retry. After 6 hours, it has mapped a complete list of “good” moves to affect it’s final outcome.
The answer your question: no, it would not be able to use what it learned here on a different map of the board. It’s building reactions to events based on this one board, and bound by rules. You could use the ruleset with another board, but it would need to learn it all again just as a human would.
The thing about these models is less that they will work (it is assumed they eventually will through trial and error), but how efficiently they will work. The number of generational cycles and retries is usually the benchmark when dealing with reinforcement, but they don’t discuss that data here either.
Yes, but that’s kind of my point
We see it learn something with insane precision but most often it is almost an effect of over-training. It probably would require less time to learn another layout but it’s not learning the general rules (can’t go through walls, holes are bad, we want to get to X), it learns the specific layout. Each time a layout changes, it would have to re-learn it
It is impressive and enables automation in a lot of areas, but in the end it is still only machine learning, adapting weights to specific scenario
It did learn to use shortcuts to skip parts of the maze, and had to be told not to. Super interesting!
But this sounds exactly the sort of thing that machines are better at that people, so it just feels completely unsurprising that it was good at the task.
Turning multiple dials to manage speed and direction is not normally how humans interact with the world, so we can we pretty shit at it.
A basic motor is completely designed to turn like this.
This feels no different to the machine learning tools used to train on Mario a decade ago.
Right. Computers doing the shit that we don’t want to do for a living while giving us time to do things like paint cows that don’t have two heads.
Speak for yourself, I’m painting a watercolour landscape set in the Fallout universe
Well, your two headed cows are intentional, I hope.
I’d love to see your work btw. I love fallout.
Technology has removed a lot of time consuming or boring jobs, but it also made us spend our time in front of the computers. The idea from the start was that we could live our lives while computers do our tasks. But we ended up on social media or in front of computer games.
It’s great for companies though, since now they make money both when we work and when we are off work. The attention economy is very real.
Not sure if it’s more interesting that an AI taught itself the PID instructions in order to deftly move the ball around, or if it’s more interesting if a human programs the PID instructions to move the ball around. Sounds like a lot of electricity was used doing it the first way.
