9-dan is the highest rank in Go. It is not possible to play against anyone higher.
So I am not sure why you think it isn't a big deal.
If we came out with a polynomial time solution for the graph coloring problem, you could use that same logic to say "it's just labeling colors, what's the big deal?"
Besides, people who make advances in abstract problems like that do not release PR statements and get 1/1000th of the hype and coverage AlphaGo received recently.
This achievement will be useful in a myriad of obvious applications. And, it is one of the greatest engineering feats that I have been alive to witness.
Have you read the research paper and seen how much of AlphaGo's architecture was designed around the specifics of Go gameplay? (Including a set of handcrafted Go-specific training features.)
[1] According to some comment in /r/MachineLearning the other day. I haven't looked into it myself.
Are you seriously failing to understand the implications.
That's super cool, but no I wouldn't say it's more impressive or groundbreaking than AlphaGo. They're both obviously incredibly impressive though.
I guess I don't get the point you're trying to make. Why does something have to be practical to be impressive? And why don't you think the technology used in AlphaGo is practical?
So in one sense, those machines are unupgradable; you can't upgrade them without violating a number of laws and regulations.
In another sense, they're trivially upgradable; if you don't care about violating laws and regulations, you've got a playground with a number of highly documented vulnerabilities and publicized exploits.
The sorts of people who would install malware on those computers are the sorts of people who aren't really fussed about "laws and regulations"; that's not a position that people running a hospital are really able to take, though.
Also this reminded me of a comment I read last week: "Don't anthropomorphize computers. They hate that"
Let's look at just one sentence:
>We've also had the chance to see something that's never happened before: DeepMind's AlphaGo took on and defeated legendary Go player, Lee Sedol (9-dan professional with 18 world titles), marking a major milestone for artificial intelligence.
Hype-inducers: "never happened before" "legendary" "marking a major milestone"
Also, AlphaGo didn't "take on" anyone. It plays whatever games are fed into it. It might seem insignificant, but such small details is exactly how most of marketing works. That is how we get "ultimate" luxury cars, "curious" banks, and insurance providers that are "always there for you".
>And because the machine learning methods we’ve used in AlphaGo are general purpose, we hope to apply some of these techniques to other challenges in the future.
AlphaGo's design has a lot of stuff highly specific to Go.