Of course AlphaGo has bugs and imperfect evaluation. It loses against itself. And once in awhile, a human player may create a board position that will reveal one of the bugs. Of course, to reach that position without making any mistakes yourself is incredibly hard. If you let GM Nakamura play 20 games against Stockfish, he may exploit a bug/weakness once, and get crushed the other 19 times simply because he never gets a setup that leads to one of the weaknesses before he makes a mistake himself.
It is a huge dynamic neural net being fed data from multiple humans.
No, this new 'Master' version of AlphaGo was initially trained with the self-play data from the previous version, and then enhanced by further play against itself. There was very little human input.
f you want to understand the issue, you need to understand the difference between weak and strong AI.
I know the difference, but weak AI still has an "I" in it. Intelligence is a broad and fuzzy concept, with many different elements. The computer can now capture some of these elements, just like a chicken or a dog can capture some, and in a growing number of cases, the computer can do it better than us. Obviously, we're not even close to making a computer that can capture the full range, but I don't believe there's a fundamental gap, just like there's no fundamental gap between a chicken and a human brain.
AlphaGo is provably inferior to human intellect (the brief proof is that it's not a Turing machine). It is incapable of self-introspection: it will never understand that it was playing Go. It doesn't know who Ke Jie is, it doesn't even know what a Go board looks like.
Of course not. It was never trained for that. It was trained for recognizing and judging Go patterns. The part of the brain of a human Go player that is responsible for a similar task also don't have self-introspection. That's a responsibility of a different part of the brain.
And human brains aren't Turing machines either. We can't even do trivial problems like factorization of million digit numbers.
AlphaGo has encapsulated knowledge about good and bad Go positions, and can apply that knowledge, not only in identical situations, but also in completely novel situations that resemble similar patterns.
Can you point me to a book that can apply the knowledge contained in it ?
Intelligence according to a dictionary definition is "the ability to acquire and apply knowledge and skills". Surely the machine is doing that, and so are Chess computers.
But Go is not anywhere near that point
Right now, it's already beyond the point where it can beat any human. And we've only just started. It's already stronger than Deep Blue was when it beat Kasparov. People also cried when IBM retired Deep Blue, but by today's standards, Deep Blue is a mediocre program. The same will happen with Go.
Indeed. In chess we haven't had any serious man/machine matches since 2006 where Deep Fritz defeated GM Kramnik 4-2. And in the year before that, Hydra beat GM Michael Adams 5.5-0.5. Modern versions of Stockfish and Komodo would wipe the floor with these old programs, and would totally humiliate any human grandmaster.
DeepMind's approach to Go is still relatively immature, and others will surely adopt and improve their ideas and develop even stronger machines.
I don't think Ke Jie has the balls to do it again. It would be utterly pointless too, because the AI will keep improving much quicker than human players.
“I feel like his game is more and more like the ‘Go god’. Really, it is brilliant,” he said. Ke vowed never again to subject himself to the “horrible experience”.
...I don't think it has much real-world worry. If you're running an intentionally malicious program on your computer, you've got far worse problems. A SSD is one device. A single credit card number is worth thousands of dollars to you and possibly dozens of hours of your valuable time to fix.
What if you're running a virtual instance on a cloud platform, and somebody else is running another virtual instance on the same platform, sharing the same physical memory and SSD ?
Why make an exception for women ? Why don't the non-assertive men get a raise too ?
But if your policy of "give anyone a raise if and only if they ask for one" results in systematically different pay for equally qualified men and women, you are breaking the law.
If you are only giving raises to men who ask for it, and you give them to all women, to keep the averages the same, you are discriminating the non-assertive men based on their gender, which is illegal.
we generally do not have a problem learning technical skills or performing jobs with objective requirements, and those tend to be the jobs that pay well.
And Aspergers is about 4 times more common in men than in women....
If you're systematically paying equally skilled and qualified people in the same role different amounts which correlate with gender then you are doing something illegal.
Wrong. The law, assuming that you're talking about the Equal Pay Act of 1963, forbids a discrimination based on gender. It doesn't say anything about correlation. So, if there's a correlation between gender and skill, you may discriminate based on skill, and end up with a correlation between salary and gender.
I think that pretty much says YES, they must do the governments bidding. At least in this instance.
They still have the right to argue that they've already complied with the law, or that further demands are overly burdensome. They may be wrong, in which case their objections will be overruled, but that doesn't mean they shouldn't try.
Slashdot Mirror
Which results in losses of hundreds of millions of dollars for companies. Over and over.
The solution is simple then. Start a company, hire a bunch of old folks, and become a billionaire.
They'll double check the rivets this time.
He has a secret plan to collect it at night.
You must not be familiar with the search space that Go has, compared to the processing speed of computers.
AES-256 is also a set of rules. Are you surprised that computers can't break it ?
Of course AlphaGo has bugs and imperfect evaluation. It loses against itself. And once in awhile, a human player may create a board position that will reveal one of the bugs. Of course, to reach that position without making any mistakes yourself is incredibly hard. If you let GM Nakamura play 20 games against Stockfish, he may exploit a bug/weakness once, and get crushed the other 19 times simply because he never gets a setup that leads to one of the weaknesses before he makes a mistake himself.
It is a huge dynamic neural net being fed data from multiple humans.
No, this new 'Master' version of AlphaGo was initially trained with the self-play data from the previous version, and then enhanced by further play against itself. There was very little human input.
f you want to understand the issue, you need to understand the difference between weak and strong AI.
I know the difference, but weak AI still has an "I" in it. Intelligence is a broad and fuzzy concept, with many different elements. The computer can now capture some of these elements, just like a chicken or a dog can capture some, and in a growing number of cases, the computer can do it better than us. Obviously, we're not even close to making a computer that can capture the full range, but I don't believe there's a fundamental gap, just like there's no fundamental gap between a chicken and a human brain.
AlphaGo is provably inferior to human intellect (the brief proof is that it's not a Turing machine). It is incapable of self-introspection: it will never understand that it was playing Go. It doesn't know who Ke Jie is, it doesn't even know what a Go board looks like.
Of course not. It was never trained for that. It was trained for recognizing and judging Go patterns. The part of the brain of a human Go player that is responsible for a similar task also don't have self-introspection. That's a responsibility of a different part of the brain.
And human brains aren't Turing machines either. We can't even do trivial problems like factorization of million digit numbers.
We can make as much hydrogen as he needs. And it's lighter than helium too.
Or would you claim a book can be "intelligent"?
AlphaGo has encapsulated knowledge about good and bad Go positions, and can apply that knowledge, not only in identical situations, but also in completely novel situations that resemble similar patterns.
Can you point me to a book that can apply the knowledge contained in it ?
Airships can deliver from point A to point Z without stopping anywhere in between.
Except when there's a storm in A or Z.
Google makes a grave mistake by not making AlphaGo available on Go servers against which the public can train to get better.
It doesn't matter. The real contributions are the ideas and techniques, which will be described in a paper. Other people will take it from here.
Doubt about AlphaGo being a fluke can be debunked by making it available to the public.
If you're not already convinced by the 60-0 victory, and the 3-0 victory, you're not going to be convinced by further games.
Intelligence according to a dictionary definition is "the ability to acquire and apply knowledge and skills". Surely the machine is doing that, and so are Chess computers.
But Go is not anywhere near that point
Right now, it's already beyond the point where it can beat any human. And we've only just started. It's already stronger than Deep Blue was when it beat Kasparov. People also cried when IBM retired Deep Blue, but by today's standards, Deep Blue is a mediocre program. The same will happen with Go.
Indeed. In chess we haven't had any serious man/machine matches since 2006 where Deep Fritz defeated GM Kramnik 4-2. And in the year before that, Hydra beat GM Michael Adams 5.5-0.5. Modern versions of Stockfish and Komodo would wipe the floor with these old programs, and would totally humiliate any human grandmaster.
DeepMind's approach to Go is still relatively immature, and others will surely adopt and improve their ideas and develop even stronger machines.
https://twitter.com/DeepMindAI...
We decided to publish the remaining #AlphaGo self-play games in one go. We hope players around the world enjoy them!
https://deepmind.com/research/...
At least IBM had the balls to go again.
I don't think Ke Jie has the balls to do it again. It would be utterly pointless too, because the AI will keep improving much quicker than human players.
“I feel like his game is more and more like the ‘Go god’. Really, it is brilliant,” he said.
Ke vowed never again to subject himself to the “horrible experience”.
https://www.theguardian.com/te...
...I don't think it has much real-world worry. If you're running an intentionally malicious program on your computer, you've got far worse problems. A SSD is one device. A single credit card number is worth thousands of dollars to you and possibly dozens of hours of your valuable time to fix.
What if you're running a virtual instance on a cloud platform, and somebody else is running another virtual instance on the same platform, sharing the same physical memory and SSD ?
It quickly becomes easier to just waste a bit of fuel to run the pumps - kerosene is more energy-dense than LiPo, after all.
And the kerosene tank gets lighter as you go, whereas the LiPo still weighs the same when it's dead.
Came here to say this exactly.
When I took my database course in university, gender was a boolean. Now it's a tuple of floats.
Why make an exception for women ? Why don't the non-assertive men get a raise too ?
But if your policy of "give anyone a raise if and only if they ask for one" results in systematically different pay for equally qualified men and women, you are breaking the law.
If you are only giving raises to men who ask for it, and you give them to all women, to keep the averages the same, you are discriminating the non-assertive men based on their gender, which is illegal.
we generally do not have a problem learning technical skills or performing jobs with objective requirements, and those tend to be the jobs that pay well.
And Aspergers is about 4 times more common in men than in women....
If that "systematic difference" is objectively related to their ability or qualifications to perform their jobs, it is legal.
Ok, that's settled then.
That means that cases are decided on the preponderance of the evidence,
Which should still be provided by the claimant.
Just keep really detailed records (something Google apparently didn't do)
I'm sure they did, but a smart defense is multi-layered. If you can stop the claim early with some bullshit objections, then this is preferred.
I've answered your question,
Where ?
If you're systematically paying equally skilled and qualified people in the same role different amounts which correlate with gender then you are doing something illegal.
Wrong. The law, assuming that you're talking about the Equal Pay Act of 1963, forbids a discrimination based on gender. It doesn't say anything about correlation. So, if there's a correlation between gender and skill, you may discriminate based on skill, and end up with a correlation between salary and gender.
I think that pretty much says YES, they must do the governments bidding. At least in this instance.
They still have the right to argue that they've already complied with the law, or that further demands are overly burdensome. They may be wrong, in which case their objections will be overruled, but that doesn't mean they shouldn't try.