fhe

for me the clickbait title had the opposite (of their intended) effect. I was going to pass until I saw your comment that it's about "worms", which is actually interesting and if they are making claims about worms, it passes my bullshit test. I understand why people use clickbait titles, but I feel it ill-serves them by attracting the wrong kind of audience.

banks don't own the deposits. in fact, deposits are liabilities on their balance sheets.

very true. I was a math major in college, and many of the problems that I had to solve in combinatorics (through quite elaborate manipulation) turned out to have rather conceptually-simple and elegant solutions by calculus.

nice feature: every time a link gets posted, auto-generate a comment with all previous postings of the same link, together with the number of comments, dates and other assorted info.

> "their flight wasn't as controlled as I had thought of"

I had the same reaction, and it reminded me of other slo-mo videos of insects crawling -- it looked like they are falling all over themselves, with none of the gracefulness that I see in mammals (cheetah running, for example). I wonder if it has to do with insects having much smaller mass, hence they are more easily jerked around by things like airflow.

How would you compare NZ with Australia? What are the big differences you noticed? Thanks.

these examples are so often named precisely because there are few others.

I have two cats, and they show good judgment on what plants they nibble on. They only show interests in the grass that I grow for them (in general any kind of grains, e.g. wheat, barley, etc.), and they never touched my other house plants. This is anecdotal, but at least in the case of my two cats, they seemed able to distinguish edible grass from toxic ones with no prior learning.

I place quite a bit of importance on cover letters. Cover letters that are concise and clear and professional don't come up often, and are always highly appreciated. Well written cover letters and resumes also correlate highly with the professionalism and abilities of candidates, in my experience. I hire mostly for non-technical positions, and I am mindful that in highly technical positions, maybe past work speaks for itself, and there's less emphasis on cover letter and resume.

does anyone have knowledge of whether, once a battery starts losing capacity, does it do so in accelerating speed? My experiences with laptop and phone batteries suggest that they do. It took a couple of years for batteries to be reduced to 85% capacity, but from there it took only half a year for them to diminish to 60% or 50%.

what's a good textbook/tutorial for someone self-teaching Racket to follow along?

Just curious: could you define better?

just want to get a sense: any hacker newsers living in Beijing? if enough of us, I'll organize a Beijing meetup.

agreed.

can't wait for self-driving vehicles

I concur. Last night I spent 30min trying to change the setting of my house heater. It's a Bosch heater, and one of the better quality brands. My! It bemuses how they could have gotten the UX so bad. It has only a handful of simple functions -- it reminded me of PG once mentioned he got an error message from trying to adjust settings on an oven. I have had similar experiences with my car. Did these designers even bother to use their own products.

copywriting skills; humor; basic graphic design skills.

this is a very interesting move by YC. I can't wait to see if the "YC methodology" will work in China's startup scene. China's startup culture is notably different from Silicon Valley.

to live in China, one could get by with little to no mandarin; but to do business in China, mandarin is a must.

I love the way you opened the course with a personal story.

The current explanation from the professional Go community is that, duking it out in the middle is far too complex for humans to master. So maybe it's not so much that corner positions are better than edge positions, which are better than center positions; it's just that the center area is far too complex to yield to human analysis.

I think similar observations and arguments were made in the 80s about Japanese firms. It would be interesting to make some comparison, if only to see how things are (or could be) different this time.

the correct komi number has puzzled Go players for centuries, now we might finally have a chance to figure out the right answer (although not without some reservations). over the last 5 decades, komi has consistently been raised to keep the game more leveled between white and black (black makes the first move, so has the advantage). historically, there was no komi, and people kept an even game by always playing even number of games with each player switching sides after each game.

for whatever reason, it's no longer feasible in modern pro game (not to mention that this could result in no winner if each player wins half the game), so komi was introduced. at first at 5.5, and steadily climbed higher to 7.5 at present. In pro game, even a change of 1 is considered a big deal, so from 5.5 to 7.5 is hardly trivial.

Now with alphago playing "perfect" games against itself, we might finally be able to put to rest the debate of the correct komi (the Japanese Go associations for decades have kept meticulous records of every professional game, in order to find the correct komi).

There is a big "but" though. The correct komi at Alphgo Zero's level might not be the correct komi for human level players (AlphaGo is estimated to be 2-3 handicaps above human play; this is a bigger gap between the average pro player and the best amateurs).

Indeed, the change from 5.5 komi to 7.5 komi also had a lot to do with the change in play style rather than simply zooming in on the "correct" komi number. In the 70s and 80s, predominant play style was more conservative, and 5.5 might well be the correct komi for the time (defined as resulting in 50:50 chance of winning for either side). As play style shifted to become more aggressive and confrontational (actually fueld somewhat by the introduction of komi), it was discovered that komi needs to be raised to keep chances of winning at 50:50.

To make an analogy, suppose one is playing a casino game of chance that gives the house a slight advantage (similar to the first mover advantage for black in go). If one only makes small bets, the house will end up winning only a small amount. in other words, the player needs to be compensated by a small amount to make the game "fair".

If however one makes big bets (i.e. more aggressive game play), then the compensation needs to be bigger too, to make the game "fair", even if the underlying probabilities have not changed.

following this logic, while 7.5 komi is fair for Alphago vs. alphago games, it might not be the right number for human games. I suspect it might be samller for humans.... if only we could calibrate Alphago to the average human level and generate millions of self-play games...

their fund did well in China between the late 90s and early 2000s. It has not performed as well since, but still a reputable institution investor in China.

with 93 billion dollars, one can, say, invest in all reasonably promising startups in the world continuously for, say 10 years, perhaps? And a couple of them will turn out to be Facebook/Google. (I have no data at hand to back that up, but 10 billion a year sounds more than enough? there are about 20 top VC firms in the Valley, and few of them has funds bigger than a billion dollars, and they typically invest over 5-7 year periods).

It was a crushing victory actually. I watched the entire game, and followed professional commentary. Before the end game started, Alphago was leading by between 10 to 15 points -- an enormous lead in professional games. Most players would have simply conceded, which is not to say this is what Kejie should have done. Actually Bravo to him for sticking it to the very end, and let us all watch how a computer would handle end games. As it turned out, Alphago routinely picked the marginally safer move while yielding a bit of its lead. A style of playing that's not consistent with human players.

The one game that Lee managed to defeat AlphaGo was probably the last time any human player was able to beat the strongest Go program at the time. That said, there are a few interesting ideas to try, and I (being a reasonably strong amateur go enthusiast myself) would love to see Google try out:

1. how many handicaps can AlphaGo give to human players, while still come out winning? the idea of handicap is basically the stronger player lets the weaker player a few "freebie moves" before the game proper starts. For reference, a typical professional player can give 2 to 3 handicaps to the strongest amateurs.

2. Can AlphaGo defeat a group of professional who are also given unlimited time to think and discuss?

while the skewed sex ratio is true, lumping all of China together is misleading. The sex ratio is quite balanced in cities, for example, meaning that women living in cities don't quite enjoy the advantage.

My friends and I (many of us are enthusiastic Go lovers/players) have been following all of the games closely. AlphaGo's mid game today was really strange. Many experts have praised Lee's move 78 as a "divine-inspired" move. While it was a complex setup, in terms of number of searches I can't see it be any more complex than the games before. Indeed because it was a very much a local fight, the number of possible moves were rather limited. As Lee said in the post-game conference, it was the only move that made any sense at all, as any other move would quickly prove to be fatal after half a dozen or so exchanges.

Of course, what's obvious to a human might not be so at all to a computer. And this is the interesting point that I hope the DeepMind researchers would shed some light on for all of us after they dig out what was going on inside AlphaGo at the time. And we'd also love to learn why did AlphaGo seem to go off the rails after this initial stumble and made a string of indecipherable moves thereafter.

Congrats to Lee and the DeepMind team! It was an exciting and I hope informative match to both sides.

As a final note: I started following the match thinking I am watching a competition of intelligence (loosely defined) between man and machine. What I ended up witnessing was incredible human drama, of Lee bearing incredible pressure, being hit hard repeatedly while the world is watching, sinking to the lowest of the lows, and soaring back up winning one game for the human race.. Just incredible up and down in a course of a week. Many of my friends were crying as the computer resigned.

As someone who studied AI in college and am a reasonably good amateur player, I have been following the matches between Lee and AlphaGo.

AlphaGo plays some unusual moves that go clearly against any classically trained Go players. Moves that simply don't quite fit into the current theories of Go playing, and the world's top players are struggling to explain what's the purpose/strategy behind them.

I've been giving it some thought. When I was learning to play Go as a teenager in China, I followed a fairly standard, classical learning path. First I learned the rules, then progressively I learn the more abstract theories and tactics. Many of these theories, as I see them now, draw analogies from the physical world, and are used as tools to hide the underlying complexity (chunking), and enable the players to think at a higher level.

For example, we're taught of considering connected stones as one unit, and give this one unit attributes like dead, alive, strong, weak, projecting influence in the surrounding areas. In other words, much like a standalone army unit.

These abstractions all made a lot of sense, and feels natural, and certainly helps game play -- no player can consider the dozens (sometimes over 100) stones all as individuals and come up with a coherent game play. Chunking is such a natural and useful way of thinking.

But watching AlphaGo, I am not sure that's how it thinks of the game. Maybe it simply doesn't do chunking at all, or maybe it does chunking its own way, not influenced by the physical world as we humans invariably do. AlphaGo's moves are sometimes strange, and couldn't be explained by the way humans chunk the game.

It's both exciting and eerie. It's like another intelligent species opening up a new way of looking at the world (at least for this very specific domain). and much to our surprise, it's a new way that's more powerful than ours.