elliptic

Richard Hamming's thoughts (from You and Your Research) deserve to be quoted in full (below). Probably they are less applicable the less research or speculative work you do.

Now for the matter of drive. You observe that most great scientists have tremendous drive. I worked for ten years with John Tukey at Bell Labs. He had tremendous drive. One day about three or four years after I joined, I discovered that John Tukey was slightly younger than I was. John was a genius and I clearly was not. Well I went storming into Bode's office and said, ``How can anybody my age know as much as John Tukey does?'' He leaned back in his chair, put his hands behind his head, grinned slightly, and said, ``You would be surprised Hamming, how much you would know if you worked as hard as he did that many years.'' I simply slunk out of the office!

What Bode was saying was this: ``Knowledge and productivity are like compound interest.'' Given two people of approximately the same ability and one person who works ten percent more than the other, the latter will more than twice outproduce the former. The more you know, the more you learn; the more you learn, the more you can do; the more you can do, the more the opportunity - it is very much like compound interest. I don't want to give you a rate, but it is a very high rate. Given two people with exactly the same ability, the one person who manages day in and day out to get in one more hour of thinking will be tremendously more productive over a lifetime. I took Bode's remark to heart; I spent a good deal more of my time for some years trying to work a bit harder and I found, in fact, I could get more work done. I don't like to say it in front of my wife, but I did sort of neglect her sometimes; I needed to study. You have to neglect things if you intend to get what you want done. There's no question about this.

Just to be clear, it's not my version. I've always wished I could read Classical Greek.

A more sober translation seems to be:

And the gray-eyed goddess herself bestowed on them every art, so that they surpassed all mortal men as the best workers with their hands; and the roads bore works of art like living, moving creatures, and their fame was profound.

Which perhaps doesn't carry the same implications as the rather florid translation you quoted.

I'm not saying that Oracle hardware or software is the solution, but "scaling-out" is incredibly difficult in transaction processing. I worked at a mid-size tech company with what I imagine was a fairly typical workload, and we spent a ton of money on database hardware because it would have been either incredibly complicated or slow to maintain data integrity across multiple machines.

I imagine that situation is fairly common.

I wonder how many of these sorts of algorithms are out there? We might be hearing about the guy that received 10 consecutive accurate stock tips.

Are there compression techniques that are only "mostly" lossless? I was thinking something along the lines of: for delta, N > 0 the probability that the compression & decompression of a random stream of N bytes will result in loss is less than delta?

In what sense is this list "curated?" I'm seriously asking. Have you used all/most of these, and can recommend them?

Do you know he was kidnapped illegally? Or is that alleged?

What did they do that you know was illegal?

So, basically, you think that there are exactly 0 CS professors who are horrible programmers?

Anyone know of good papers relating to deep learning that are not from image classification or speech/text recognition?

Seems like a somewhat artificial distinction. I'm responsible for coming up with my own models and implementing them in production.

What's this weird idea that "B-players hire C-players to make themselves look good?" Are we convinced that all the B-players (let's face it, that's most of us) are so terribly weak and insecure? Is it relative? Would the A-players at Powerset be B-players on a team with Jeff Dean? Would that cause them to hire C(B?)-players? If you hire someone better than your current A-players does that demote them and turn them into poisonous cancers?

<< Lots of people on the other side of the hills (Concord, Moraga, Walnut Creek) have this idea that Oakland is a really scary place. I think it's partly racial (because of the higher percentage of African Americans here) and partly a PR issue (the 24/7 news cycle only presents sensational items) >> Lots of people have the idea that there is a lot of violent crime in Oakland because, well, there is a lot of violent crime in Oakland. No need to bring race into it.

I don't think it has much to do with his salary. My view of him is largely positive as well, but from what I've read (Masters of Doom, a lot of his writing) he is not a man to whom empathy comes easily (which is not to say he isn't a good, moral man).

I'm not sure I'm more productive on 8 than 6 hours' sleep - is there any way to verify this? I'd even pay good money to find out the optimal amount of sleep for me.

This raises the question - are there fields in tech or software engineering that are mostly empirical or mostly conceptual?

The "{area/field/business} is broken" template is broken (well, I don't know if ever worked). Algorithm development is not broken - it's specialized work and it's largely done by people with specialized backgrounds. Maybe that's not ideal, and maybe you can improve it, but saying "it's broken" is lazy and false.

> An ecosystem is a four-sided network — you need entrepreneurs, VC firms, schools, and journalists

That sentence tells you all you need to know about the author and his perspective, I think.

I believe that when people complain about "lack of stack allocation" in Java they sometimes mean "lack of value/non-reference types," which in other languages (at least C#) are frequently but not always stored on the stack.

Serious question - how realistic is that? How many people make significant changes to the planner/executor besides Tom Lane?

An odd rant. The judge in question appears to be an alcoholic, and came to the court drunk. Surely this is professional misconduct (and to my mind warrants firing), but it really doesn't justify the author's charges of system-rigging. Seems to me that Clark is trying to mislead people into thinking that Pollack was under the influence of e.g heroin. Pretty despicable.

Also, the smallest bit of Googling shows that Pollack heads was responsible for the creation of some sort of special "marijuana court" which expressly sent users to rehab, not jail.

I don't know much about this Clark guy (girl?), and I agree with some of the points in the article, but he/she seems pretty close to a flat-out liar.

I don't understand - when you made this decision, did you expect that you were going to be good enough so that these features of chess (draws and deep, well-studied opening theory) were going to be relevant to you?

Ehhh. Those companies and others like them (Aramco, etc) represent the heart of the modern industrial economy, for better or for worse. Are consumer companies like Apple even imaginable in their absence?

Ought "just lost their mother or grandmother" really be a single category? I don't know if I'm acting correctly, but I tend to approach those two conversations rather differently.

Probably like all books that are meant to be strange and mysterious, it's actually quite boring. The strangest books to me are those the authors meant to be understood. One example (for me) is Valis, by PK Dick.

I don't think those 3 are any less well-known than other physicists and mathematicians of similar accomplishments. Ramanujan, in particular, because of his romantic story, is far more well known than his influence might suggest. His intellect might well have been the equal of Riemann's, but one can't honestly say his contributions even approach Riemann's. The same goes for the the physicists - Bohr was one of the three or four most important physicists of the last century, and Heisenberg was one of the top 10, probably.

So I know a little about neural networks and ML in the (simpler?) context of image classification etc. Anyone have a good reference/introduction to using it for this sort of work?

I thought that one of the comments - to the effect that this article tells us relatively little about Borges and perhaps more about the author - was very perceptive. I am going to try to remember not to fall into that trap.

It is difficult to imagine what sort of evidence will convince you. All sorts of behavior is possible under all sorts of unrealistic models.

I'd also like to note the irony of your snarky comment about wishing that those who disagree with you ought to study some math, given the background of managers like Jim Simons.

Edit: > First, he didn't beat the market average 227 times in a row -- for most of those periods, he didn't lose money, but then a buy & hold investor also didn't lose money. A meaningful comparison would have to compare his outcomes with that for a buy & hold investor riding the ascending market value by holding a boring, geriatric index fund

The stock market rose by about 8 or 9% annually during that time. Dismissing his 227 positive months requires absurd contortions, like positing that his firm would invest in the stock market or t-bills for 11 months out of the year, and then make a series of large bets in the remaining month. Given that he made, I believe, 10k bets a year, the disparity in bet size must be massive to even come close to supporting your hypothesis.