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GIFtheory

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The US does not exist in a vacuum. Cuba just ran out of fuel. These things have cascading effects. Even if you do believe the U.S. exists in a vacuum and you don’t drive a big truck, there are still obvious effects. Spirit airlines went bankrupt, for one. Will this be a global catastrophe? I hope not, but it could be if we’re unlucky.

First, he's had a real anti-corruption push that seems to be meaningful and seems to apply to senior government officials and the wealthy (eg Jack Ma).

Uh, interesting take… I think many would say he was silenced/disappeared by the CCP for daring to openly speak against it.

100% agreed. The moment I saw the “revised” syntax I had a real “what were they thinking” moment. You’re supposed to take the good parts of a good thing and add it to a bad thing, not the other way around!

Really, OCaml’s syntax is beautiful, unless you’re one of those people who loves to show off how adept they are at typing matching braces, parentheses, commas, and semicolons. Writing a little lambda in C++ is an impressive display of manual dexterity… [&](…,…){… return …; }; Who would rather write that than let f x y = … in?

The only way I’d improve OCaml syntax would be to add something like python style list comprehension.

This 100%. McMaster quietly perfected e-commerce at some point, and because we’re live in a fallen world, nobody decided to follow their lead. If only we could convince McMaster to sell toilet paper and cereal…

That’s a nice idea, but I’m skeptical—where is the new wealth coming from that will allow Lesotho to pay its workers more? It’s not an issue of strong-arming some bad guys in Lesotho to pay their workers more using tariffs as a negotiation tool.

I feel that conflating tariffs with some sort of negotiation tool to bring about positive global change is disingenuous, because the real aim is clearly protectionism.

I don’t see how tariffs magically create wealth for foreign exporters that translates into higher wages. Let’s say I can buy a $10 shirt from Lesotho with zero tariff. Now a 50% tariff gets imposed. I can either eat the tariff and pay $15, in which case Lesotho still gets their $10, or Lesotho can eat the tariff to keep their exports competitive, in which case Lesotho now makes $5.

The part about giving a competitive advantage to local producers is true, though…

This argument is problematic because it implies that a person from a different background who committed the same crimes (e.g., a poor, black, uneducated person without any fancy philosophical ideals) /should/ be locked up and the key thrown away. It doesn’t work that way. The law applies the same to all, and that’s the way I like it.

My first reaction to this news was, “fine, sounds like a silly requirement.” However, being a PhD graduate from a minority background, I really have to thank my advisor for the undergraduate outreach work he did, without which there is realistically a negligible chance I would have ended up with a PhD and a great research career. I don’t know what motivated him to do this work, but from a purely pragmatic perspective, if professors know that performing such duties helps them get promoted, perhaps it’s not a bad policy, as long as inequities exist in academia. There are so many other pressures on young faculty, outreach may be something that is hard to justify spending time on unless you have to do it in some sense.

Agreed—the article is sort of silly in that it debunks a bunch of bogus claims about dark mode, but then completely overlooks the main legitimate use, which is to limit exposure to artificial light at night. You basically want to get as much light during the day as is safely possible to stay focused and alert (note that this can be counterindicated for people with certain health conditions, like glaucoma), and then limit light exposure as much as possible at night in order to be able to fall asleep and keep your circadian rhythms healthy. More information here, e.g. https://hubermanlab.com/dr-samer-hattar-timing-light-food-ex...

Nvidia Grace CPU 4 years ago

Interesting that this has 7x the cores of a M1 Ultra, but only 25% more memory bandwidth. Those will be some thirsty cores!

People generally overestimate the benefit of working long hours and underestimate the value of working hard during those hours. If working 55 hours a week is enough to cause serious bodily harm, then it seems likely that the optimal number of working hours from a productivity perspective is far less than that.

I sometimes think it’s useful to think of myself as a mental athlete. My job is to perform intellectual feats of strength in controlled efforts. The rest of my time I spend preparing for those efforts by relaxing.

1) If you're writing anything that's not a script with a few lines, and you care about your software not being terrible to maintain and change for other people in real production settings, typed languages wipe the floor with dynamic languages (excluding ecosystem moats, just judging the languages).

I really hope the typed-vs-not-typed debate is over... types > no types. However... I used to believe that types were essential. I now believe that they are more like a luxury. Good tools are a luxury, not fundamental—it’s way more important to have good software design, and the core of good software design is really tool-independent. It requires deep understanding of whatever problem you’re trying to solve, not a deep understanding of software tools—-unless you’re unlucky enough to be building some horrible middleware.

I also like to dabble in photography, where you see a similar phenomenon. When I take a really great photo, people sometimes remark, “wow, you must have a really great camera!” No, actually, that’s the least important part of the equation. There’s a reason why Canon’s top-of-the line lenses are the “L” series—the L is for luxury. They make the job a little easier, but they’re not really essential.

My take is that engineering is essentially the use of predictive models to solve design problems. I think the general trend is that the more accurate and universally accepted the models are, the more ‘engineery’ a particular discipline is. EEs use models of circuits and devices. ChemEs use models of chemical reactions. MechEs use models based on physics. Financial engineers use models of options pricing, etc. Optical engineers use optics.

So, similarly, SWEs are engineers to the extent that they use widely accepted models to solve design problems. People building compilers, databases, or OS schedulers might be called engineers, because there are relatively well accepted (but evolving) models of the performance and capabilities of those things—-although those models are perhaps less universally accepted than say, Newton’s laws. Hacking, on the other hand, is not engineering, because it is not backed by something like a well-understood model. It therefore tends to command less respect, as the output of such activity is less certain—since there is no good predictive model to judge whether that activity will achieve the goal.

As an example, despite the Star Wars: Episode III - Revenge of the Sith prompt containing text from a single scene, the 0.7 temperature generation imputes characters and lines of dialogue from much further into the movie

This makes me believe it is actually just memorizing the movie script, which is probably in its corpus. As pointed out here, the model has enough parameters to straight-up memorize over 1/3 of its gigantic training set.

https://lambdalabs.com/blog/demystifying-gpt-3/

I'm fairly sure the model is implemented in a reasonable way. It's an experimental deep generative model based on https://github.com/openai/glow, though more complex because the warp and its inverse are evaluated at training time, and the outputs fed to other things. The warp has around 200 layers, IIRC. The model requires keeping track of the evolution of the log-determinant of the warp after each operation, along with the derivatives of those things... so the graph can get pretty huge.

So, this doesn't apply to torch specifically, but to give an example from my own experience... I have a tensorflow model that takes 45 minutes just to build the graph. You can imagine how frustrating it is to wait most of an hour to run your code, only to see it crash due to some trivial error that could have been caught by a compiler.

Although this is somewhat of an extreme example, I'd say most of my tensorflow models take at least several minutes to build a graph. Anything that reduces the possibility of runtime errors would therefore speed up my development cycle dramatically. I'll also note that the OCaml compiler is lightning-fast compared to say, gcc.

Did not freakanomics come up with a famous (and to me more convincing) argument that it legalized abortion was the reason for the drop in crime? At they very least it dispels the arguments we don't have a better explanation and doesn't even mention it.

There was a bug in Donohue and Levitt's code which, combined with other factors, makes the effect go away, supposedly: https://www.economist.com/finance-and-economics/2005/12/01/o...

This story reminded me of how this morning, while commuting via bike to work in the rain, I was tailgated by an SUV. If I had slipped and crashed on some wet leaves, I probably would have been crushed to death, and (in a just world) the driver would be guilty of 4th degree murder. Yet we both carried on with our day as if nothing out of the ordinary had happened. This is insanity. Why does US society tolerate such casually reckless behavior on the roads?

I believe that the problem with a lot of these tech interviews is that they reflect a deep-seated belief on the part of the interviewer, that there exists such a thing as absolute intelligence, that it is immutable, and it is the most important factor in hiring. When you think in these terms, racism seems almost inevitable: after all, if intelligence is a measurable, absolute, and immutable quantity, akin to height or skin color, then shouldn't it also be hereditable?

Instead of administering thinly-veiled intelligence tests, interviewers should hire based on two factors: technical skill, and more importantly, the ability to acquire it (i.e., learn). You don't want to hire (or be) a person who believes in the fiction of genius. You want to be and hire the kind of person who believes and demonstrates that ability is a deterministic function of practice, not genes.