dawnofdusk

6 ms·

1.
by dawnofdusk 11mo ago
>Mathematicians are prone to taking words from elsewhere, either twisting their meaning or inventing wholly new meaning out of thin air, all according to their whimsy for their own particular needs. True but one benefit of those guys is
2.
by dawnofdusk 11mo ago
>what this routing mechanism is (heating a substrate, maybe?) You can engineer a waveguide if you understand the nonlinear theory they propose. There's no heat exchange involved, which is easy to get confused on because the writing
3.
by dawnofdusk 11mo ago
I really like the second part of the blogpost but starting with Gaussian elimination is a little "mysterious" for lack of a better word. It seems more logical to start with a problem ("how to solve linear equations?" &qu
4.
by dawnofdusk 11mo ago
>My goal is to develop a practical, working understanding I can apply directly. Apply directly... to what? IMO it is weird to learn theory (like linear algebra) expressly for practical reasons: surely one could just pick up a book on tho
5.
by dawnofdusk 1y ago
Although I am not an expert in quantum information, I think the problem you pose is resolved by the fact that the no-signalling theorem is about measurements of a quantum state, which is a microscopic state, and heat transfer is a measureme
6.
by dawnofdusk 1y ago
I have some minor complaints but overall I think this is great! My background is in physics, and I remember finally understanding every equation on the formula sheet given to us for exams... that really felt like I finally understood a lot
7.
by dawnofdusk 1y ago
If it is factually wrong please tell me how.
8.
by dawnofdusk 1y ago
The error in the OP is a typo that could never seriously confuse anyone, as the element Gr does not exist. An interesting perspective is Terry Tao's on local vs. global errors ( https://terrytao.wordpress.com/advice-on-w
9.
by dawnofdusk 1y ago
As any practicing scientist knows even good research papers may be littered with blatant but unimportant errors. There is unfortunately no good reason or system to "correct the record", and it is not clear to me if such a thing is
10.
by dawnofdusk 1y ago
From what I read in the comments of the first post, the Pyon guy seems very toxic and pedantic, but the rebuttal by Ned isn't great. For example, nowhere in the rebuttal is the pedantic technical detail ever actually described . In fa
11.
by dawnofdusk 1y ago
>This seems to be quite a bit of a strawman to me. Not really, if you ever listen to CS undergrads or people in non-traditional schooling (bootcamps, etc.) talk about software engineering this opinion is essentially ubiquitous. People in
12.
by dawnofdusk 1y ago
It's reasonable but essentially every "common misconceptions about Big O" is because people didn't have the necessary notions in calculus. For example, the fact that O(x^2) can be practically faster than O(x), due to the
13.
by dawnofdusk 1y ago
Whenever I read content like this about Big O notation I can't help but think the real solution is that computer science education should take calculus more seriously, and students/learners should not dismiss calculus as "use
14.
by dawnofdusk 1y ago
Agree. Science communicators should stick to talking about well-established or at least peer reviewed results. They do not need to be peddling fringe crackpottery. I don't think Tim's prose is magnificent, but the work speaks for
15.
by dawnofdusk 1y ago
>but we know that reasoning is an emergent capability! This is like saying in the 70s that we know only the US is capable of sending a man to the moon. Just because the reasoning developed in a particular context means very little about
16.
by dawnofdusk 1y ago
It's not that troubling because we should not think that human psychology is inherently optimized (on the individual-level, on a population-/ecological-level is another story). LLM behavior is optimized, so it's not unreaso
17.
by dawnofdusk 1y ago
Optimizing for one objective results in a tradeoff for another objective, if the system is already quite trained (i.e., poised near a local minimum). This is not really surprising, the opposite would be much more so (i.e., training language
18.
by dawnofdusk 1y ago
Basically the same as decrying why we should have to learn foreign languages instead of everyone speaking Esperanto.
19.
by dawnofdusk 1y ago
Essentially all physics simulations are either particle based or based on integration of differential equations (although in a computer both approaches involve a discretization which makes them somewhat computationally similar). You can con
20.
by dawnofdusk 1y ago
Yann LeCun (Meta AI head) is still all-in on energy based models, which are basically Hopfield-like. Not sure if there are any major developments in that direction, but the hype/optimism is still there. https://iopscience.io
21.
by dawnofdusk 1y ago
Pretty cool. Makes me think if we're overdue for another 1960s era tech boom?
22.
by dawnofdusk 1y ago
>FWIW our CS program mandated a programming languages class and the first third of the class was taught in Scheme. This is important but doesn't replace having a dual-track intro sequence. The reason one has "physics for physic
23.
by dawnofdusk 1y ago
I think the solution is to have, as is the case in math/physics, an honors intro CS sequence compared to the regular intro CS class. The latter would be the recommendation for all non-CS majors, and the former would be for CS majors. I
24.
by dawnofdusk 1y ago
Another take along similar lines can be found in the book The Drunkard's Walk: How Randomness Rules Our Lives, by Leonard Mlodinow. Highly recommend.
25.
by dawnofdusk 1y ago
I mean they get evaluated in a weird way: for example you cannot use the `rec` keyword when declaring inputs.
26.
by dawnofdusk 1y ago
I think the more interesting observation here, although the OP doesn't originally point it out, is that the spread of technology is associated with some sort of utility. Fashion and language seem more subjective: there's not a rea
27.
by dawnofdusk 1y ago
At this point I use AI primarily to write docstrings and to do annoying refactors. The value add in other situations is decent but not great, and IMO most of the agentic things are trying to iterate and implement way too much at one time. I
28.
by dawnofdusk 1y ago
Is Apple supposed to be one of the kind and benevolent megacorporations?
29.
by dawnofdusk 1y ago
Not sure if it's the perfect example. Pretty sure Arc was shady before it had any AI stuff.
30.
by dawnofdusk 1y ago
Actually in most deep learning schemes for science adding in the "laws of nature" as constraints makes things much worse. For example, all the best weather prediction models utilize basically zero fluid dynamics. Even though a) gl

More ›