HN user
Just FYI, Amazon and most other providers offer instances that go up to many TB of ram — the largest listed on EC2 right now is 24TB.
Depending on your workload, you may get far better throughput not worrying about distributing the work and data
If you can, working with the logarithms of the intermediate large or small values is one way around the issue
One example talking about this here: http://aosabook.org/en/500L/a-rejection-sampler.html#the-mul...
Context for point 5:
- MIT sued Gehry's firm: https://thetech.com/2007/11/09/lawsuit-v127-n53
- Eventual settlement: https://thetech.com/2010/03/19/statasuit-v130-n14
Carrier freezout actually makes this non-workable -- there's a limit to how cold you can make CMOS devices before they stop functioning. To say nothing of the specific heat of liquid helium, which is miniscule compared to LN2
That is not the free file page, and the fact that it tricks you into thinking it is is exactly the point: https://www.propublica.org/article/turbotax-just-tricked-you...
Looks like matplotlib to me (assuming you mean the top window, not the terminal or what looks like a browser behind)
Yeah, the BladeRF uses an AD9361[1] as the transceiver, which features a pair of ADCs per channel, of which there are two (so, a total of 4 ADCs and 4 DACs in the package). It's got a bunch of other convenient features like built-in PLLs both LO and baseband.
[1]
C-o for me, for exactly the same reason
The latter can be accomplished with inverted flame graphs (sometimes called icicle graphs) which show the call stack inverted
Most of the rocket scientists I know also exercise
Surface mount device: https://en.wikipedia.org/wiki/Surface-mount_technology
How about pointing to several hundred years of systemic slavery and oppression without any meaningful reparation efforts?
https://www.apple.com/business/docs/iOS_Security_Guide.pdf
https://images.apple.com/business/docs/FaceID_Security_Guide...
Seems pretty likely there will be a whitepaper and some conference talks about this as well.
So long as all frequencies you're trying to represent are below the Nyquist frequency, there's still only one band-limited reconstruction of the samples. So yes, it's still possible to reproduce everything accurately so long as all of the individual frequencies (no matter their relationships) fall below 1/2 the sample rate.
If you're going to do any random processes, the graduate course (and corresponding textbook) from EECS at MIT is great: https://ocw.mit.edu/courses/electrical-engineering-and-compu...
Textbook: https://www.amazon.com/Stochastic-Processes-Applications-Rob...
https://en.wiktionary.org/wiki/bury_the_lede
OP is implying the "real story" (i.e. the most important part of the article) is not what the article begins with
I paid $12 on Amazon for 6 Travalo lightning cables on Amazon and I couldn't be happier with them. Lightning interface is legit (no notifications about unsupported lightning connector) and they're more robust than the official Apple cables.
FFTW is one of the seminal examples of the importance of cache awareness, if I remember my history correctly. As I understand it, the reason the fftw authors (Matteo Frigo and Steven G. Johnson) won the Wilkinson prize was essentially because fftw exemplified the importance of cache-aware algorithms, as opposed to blindly optimizing number of operations.
I don't know, but I would guess that intel's implementation post-dates fftw?
Same goes for me when doing CAD and having to constantly convert between standard & metric -- 254, 508, etc show up in numbers a lot and it gives you a nice hint that it's a "clean" value in the other system. Super useful for reading IC footprints off datasheets that only use one of the two systems
[1] turns out to be more subtle than people originally thought. Even assuming you can make loophole free bell tests (hey, it's been done!), the best anyone has been able to show this does -- even theoretically -- is randomness /amplification/ not true verifiable randomness. This boils down to the need for an initial random basis preparation of the qubits for which you have no true random seed.
I know some people have been working on solving that chicken and egg problem, but -- unless there's very new work I'm unaware of -- it's still unsolved.
"Utterly bizarre" captures a lot of my feelings about science funding and the graduate student research mill, yeah
Not universally true -- I know students on NDSEG fellowships (i.e. DoD) receive a 1099. I can't speak to the other fellowships though, and I don't get any deduction/withholding done for me, so I have to pay estimated quarterly.
And funds that come through my university do get a W-2 come tax time.
Wow, I've literally never heard of a PhD where you were only expected to work 20 hours/week. I'd say 50-60 is closer to the norm, especially once you're done with your coursework (usually a year or two into a 5-7 year long PhD).
If you don't mind, what field(s) are you two in?
Well, the entire human race is inadequate to run a marathon in less than 2h so far...
Previous discussion (~5 years ago): https://news.ycombinator.com/item?id=2477667
Just worked for me
That was a fantastic post, thank you for sharing. Ironically, while affirming the view I held above, it also makes me think I should -- maybe -- give them another chance now that I'm well along in graduate school as opposed to a struggling undergrad.
I'm not sure that Feynman is the best example here. In fact, in my experience, he's actually more of an example of the problem than the solution. While Feynman does a great job of explaining concepts if you never need to use them, I always found his lectures to be of the "captivating until you try to use them" variety.
This wasn't just my experience either -- after struggling with this as a physics undergrad for a while (after all, they're supposed to help!) I started asking around. My academic advisor, several other professors, and many students felt the same way. Feynman may get closer -- or may do more to bring common understanding to complex principles -- but his approach broke down for actually learning to /do physics/.
But I'll agree that he's a major step in the right direction; I just want to caution against the hero worship. There's no magic formula, no one person, who can make learning complex concepts easier. Some things are hard, and trying to make them seem easier can easily make them more confusing in practice.
Nifty, thanks. I've been lucky enough to be able to default to microcontrollers with usb-serial built in recently, but that's lookkng to be short lived...