adyavanapalli

Consider adding this comment on the grandparent. Thank you!

The author wrote a follow-up article as well: https://thegradient.pub/a-speech-to-text-practitioners-criti...

Not that it's important making this distinction, but what you're describing doesn't sound like occupational burnout; you've listed significant trauma that are only exacerbating your work-related stress, and I'm really sorry you're going through this!

First, I would agree with @codingslave in that you SHOULD NOT quit your job, if you can help it. Let me explain: Work provides important scaffolding when you are in a rut. It provides routine and social contact. Without it, it is possible you might start sliding into poor sleeping habits and withdrawing socially, which can make things even worse. At the very least, find a less stressful job to move to before leaving your current one. If this is hard to do, please reach out to family or friends for help. Please understand that it's absolutely okay to struggle and have bad days. Give yourself permission to feel.

Second, it's awesome that you're seeing a medical professional/therapist about this, and I encourage you to keep doing so regularly. "What should I do?" I think you're approaching this well. I wish you the best!

What do you dislike about it?

There are two complementary parts participating in the registration and authentication ceremonies, WebAuthn and CTAP. The response from the authenticator, as per the CTAP protocol standard, is encoded as CBOR. We need the JSON parts from the WebAuthn browser API for the parts in the ceremony that talk to the relying party (particularly for relaying the challenge responses, and allowed authenticator algorithms and behaviors).

Can you clarify whether you mean only the `attestationObject` should be sent to the server or that everything should be encoded as a single CBOR object and then sent to the server?

The intended audience of AMS's Graduate Student Section is mathematics graduate students. Nevertheless, it's hard to say whether symplectic manifolds has any easily explained analogy for lay audiences. The subject originally arose from more abstract formulations of classical mechanics.

How recent was this?

I'm sorry that I can't find the reference for this right now, but I read a paper a while back showing that (particularly stochastic) gradient descent usually finds good solutions (and that these solutions are very close to each other), although not absolute extrema, to highly dimensional neural networks. Whats more, you usually want to avoid finding absolute extrema solutions because they often suffer from overfitting behaviors.

I think the OP is asking about the _value_ of the FPR instead of the definition.

How the flying heck did your psychiatrist let you stop taking your medication cold turkey? There's usually a weaning off process for any sort of psychiatric drug.

Ketamine is usually prescribed to people with "treatment"-resistant severe depression, and these "treatments" include other types of medication, exercise, and meditation. That aside, often, severely depressed people can't do even the basic things like showering, going to work, or making dinner. Ketamine treatment offers a severely depressed person to bootstrap themselves into a state where they _can_ start doing things that will allow themselves to support themselves.

Episode link: http://omegataupodcast.net/159-analog-computers/

The author says the opposite:

"The non-recursive way is more efficient as the CLR does not have to keep pushing and popping its call stack (which is quite slow). The non-recursive way is unfortunately harder to code. So the challenge was on!"

"Peta floating point operations per second per second" XD

From the abstract:

In this dissertation I investigate the theoretical possibility of a universal method of prediction. A prediction method is universal if it is always able to learn what there is to learn from data: if it is always able to extrapolate given data about past observations to maximally successful predictions about future observations. The context of this investigation is the broader philosophical question into the possibility of a formal specification of inductive or scientific reasoning, a question that also touches on modern-day speculation about a fully automatized data-driven science.

I investigate, in particular, a specific mathematical definition of a universal prediction method, that goes back to the early days of artificial intelligence and that has a direct line to modern developments in machine learning. This definition essentially aims to combine all possible prediction algorithms. An alternative interpretation is that this definition formalizes the idea that learning from data is equivalent to compressing data. In this guise, the definition is often presented as an implementation and even as a justification of Occam's razor, the principle that we should look for simple explanations.

The conclusions of my investigation are negative. I show that the proposed definition cannot be interpreted as a universal prediction method, as turns out to be exposed by a mathematical argument that it was actually intended to overcome. Moreover, I show that the suggested justification of Occam's razor does not work, and I argue that the relevant notion of simplicity as compressibility is problematic itself.

That's the joke XD

To see all available commands, `compgen -c | sort`.

Perhaps it is more "speaking" to give what that distance means in terms of area. A radius of 50 mi. would mean an area of approximately 7854 square mi. Doesn't that sound like a lot now?

I had the literally the exact same thing happen to me about a month ago. The automated account recovery provided by Gmail was not helping the least bit, and I desperately needed to talk to a human. I ended up creating a Twitter bot to tweet at the Gmail team every 12 hrs or so complaining about how I couldn't recover my account even though I had it for 10+ years, and about three days later, they responded and helped me through a streamlined recovery process that helped reset my password.

You don't need to create a Twitter bot like me, but I would try tweeting at @gmail or @google once a day until they respond. Good luck!

That is so cool!

Do you know any resources for learning this?

> I am so psyched... Heh, I see what you did there XD

Anything for Windows or Linux users?

I'm curious, is there a better strategy?

To piggy back on this, Devlin has an excellent free course on Coursera roughly following the textbook.

>If coffee is too hard to give up, try soft drinks. Right. You could get by with saving less because you will also die earlier! :P

WNYC ran a great podcast series on busting myths about poverty. Here's a link: https://www.wnyc.org/series/busted-americas-poverty-myths

My favorite go-to book for basic physics is the 1966 edition of Haliday & Resnick, which you can still find on Amazon as a combined two volume book, I think. The newer editions are quite watered down, but they do an acceptable job. There's also a newer, more advanced version of these books called Physics, Volume 1 & 2 by the same authors that you may consider checking out.

Books are hard reading though, so video lectures are also the next best option. Walter Lewin does a good job with this, so try googling his lectures.

Also, you'll probably want to stay away from Feynman lectures until you actually understand the theory.

You'll find that no such thing is true. Intuition is something you develop over time in mathematics, and mathematicians will often use this intuition to have certain "feelings" about problems e.g. a feeling that a certain conjecture must be true.