What you're describing is a simplified version of gradient descent (tweaking the weights) and online learning (working on one sample at a time).

This version will not get you far, you will just train a model that solves the last math problem you gave it and maybe some others, but it will probably forget the first ones.

There are other similar procedures that train better, but they've been tried and are currently worse than classical SGD with large batches

Not sure how you can compare vscode with TRAMP. A lot of dev work nowdays is done in containers where you install specific versions of dev tools, compilers, etc. Vscode is one click from seamlessly working inside such a container with its dev tools. TRAMP doesn't provide anything like that, right?

Let me get this straight.

* A west-aligned country is at war with a terrorist organization which is part of the Russian-Iranian-North Korean axis of evil.

* A war which the terrorist organization started unprovoked

* The ally country conducts the most precise strike against militant combatants in history (also completely legal by my understanding of international rules of war)

* Your suggestion is that they should've confiscated their walkie talkies instead

Isn't this a circular argument? The question was what "useful" things do these crypto solutions/companies provide, and your example is a product which allows regulated entities to invest in crypto.

"Why is X valuable? Because X allows you to invest in... X."

Also, in this specific example (Arc), is the solution even considered DeFi? There's a centralized list of whitelister entities and you can only participate if you're a customer of these entities. So they're like banks.

The solution you suggest is irrelevant to the issue mentioned in the article. Even if you use np.random.RandomState, or any other "explicit RNG state", that state will still be copied in the fork() call.

The post just stresses that one should be careful when using random states and multiprocessing, so you should either reseed after forking or using multiprocess/multithread-aware RNG API.

Why use autoscaling and not just launch the instance directly from lambda? The run time is short so there's no danger of two instances running in parallel

> Convolutional layers are just simplifications which make training easier. They are priors in the sense that we know a fully connected layer in image applications would just devolve into a convolutional layer anyway, so we might as well start with a convolution layer. That "design" is the prior. But it's not mandatory; the network would still function without that "prior".

As far as I know this is incorrect. Can you point to a paper that shows this? If by "easier to train" you mean that the models do not overfit training data, then that's the whole point of using correct priors / hypothesis classes.

I'm not sure what bugs you in this paper, but the point is that they decouple the prior architecture from the training/optimization mechanism, and that seems interesting.

Sorry, I meant the claim about f and g. Assuming you meant that F(I) should be continuous functions, you can construct an h from f,g to be cont on I and J, no? So it's not an axiom. Just making sure I understand correctly...

I don't understand why the claim in your second paragraph is an axiom. Doesn't it follow trivially from your definition?

Interesting articles, thanks!

The US, France, and other European countries I can actually understand, since these countries performed military operations in Iraq and/or Syria, but I'll be very surprised if Israel is used as a recruiting tool. If you have some sources implying this I'm interested in reading them!

A lot of "may" and "might" in your reply, and absolutely no facts. The facts are that on ISIS' agenda, fighting Palestinian groups such as Hamas has a higher priority than fighting Israel [1][2], yet people in this thread still manage to "lightly" blame the Israelis, the US, basically anyone except those responsible, as if these people are incapable of independent thought.

[1] http://www.nytimes.com/2014/09/25/world/middleeast/isis-abu-...

[2] http://www.al-monitor.com/pulse/originals/2014/07/islamic-st...

I think the context you've quoted only further proves my point. This sentence means absolutely nothing to me, it's trivial and devoid of any actionable information. But because the interviewee is a "famous data scientist" it is suddenly important info that needs to be shared with the world?

I'm going to sound very aggressive, but I don't understand the point of this book. They say

> The material in this book is too valuable not to share.

and after reading the sample I feel their definition of valuable doesn't align with mine. It's a "handbook" but the chapters are interviews that don't go in depth into anything. Here's a sample "question"

> Compassion is also critical for designing beautiful and intuitive products, by solving the pain of the user. Is that how you chose to work in product, as the embodiment of data?

Really? This reads like an onion article about data science.