curry-castaway

> They're a consultancy which evaluates computer security for insurance companies, before they insure a business.

Can you share the name of the company?

Google's related post, "Exploring Neural Networks with Activation Atlases", has some more detail and image samples: https://ai.googleblog.com/2019/03/exploring-neural-networks....

Interesting example of the activation atlas in action:

> These atlases not only reveal nuanced visual abstractions within a model, but they can also reveal high-level misunderstandings. For example, by looking at an activation atlas for a "great white shark" we water and triangular fins (as expected) but we also see something that looks like a baseball. This hints at a shortcut taken by this research model where it conflates the red baseball stitching with the open mouth of a great white shark.

> We can test this by using a patch of an image of a baseball to switch the model's classification of a particular image from "grey whale" to "great white shark".

I can second this recommendation – Oclif[0] is an absolute pleasure to use. I'd even encourage developers who aren't at a "full-stack Node.js shop" to give it a shot.

I'm particularly impressed with the bash and zsh autocomplete support. I was delighted when I finished setting it up and everything worked perfectly on the first try.

[0]: https://oclif.io/

I committed my dependencies until recently too, and I've been trying to figure out a better alternative. Are you doing something else now rather than committing dependencies? (Right now I'm just using a hodgepodge of npm scripts to lock things down.)

> We don’t allow automatic upgrading of packages/dependencies due to the risk of malicious code

That's a good idea, how do you do that?

> you always need local archived copies of any dependencies you use.

Are you committing your dependencies? Or using a package manager with caching?

> The real question is: do you -really- need an external lib with 20 dependencies just to show a freakin’ loading spinner? Remaking the wheel is bad but so is never making truly simple things yourself, or just not using them.

So the problem is the sheer number of dependencies? What is a reasonable upper limit?

Yes, javascript should continue to standardize commonly used features, but avoiding dependencies doesn't seem to be a solution.

If anything, more dependencies are a good sign because they imply that other people have spent more time and effort on a solution than anything you'll be able to hand-roll for single-use.

It sounds like the root issue here is just dependency management. If our package managers were solving this issue well enough, there should be no practical difference between 2 big dependencies with significant functionality (and more code to review) or 20 tiny, easy-to-review dependencies.

Direct link to the study – "Electrophysiological and transcriptomic correlates of neuropathic pain in human dorsal root ganglion neurons": https://academic.oup.com/brain/article-lookup/doi/10.1093/br...

> One of the direct dependencies is a library that renders a loading spinner in command line interfaces, which itself pulls in over 20 transitive dependencies.

Just trying to understand, is this a bad thing?

Someone else made an open source CLI spinner library which also uses other people's existing open source libraries. This saves a lot of time and gives developers many good options.

Should Pika write and maintain its own custom CLI spinner animations? Are you saying the CLI spinners should be standardized in the next version of ECMAScript itself?

How is this worse than the same thing written in Python, for example? (I mainly use javascript, so maybe I haven't been exposed to the kinds of alternatives you're thinking about.)

I always have trouble using PGP to encrypt and send files – I always have to refresh on the CLI usage, and whoever I'm sending to usually does too. I think this is a really cool tool for sharing encrypted files with people who are less comfortable with PGP.

> one of my friends has a mega-sized server than he just runs builds and trains ML models on

I built my first desktop computer to do this recently. I can definitely recommend it, even for local server development. It's nice to be able to have a version of a codebase running on the remote machine so my local laptop stays cool while I'm testing.

Do any of these options have a case that feels sturdy? It seems a little silly describing it this way, but one of the reasons I keep coming back to macbooks is the aluminum case. I want good specs, but my lizard brain also wants a laptop which doesn't feel like a flimsy plastic toy.