undreren's comments

> This is what we, humans, do too when we talk. All these people talk about intelligence in such tautological terms... It's discouraging.

But is it all that we do? And how do you know?

It seems too simplistic to be taken at face value that statistics, randomness and pattern matching would be the only ingredients necessary for intelligence and sentience.

I would guess that it is a convention used to highlight a code dependency.

“If you remove or rename this class, the code will break.”

Can confirm. IME, software that does less usually end up achieving more.

Haskell has “otherwise” as a built in constant that equals true. It reads better in some cases.

    f n | odd n     = 3 * n + 1
        | otherwise = n \\ 2

> They way I've run CD is we had continous deployment to a staging environment where final testing and stakeholder review happens, then periodic deployments to production.

As you hint at, it is called continuous delivery, not continuous deployment.

The best strategy IMO is to mob with testers, and clarify how a thing will be tested before implementing it. It saves you a lot of headaches.

Precisely :-)

Agile is (maybe a bit oversimplified) about releasing as often often as possible.

Delivering sooner, not faster.

To do this, decision makers must be close to the team, and ideally a part of the team. Either managers are part of the team, or the team a given the authority to make product decisions.

Full time managers lose power and influence either way, and I think this is the real reason Big Corp never really bought into it except on paper.

It also interprets and coerces values in formulas.

Empty cells are interpreted as zero, which can be downright catastrophic, if the data is just missing.

Sloppy science is done in every field, natural sciences included. The article even leads with the statement that psychology experience more reversals due to being exceptionally open in terms of sharing code and data compared to other social sciences.

Reversals through replication failure is scientific progress. Your “better” question is nothing of the sort, just lazy contrarianism.

I really enjoy writing parsers. It’s just really fun, though as the article suggests, error detection and comprehension is hard and tedious.

I don't know if I agree with that. The problems of ontologies described in the article are still around today.

Regardless, I thought it was an interesting read, and it put to words things I've observed but couldn't communicate.

Though I have to wonder, if tagging isn't in fact already becoming a dominant strategy for associations? Hashtags and web page sharing on social media posts are both technically and practically tagging systems with wide adoption in what now consititute the majority of the web for many people. There are of course hard categories within these systems, but those are more like a subset of the wider association graph model, not the whole thing.

I have a feeling that "opinionated software" is popular exactly because of YAGNI. Users feel like it's made for them instead of everyone.

I’d say that the logical conclusion is that KPI’s are the problem here.

Let the team measure themselves, bit give them a clear mandate and shared purpose.

When teams are incomparable, no such rivalry can make sense.

But for every adversarial distortion algorithm, you’d in theory have to double your training set, wouldn’t you?

I think the better word is “trained”, not “robust”.

By making almost invisible (to humans) distortions to a picture, a previously well-trained algorithm is now facing a completely unknown problem.

I second this. I have been diagnosed with ADHD as an adult, and my experience, before medication, sounded very similar.

> The thing Ive learned is that a lot of people have both a vested interest and a sort of stockholm syndrome with vendors.

Not to mention “resume driven development”. Recruiters love cloud experience.

If anything, vendor lock-in is consistently underblown.

Caches seem to be much easier to handle using the actor model for handling concurrency.

Actors can have their own cache, and since they queue messages and handle them in order, one at a time, the cache will never be out of sync.

It does come at several other costs though.

If all nodes had a 1:1,000,000,000 chance to randomly flip every tick, then resilient structures would probably arise eventually, given a very large (or infinite) board.