Patently not so. There were a myriad BAD phones out there until the iPhone won it from a design perspective.

When Apple changed to OS/X, there was a huge wall of competition known as Windows stuff. Macs continue to thrive.

The iPad seemed like it was plainly stupid, until it took off.

Lots of watch markers until that worked for Apple.

Apple is excellent if TRAILING-EDGE. Let other titans fight and cross-fertilize themselves with deals, litigation, and harrumphing. My guess is that Apple waits for the dust to settle.

Unlike every other over-caffeinated PR minion in the world, Apple's don't get in a tizzy easily. Short game and long-game are two different beasts. Although I have much bad to say about Apple, they've learned how to avoid expensive catastrophe before; take driverless tech as an example.

Training data litigation, model integrity, the plateau of model crash, all these are good reasons to wait until there are clear winners.

Microsoft and Google and Meta are pissing off the public with aggressive moves surrounding AI in apps.

A wait-and-see attitude isn't likely to leave Apple in the dust.

Yes, AI is super interesting as computer science, its threats are entirely related to how it is being deployed, or even that it is being deployed at all. AI is more sociopathic that even the worst human sociopaths, yet politically we seem to think that any regulation of AI deployment must be illegal. Imagine if our laws grant immunity for murder to clinical sociopaths, it would almost be precisely a recent SCOTUS decision regarding the President.

"... first of all, Python is one of the very few languages that can handle numbers very, very well."

This is false. Python has 3rd party libraries that handle numbers well. Those libraries are not Python and learning Python does not mean learning those libraries.

"Python is a great choice for large databases because there's a lot of support for Python libraries."

They aren't Python libraries, they are libraries that support Python. And they make Python a good choice for accessing large datasets, not large databases. Yes, these are complaints over sloppy language, but if this "Walmart data scientist" cannot get language right, why are we interested in his comments regarding educating of children? It seems to me this guy is just a layman.

It is both, and has been for quite a long time. But it's a symptom, there's a root cause.

"I agree the admins should ban him."

Your free speech absolutism is super sexy.

"It damages coral reefs and other ocean habitats and, in extreme cases, can dissolve the shells of marine creatures."

Well they were asking for it, amirite?

Nothing left to defend? Have you met SuperKendall?

And Apple doesn't copy everything from Microsoft, for example Apple won't let you turn the shit off.

skeumorphism is when Jonny Ive took a big hairy shit on your screen, and is still getting paid for it.

"In the same way that many students today convert their school-issued Gmail accounts into personal accounts when they graduate, Ms. Belsky envisions graduating students bringing their A.I. chatbots into their workplaces and using them for life."

These "technologies" won't last 6 months, much less 60 years. Students could not care less what they're using as a crutch in the future, only that their lack of learning remains unexposed.

... "you" ...

Also, it should be mentioned that humans are notorious for inadvertently making these kinds of copyright violations themselves, not necessarily with text because their recall isn't that good, but with music it happens frequently. If you think a detector applied to output is going to solve problems, intuition says you will be disappointed.

But you are right, it's not clear there is copyright violation during training but there certainly is during inferencing. Problem is, it is not AT ALL clear that copyright-clean training data will prevent copyright violations during inferencing.

That is true, but a "copyright classifier" contains what? Given the term used, it appears you are suggesting another LLM with imperfect memorization. How do you think that solves any problem?

The hard part is in the doing, what are suggesting is obvious.

"Marketing AI without compensating data creators is, in essence, intellectual property theft."

It is not, marketing is marketing.

And it remains to be seen if training is IP theft, so far the focus has been on copying and storing data, not training with it. They are doing that because it's not clear that training isn't fair use.

Except in the AI case, it's not clear it's not fair use. People now accusing AI training of criminality are worse.

"They say that because they're fucking liars."

They don't say it, that's a just a troll that you are excited to believe. But, yes they are fucking liars.