That knowledge is out of date and out of touch. While it’s possible to expose small bits of training data, that’s akin to someone being able to recall a portion of the memory of the scene they saw. However, those exercises essentially took what sometimes equates to weeks or months of interrogation method knowledge gained over time employed by people looking to target specific types of responses. Think of it like a skilled police interrogator tricking a toddler out of one of their toys by threatening them or offering them something until it worked. Nowadays, that’s getting far more difficult to do and they’re spending a lot more time and expertise to do it.

Also, consider how complex a dragonfly is and how young this technology is. Very little in tech has ever progressed that fast. Give it five more years and come back to laugh at how naive your comment will seem.

Half of your argument is just saying, “nu-uh” over and over again without any valid counterpoints.

In the same way that a person can learn the material and also use that knowledge to potentially plagiarize it, though. It’s no different in that sense. What is different is the speed of learning and both the speed and capacity of recall. However, it doesn’t change the fundamental truths of OP’s explanation.

Also, when you’re talking specifically about music, you’re talking about a very limited subset of note combinations that will sound pleasing to human ears. Additionally, even human composers commonly struggle to not simply accidentally reproduce others’ work, which is partly why the music industry is filled with constant copyright litigation.

For summarization, having the data correct is crucial because manual typing itself is not a large chore. AI tends to shine more when you’re producing a lot of manual labor such as a 10-page document for something. At that point, the balance tips the other way where proofing and correcting is much easier and less time-consuming than the production itself. That’s where AI comes in for the gains in workflows. It has other fantastic uses as well, like being another voice for brainstorming ideas. If done well, you’re not taking the AI’s idea so much as just using it to spur more creative thinking on your end.

One that’s intuitive and doesn’t require a cheat sheet or what I like to call fingular contortionism discovery.

There is far more nuance in real life than the myopic view your comment reflects. The amount of effort it takes to make a movie is not small. Even low-budget arthouse films take a handful of people to make and those tend to be far less focused on profit than major Hollywood big-budget blockbusters. By logic, this means that there are even more reasons for the movie being made because there are more people involved, each with their own motivations.

Additionally, I didn’t say that money doesn’t play a role or even that it wouldn’t be the primary driver for the project moving forward. What I said was that it’s never the only reason.

Also, there’s no reason to be a condescending prick.

For which there clearly has been. Some people made the various sequels because they had a story to tell, some because there is an audience that wants more from the IP, some because they wanted a chance to take part in such a project, some because they saw them as an opportunity to share their particular craft.

Movie making is a massive group effort. I can assure you that there is not a single movie where the sole reason it gets made is for money. In fact, most of them go into the project thinking it’ll be a losing prospect from an accounting point of view.

Y’all got anymore of that celery?

That’s rad, bro.

The jitters.

Did they stutter?

What are you? Some kind of tape leg?

Why stop there?

Using a well established name for a web-based thing, see gleam.io, is probably not the best idea.

To be fair, schools are not responsible for the availability of the job market.