cryogenicfire
For writing tasks, I haven't been able to use it effectively for most tasks. It does fine on creative tasks but it doesn't really produce anything impressive enough to be middleware for writing. It's fine for writing emails and stuff though, just that I am not writing enough emails in a day for it to be a notable part of my workflow. I also don't like using it for technical writing. Expanding or rewording on technical content often leads to strange sentences, mostly because it tries to synonimize technical words that ideally shouldn't be tampered with in such a corpus... Maybe some better prompts would help with this, but I haven't had the chance to experiment more
I also tried it as a brainstorming tool, to try and pull out new ideas or to hold "discussions" so to speak. Again, it isn't bad at it, but often reverts to generic responses or occasionally repeats itself and it's just not efficient nor consistent enough for being a regular tool for this
The one thing that these models are exceptionally good at, however, is giving great overviews and explanations on concepts. It probably won't help you much if you are asking highly detailed, convoluted and specific things but they are amazing at "skimming" information. Like another user mentioned, it's good for obtaining domain knowledge on topics you're unfamiliar with. Kind of like a headstart for your learning process. I've found it very useful to get a general notion of "where to look" when I want to learn something new or run into hurdles on a project.
But hey ultimately I just think people should satisfy their curiosities. My work is often always in Python, JS or Java, but at some point I got tired of just doing regular software development stuff and lately I've happened to gain interest in low level development. (Like any definitely sane person I chose to start with rust and decided my first ever rust project should be an emulator, so maybe I'm just dead inside and I don't know it yet)
1. To be faif, these kinds of "hacking" projects aren't technically meant for learning software engineering in the context of a job, but they are really interesting and a treasure trove of new knowledge for anyone willing to put in the effort. I don't think it's a bad thing. A person can learn to be a good software developer and simultaneously have deep knowledge of the systems they are working with.
2. The goal of this project is not to research and implement some novel algorithm to replace existing works. The goal is to learn how things work. You are still going to use libraries, procedures and algorithms designed by other people and compile them into a cohesive system, it is merely the depth and complexity of the problem that makes it an interesting learning challenge. It's not about some absurd NIH philosophy, it's about curiosity.
3. Software development is not as straightforward as you make it seem. It's not just about best practices, management and finding an optimal way to combine existing libraries into your project. Sometimes you run into unforeseen issues, strange niches that your libraries may not account for. Sometimes you need to dive into the specifics of these libraries, understand at a lower level why they do not function for your use case. You might need to "hack" these libraries. Fork and customise them to truly fit in your project and produce the desired results. And the only thing that will help you then is deep knowledge and the ability to work with low level software.
... Anyways, my point being that Apple will gladly introduce a polished product a couple of years after everyone else has already done it, and their target audience will still applaud their work and give them money. Apple for some reason simply _can_ afford to test the water
Maybe they can just afford to observe before making major decisions on the direction of the company... For a company like Apple, I feel like they won't lose their customer-base just because they are taking the AI race slowly, in fact Apple has often been late to introducing very common feature