The big downside that keeps me from using it is that you need to whitelist the contacts you want to be able to call/text, and can’t add new contacts in assistive access mode. Sad, because it otherwise looks perfect as a distraction minimizer.
I’m a musician. For the vast majority of colleagues I know (classical), having to use docker will make it a non-starter. But I’m also curious what your app does, if you don’t mind sharing details!
It's basically a lyric video generator. Right now I'm processing the lyric transcription on a server, but I'd rather users do this locally so I don't have to spend money on that.
I've actually made a few lyric videos with my own music, but I just don't want to have to manage the data of other people.
It’s a good hypothesis. Anecdotally though, I know a bunch of people who have experience playing both, and say that the old instruments can be difficult to play, though sound amazing when played well.
Part of the problem is the potential loss of public value in the form of the undigitized archive, and archive.org provides no solution for that.
Now, is it the responsibility of organization X or person Y to preserve this value? I’m not sure, but that seems to be a separate (albeit also interesting) question.
Hah, I flew planes into ceiling fans too! I also remember scraping my planes against the floor until holes wore into the paper, and seeing how well they could continue flying. There was something really cool about seeing a plane with so much accumulated damage still able to fly.
Is this the type of reasoning that could be used to basic math without errors (without using a dedicated math engine)? I wonder why that type of reasoning seems to struggle.
I think chatgpt is interesting in its ability to highlight the subtle variations in a concept we tend to think of as more of a single attribute (e.g. reasoning) because humans tend to do certain types of reasoning tasks at the same relative proficiency as others. No human can write complex code without being able to add large numbers, so they are often lumped into the same skill category.
I think there just isn't enough mathematical data. English language data is magnitudes more and longer then mathematical data so there is a correlation here.
The more data the better the LLM can formulate a realistic model. If it has less data then the resulting output is more of a statistical guess.
There is an argument that can be made here that the more data the more things chatgpt can copy and regurgitate but given how vast the solution space is I think data at best covers less then 1 percent.
Basically I think that if your data covers say 2 percent of the solution space you can generate a better model then if the data covered 1 percent.
For guis in general, I like how the actions available to me are much easier to learn, and therefore use. The information conveyed through the layout often provides context for related actions.
In my experience, CLIs are great for efficiency, if I am doing a task so often that it becomes rote behavior and learning the tool is no longer helpful, or if I want to automate it. I find my real world need for either of these to be relatively slim, but I am not surprised that it is common for others.
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