When I was growing up (millennial) it seemed to me that the default for smart young people drawn to technical problem solving was something like aerospace, software or hardware was more or less a fun hobby, like it was for Steve Wozniak. Nobody cared whether or which of these were a commodity, which is what happens when you actually enjoy something.
These days I do see a lot of people choosing software for the money. Notably, many of them are bootcamp graduates and arguably made a pivot later in life, as opposed to other careers (such as medicine) which get chosen early. Nothing wrong with that (for many it has a good ROI), but I don’t think this changed anything about people with technical hobbies.
When you’re young, you tend not to choose the path the rest of your life will take based on income. What your parents want for you is a different matter…
Could you elaborate on this? I can’t tell whether you mean to say that open source projects run into user-initiated time sinks that detract from their productivity (which is arguably the case for any public facing project), or whether private repositories bypass this type of scrutiny by default which affords them an advantage, or whether this is about the Stoat/Revolt devs specifically and how they choose to spend their time.
I think the parent comment is referring to the fact that even focusing on whether ~100 lines of code across 3 commits should/should not be generated by an LLM is meaningless bikeshedding which has no place in a serious project.
Initially named Revolt then renamed to Stoat due to a cease-and-desist. Both awful names. (Granted Discord is not a great name either). In their docs and website you'll still find a mix of the new and old names.
The project is ~4 years old. Screen sharing is still a work in progress. It's been a while since I tested it myself but you can still see plenty of reports of it being buggy and slow.
Basically it gives of major bike shedding impressions.
I looked into AI scribes when they were new, finding them interesting, and spoke to many doctors. Across the board, the preference was for a human scribe, the reason being that they actually take away cognitive load by learning to work with you over time, to the point where eventually your scribing problems are wholly solved by having them around and you need not think about it.
AI scribes have their place since many doctors and nurses can’t afford a human scribe, but as of now they don’t *replace* people. They’re a tool that still needs wielding, and can’t be held accountable for anything.
The original [0] that this is in response to, essentially posits that something you cannot afford to ignore is going on, especially if you work in a white collar job. Admittedly a little bit of FUD [1] is going on with the "AI is coming for your job" narrative, but the core idea, that this is a fast moving field where it's worth re-examining your assumptions from time to time, appears to be sound and hard to disagree with.
This article has a confrontational title, but the point made here seems to not be incompatible with the original...the author is confronting the FUD directly, which is understandable but perhaps not quite as useful as refuting the core thesis, which is that something you cannot afford to ignore is happening.
In fact, both these people seem to be in agreement that you need to keep an eye on this ball, they just have a "panic" versus "don't panic" framing. Should you panic in an emergency? Research says no [2].
As far as these model releases, I believe the term is “open weights”.