Finally companies understand that consumers do not want AI products, but just better, stronger, and cheaper products.
Unfortunately investors are not ready to hear that yet...
Unfortunately investors are not ready to hear that yet...
I can see a trend of companies continuing to use AI, but instead portraying it to consumers as "advanced search", "nondeterministic analysis", "context-aware completion", etc - the things you'd actually find useful that AI does very well.
Anyone technical enough to jump into local AI usage can probably see through the hardware fluff, and will just get whatever laptop has the right amount of VRAM.
They are just hoping to catch the trend chasers out, selling them hardware they won't use, confusing it as a requirement for using ChatGPT in the browser.
But when I come on HN and see people posting about AI IDEs and vibe coding and everything, I'm led to believe that there are developers that like this sort of thing.
I cannot explain this.
But the fact remains that I'm producing something for a machine to consume. When I see people using AI to e.g. write e-mails for them that's where I object: that's communication intended for humans. When you fob that off onto a machine something important is lost.
It's okay, you'll just forget you were ever able to know your code :)
But I wasn't talking about forgetting one language or another, i was talking about forgetting to program completely.
this is their aim, along with rabbiting on about "inevitability"
once you drop out of the SF/tech-oligarch bubble the advocacy drops off
That usually means you're missing something, not that everyone else is.
The guy coding in C++ still has a great job, he didnt miss anything, is all fucking FOMO.
I've also had luck with it helping with debugging. It has the knowledge of the entire Internet and it can quickly add tracing and run debugging. It has helped me find some nasty interactions that I had no idea were a thing.
AI certainly has some advantages in certain use cases, that's why we have been using AI/ML for decades. The latest wave of models bring even more possibilities. But of course, it also brings a lot of potential for abuse and a lot of hype. I, too, all quite sick of it all and can't wait for the bubble to burst so we can get back to building effective tools instead of making wild claims for investors.
"This package has been removed, grep for string X and update every reference in the entire codebase" is a great conservative task; easy to review the results, and I basically know what it should be doing and definitely don't want to do it.
"Here's an ambiguous error, what could be the cause?" sometimes comes up with nonsense, but sometimes actually works.
I never use LLMs