2,205 karma · joined March 22, 2012
That said, this is cool and I would have probably celebrated a similarly fun project in their shoes. Perhaps the real accomplishment here is getting Toyota to employ you to build a new, niche game engine.
This may say more about how people interpret you, personally, than about the situation generally.
The Venn diagram between people who shop at dollar stores and people who shop at Costco isn't empty.
Automobiles are large, expensive purchases with a relatively small set of options though... For most purchases, it's impossible to determine quality ahead of time.
The difference is that a human can learn and grow.
From your examples, it sounds like we're talking about completely different applications of code. I'm a software engineer who is responding to the original topic of reviewing PRs full of LLM slop. It sounds like you are a hobbyist who uses LLMs to vibe code personal apps. Your use case is, frankly, exactly what LLMs should be used for. It's analogous to how using a consumer grade 3d printer to make toys for your kids is fine, but nobody would want to be on the hook for maintaining full scale structural systems that were printed the same way.
It is not a worthwhile use of my time to similarly "coach" LLM slop.
The classic challenge with junior engineers is that helping them ship something is often more work than just doing it yourself. I'm willing to do that extra work for a human.
No, not if I have to maintain it.
Code is liability. LLM written PRs often bring net negative value: they make the whole system larger, more brittle, and less integrated. They come at the cost of end user quality and maintainer velocity.
The suggestion that the only alternative to paying $96 million AUD ($62 million USD) for a website is getting one that was "coded, zipped, and mailed" is absurd.
> That's why you have thousands of employees in tech companies with seemingly a simple product that you can fully code in a week(at least the user facing part of it).
I've worked at Salesforce, Facebook, and Adobe. I couldn't code even the thinnest sliver of a vertical slice of any of their products in a week.
A quick check of just one of your examples shows the term "3d printer" is googled for literally twice as frequently today as it was in 2016, for instance.
A class 1 e-bike is pedal-assist and stops assisting beyond 20mph (mine, for instance, tapers off starting probably around 15 mph).
A class 2 is the above, plus a throttle.
A class 3 is anything that assists over 20mph. The "basically motorcycle" set exists here.
However, I do judge adults who aren't in good circumstances who also decide to bring children into their hardship. I have two kids, which is the most I felt I could provide for (time, money, attention, energy, etc).
You should check out the xreal one!
That's the worst, most tortured string of English I've read all month.
This leads to incredibly efficient, dense semantic consistency because every object in an image is essentially recreated from (intuitively) an entire chapter of a book dedicated to describing that object's features.
However, it loses direct pixel reference. For some things that doesn't matter much, but humans are very discerning regarding faces.
Chatgpt is architecturally unable to reproduce exactly the input pixels - they're always encoded into tokens, then decoded. This matters more for subjects for which we are sensitive to detail loss, like faces.
That hasn't been my experience. I suspect that most others who also daily drive linux would find it remarkable if someone used Linux every day for a year and never needed to open a terminal to install anything, fix anything, reset anything, update anything, follow any instructions given by any software they found and wanted to use, etc.
Definitionally, it means you're hiding (non-disclosing) features behind at least 1 secondary screen. Usually, it means hiding features behind several layers of disclosures.
Making a very simple product more powerful via progressive disclosure can be a good way to give more power to non-power users.
Making a powerful product "simpler" via progressive disclosure can annoy the hell out of power users who already use the product.
AI is good at local coherence, but loses the plot over longer thoughts (paragraphs, pages). I don't think I could identify AI sentences but I'm totally confident I could identify an AI book.
This includes both opening a large text in a way of thinking that isn't reflected several paragraphs later, and also maintaining a repetitive "beat" in the rhythm of writing that is fine locally but becomes obnoxious and repetitive over longer periods. Maybe that's just regression to the mean of "voice?"
But clearly it's happening, so I'd like to understand better the venn diagram of people who have $20k completely disposable and people who are so highly motivated by their appearance in a video game. My assumptions are obviously wrong.