hdsrob

u/hdsrob@lemmy.world
1 posts · 170 comments

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Absolutely. ...

I own a software company, but we sell computer hardware to about half of our clients as well. We passed the increase in hardware to our clients as our suppliers passed it down to us.

But I'm not an importer, and my main supplier imports about 50% of what we buy from them. The rest they buy from manufacturers that import their own product, or importers (or possibly even wholesalers that buy from importers), and we buy some stuff at retail, since we just don't need.

We absolutely struggle to be competitive, and more so now than before. We don't have VC money, or credit card processor backing that many of our competitors do, so can't give hardware away at below cost, or for free. At the end of the day, we decreased our markup to help keep prices down, knowing that we'll ultimately make it up on software licensing over the next few years.

Even then, our customers are all businesses that paid the increased tariff at the end of the day, so how do they get their taxes back, since most people are suggesting returning taxes to individuals.

The whole thing is a freaking mess, without any real good answer that will actually make everyone happy.

I don't think that the government ever promised a tariff rebate to residents directly.

The rapist or Musk may have offhandedly suggested on social media that they would, but anyone that believes anything they say is a fool.

Most don't even directly pass the cost to the consumer, they pass them down the line to retailers, wholesalers, manufacturers, etc.

Then those companies add the additional cost to the product as the sell them .... So only the importer is getting the refund, and only a handful of very large resellers are actually importers. Most small businesses buy from importers or wholesalers, and they won't get anything back either.

Agree that he puts on an incredible show. Definitely worth catching him if you can.

I've been a fan since I was a kid in the '80s, and my sons both liked him a lot (my youngest has all of his albums).

We saw him on the Poodle Hat tour, and it was a really great show.

I spent time over several months hand deleting my post one by one, and they don't show up for me.

But one time after deleting them, someone replied to one of those deleted posts, so I think they're visible to others, but not to me anymore.

on 🏭🏭🏭 · c/lemmyshitpost · 30 pts · 5d

Same here ... after two boys (and a few years to think about it), I had a vasectomy.

Have two granddaughters now though, so the wife gets to do all the girl stuff she missed out on.

on Tortilla pizzas · c/cooking · 3 pts · 6d

We used to make those all the time: I probably got the idea from a South Beach or other low carb diet site 15+ years ago. I had totally forgotten about them.

With the right size tortillas you can also do them in a toaster oven.

We still do flat bread (naan) versions of these. I start on a round cast iron griddle on the stove top, and let the bottom crisp while building the sauce and toppings, and then throw them under the broiler for a few minutes. I bet the tortillas would be just as good that way.

Both versions are handy when not everyone wants the same toppings (kids or grandkids) since each one is basically a personal size pizza.

I think the fundamental difference is that a human trained on something isn't likely to reproduce the thing they were trained on exactly.

I know that some research I read a few years ago showed that LLMs generally produced novel text (rather than simply returning verbatim training material), but that that wasn't always true, especially as the training sample got smaller, or a single training text got larger (something like a 1000 words).

So sure, for something simple like creating super standard CRUD or basic API endpoints in common languages, the sample size is significant enough that what you get is likely to be homogenized from thousands of samples available, and not likely to be an exact copy of someone else's code. But the risk is that as the problem being solved gets more niche, and the training sample size gets smaller, you become more likely to get exact copies of someone else's code, or something close enough that it might be considered plagiarism.

There's also still grey areas where some courts in some areas have stated that LLM generated content can't be copyrighted, since a human didn't create it, creating issues with protecting sources with copyright.

IMO proprietary code has this same risk.

I have non FOSS projects that my company writes / sells (I've written these for over 20 years, but only owned them for 3, and opening the existing source is complicated as it's tangled deeply with non OSS projects).

I don't allow LLM generated code in our products either, since I have to assume that most of training was done on public repos, and there's no way to know what licenses existed on that code (in addition to all of the other valid arguments to not use that shit).

Repetition is key here. And solving problems.

I started many years ago with a "for beginners" book, and didn't fully understand a lot of it by the end.

So I started trying to build something, and searched for answers to the things I couldn't figure out (and went back to the book numerous times). I don't think I ever finished that project, but by persisting through it, and figuring out how to solve the problems that I ran into, I learned how to build something, and it stuck.