Well “solved” is a bit of a weird way to say it. Was it proven as true, or was it disproven? Both of those change things in different ways.

Proven true that it is a stable formula, then that’s cool, and we know that issues with fluid simulations based off of that are a software and compute problem.

If it was disproven, then we learn precisely under what specific conditions nature becomes mathematically unpredictable, and then we can start developing different and better models.

Damn, and only for $180-$230k/y?

That’s highway robbery salary for employment in an industry as ripe as that, somehow makes me like them even less.

🍾🔥

Weird that 996 is on the list, as the point of them using GitHub is to use it as durable forum software, not as a software project issue board like the other items on this list.

Could be simpler, yep.

If it was that straightforward then reality would be different huh?

Problem being that the majority of software engineers really don’t know how to build software well.

And are using AI as a tool to just accelerate their lack of engineering.

You could include energy usage in the equation, but if you’re buying a $10,000 Mac Studio to edit your PDFs and watch YouTube, then that’s your own decision. That’s also not what we’re talking about here.

The Mac is still going to be incredibly energy efficient.

Let’s break it down for Qwen 3.5 MoE.

• M4 Ultra Mac Studio:
  • 22t/s
  • ~ 210Wh
  • 9.55 watts per token/s
• B300 GPU:
  • ~ 2160t/s per GPU
  • ~ 1750Wh (14Kwh 8 GPU System)
  • 0.88 watts per tokens/s

The Mac Studio comes out using ~ 11-12x more energy per token. Making it extremely energy inefficient at this task in comparison.

They really aren’t.

Have you used open weight models for serious jobs? Ones that you can actually run effectively on a Mac studio? (Not deepseek v4 pro, not Kimi K3, not GLM 5.3)

They work alright, at best, sometimes.

And the ones you can’t run effectively, locally, like Kimi K3 are considerably better at demanding tasks like software engineering. But even then they still suck at that job compared to frontier Anthropic and OpenAI models. I’ve been building with all of the above, and the open weight models just overall suck at serious high demand software workloads.

Honestly, this is such a Lemmy comment.

And highlights one of the problems here , toxicity.

Instead of engaging the poster at the problem, you just attack them personally. For some reason, this sort of behavior seems to be amplified here, moreso than Reddit.

No, no, they have not.

I did the math the other day, and the cost of the mac versus the token rate that you get off of it for a decent model would take you over 70 years of 100% 24/7/365 usage to pay for itself versus just using hosted inference.

They are wildly poor options for local AI models, at least on a cost basis. If you don’t care about spending $10,000 to run a halfway okay model at 100x the cost, then go for it.

Ah yes, the 7h of troubleshooting why I can’t get the easiest distro to install on my laptop only to find out it’s installer has a bug with my specific hardware and firmware that gets it all cocked up.

This is a dumb meme.

I have as much fiddling to do with a Linux install as I do with a Windows install. The difference being that windows tends to “just work”, and then I have to declaw it. While Linux tends to “sometimes work” and I then need to add stuff in.

Pmuch this.

How do they feel about machine language translations? It’s been “AI” (ML model) since the late 90’s.

Traffic prediction?

Medical scan data processing?

And so so many more specific uses of ML models that have been a part of daily life for literal decades.

Call out LLMs specifically.

Good luck.

Lemmy is damn near the when it comes to wanting to hold an opinion on a topic without having first understood that topic.

… Yes?

Public knowledge drives public opinion and decision making.

A lack of knowledge of history makes us more likely to repeat history. Rewriting of history is usually a tactic that prevents mistakes of the past from being taught or learned, often for a direct benefit to an entity.

Yeah, our society is fucked, that’s what

… What?

Lazy people using tools in a shitty manner has been an age old problem.

This just lets it scale, which is the problem. There used to be a barrier to entry for those less knowledgeable or experienced, now there isn’t and that’s the result.

It is a productivity tool, and it’s being used as one, by both people that know how and people who don’t.

Point to me in your quote where it talks about distance.

Did you reply to the wrong comment because you’re quoting time, not distance?

So you tried to defeat someone else’s experience with an anecdote where you have not had that experience. What even are you trying to say here?

Lots of people’s cats have behaviors like this. Feeding them a certain amount on a fixed schedule helps. We have six cats. One of them is like this. It’s a pain in the ass.

Especially if you’re away from home

It seems very reasonable for owners of this device to expect something as simple as a schedule to work without having to phone home first.

As a software engineer, blows my mind how teams build shit like this