daveguy

But immitating others is about the only thing genAI does. Sometimes "others" is a 'programmer', sometimes "others" is an 'artist', but regardless, it still does it poorly.

Not OP, but I'd settle for something that actually learns, instead of being a static pile of linear algebra. Pretending it learns because you change the input (context) doesn't count.

That Ford story was really misleading. It wasn't about modern LLMs, and the way it was reported implied that Ford had fired and then hired people but if you read closer that wasn't necessarily the case at all - it sounded more like they were re-hiring people who had retired because they needed expertise that had left the company.

Oh come on, Simon. Are your glasses so rose coloured they are opaque? They fired, and then re-hired because the AI couldn't do the job. They had to re-hire the quality folks. So, no, it wasn't LLMs, it was quality control -- which is a much more well established domain for automated systems. LLMs are a complete shitshow compared to industrial process automation.

Side question -- do you worry about being so pro-LLM when the promises of LLMs are so clearly falling short?

Be sure to short the shit out of that company after you leave, assuming something in your employment contract doesn't prevent it (doubtful). Especially if they are software development focused.

Sorry, but labs working hard doesn't make non-polynomial problems suddenly polynomial.

The revolution is way overblown.

Yes, definitely a case of bad-think.

Certainly not double-plus-good like AI.

Dangerous.

Well, it didn't take long for this post to be disappeared from the front page.

Edit: ahhh, I see why. In the list of ways to keep your sanity through the AI mania -- "I no longer visit Hackernews, Reddit, or really anywhere where I am going to be drip-fed nonsense."

The context is the input to the LLM model. It seems like you need to study up on how LLMs work, instead of spouting hype.

Seriously? Supid is literally incapable of learning. That is the underlying model. It does not change, therefore it does not learn. LLM models are quite literally stupid. No one gets a new model no matter how much they yell at it in the context.

You are incorrect. "memory.md" and other context manipulations do not change the underlying model.

Both of those things only happen once by the LLM model provider and not every time a prompt is issued.

I think just the possibility of consequences that they can give a damn about. An LLM doesn't have feelings no matter how much human-like text it can simulate. There is literally nothing going on between prompts for any given model. They are incapable of worry or any other emotion. Wipe the context clean and the LLM is completely unaware there was ever a problem.

Why did you drop the first half of the sentence in your quote?

Because this entire discussion is about the release of a new model, and models are fixed. Sure you can try to modify all the scaffolding around it, but the model is the model. It doesn't matter what you're trying to improve. You can only improve the peripheral aides. And the peripheral aides can't fundamentally fix the problems with llm models when they can't learn new relationships or facts.

You will always have to wait for a new model (like this one we are talking about) for improvements to the model.

The models do not get better until a new one is released. And we are already at diminishing returns. So sorry. Also sorry you don't know the difference between a model and a context, harness, router, or cache.

None of what you mentioned changes the model. Because it's a fixed model. The weights are constant. It does not learn. It only knows what gets repeatedly fed to it and those fixed relationships represented by the weights. You can pretend like that's not true, but unfortunately for VCs it is true.

End of discussion.

Neural plasticity is real, and something LLMs are incapable of. So sorry.

Often yes. In this case, it's more like they get upset when someone says something factually wrong, and then defensively changes the goalposts.

Oh give me a break. Show me one example of 1) any knob twisting that makes the underlying model better. or 2) any example of the AI providers twisting those knobs to do anything other than degrade performance for their own bottom line or safety.

The current post says: "it would be expected for a better model to use different amounts of brevity if it gets better at determining the appropriate amount."

When no, the model cannot "get better". It doesn't determine any appropriateness of response realtime except for the weights baked into it from the beginning and whatever context it can muster. If you cram enough guidance that it doesn't decide to ignore maybe you can make it more brief. But it (the model) can do none of those things.

LLM models are literally stupid by design.

Right. They can do all those things. And none of that will make it smart or able to learn new things. The underlying model is just an llm. But judging from the downvotes, it seems AI folks get upset when someone talks honestly about their precious piles of matrix multiplication.

It was edited. Original talked about the model learning. Glad they managed to clarify. Because the models are quite literally stupid.

The models don't get better, except when a new one is released. Their performance depends solely on the model training before release and how well you curate the context you feed it. That's it. Contrary to popular belief these things are not intelligent.

Can we turn off the whining bitchy little comments like yours along with the political commentary? That would be great.

Did you honestly think the mechanazi / porn generator AI wouldn't receive negative comments? Even "hardcore nerds" recognize garbage. Sorry 'bout your luck.

I doubt you can turn that off. That's how they upgrade it up from a tool to an engagement optimized addiction platform.

Or, phrased another way: there's a reason why we consider basic availability in nines and 2 nines is still considered pretty bad. 99% uptime means being down over 7 hours each month.

Russia is a paper tiger.

That's not how mantle3d works. It's 3d printed metal alternating with CNC machining after several layers for precision:

https://mantle3d.com/how-it-works/

This is optionally followed by a pressurized furnace for sintering.

Yeah, big 'ol asterisks in this "world air speed record". This is for electric-powered flight, and is equivalent to 57% of Mach-1.

Bottom-line win-win! All hail the shareholder value!

Or it's just plagiarism, eg "windows blinked awake":

https://web.archive.org/web/20190825132048/https://patriciae...

See also "wind moved restlessly", "weather became angry". And raging storm? I mean come on... I won't even put that last one in quotes.

And like a sibling reply pointed out, personificiation is not the same as anthropomophism. Nor is plagiarized personification. It has no inner thoughts, and no fondness of anything. It's nothing but a cheap, superficial facsimile of human writing and nothing more. Great for form filling and boilerplate though. Not so great for anything else.

It's because the first sentence of the American Society of Civil Engineers code of ethics is:

Members of The American Society of Civil Engineers conduct themselves with integrity and professionalism, and above all else protect and advance the health, safety, and welfare of the public through the practice of Civil Engineering.

The first tenant of a software engineers code of ethics is:

fuck it, make the boss some money.

Or, formally, according to the ACM:

Contribute to society and human well-being.

Which means fuck-all and includes absolutely zero enforcement like it does for real engineering professions. So do us all a favor and don't whine about our discipline's lack of standards while dipshits who call themselves software engineers are tokenmaxxing a pile of shit and SEO optimizing manipulative user environments for profit.