deeviant

It's 100% a scam, and it's obviously a scam. They are not slowing down their efforts in any meaningful way, just the progress because they are hitting a wall. They want regulatory capture and an excuse to pump the brakes and slow the money burn, even if that is before their models reache even half way up the bar of what they were promising.

And this is coming from somebody who is, as a whole, positive on AI being useful.

Then again, if the only thing the human doing is bitching about AI use, it's not really that comparatively useful.

It's a huge problem, it's just not a problem to economic model, but the ecological one.

Yeah if you are trying to manually validate a firehouse of agent commands you are already losing before you started...

You sandbox, you have good checkpoints, and good agents, that's it. If you are manually reviewing commands you are wasting your time.

I think it's just more about market incentive. At it's core, LLMs are bad for google's previous business model, which was to send you to as many sites 'good enough' for what you were looking for and plant Ad land mines along the way, in the search results and in the websites themselves.

The new paradigm is you ask the llm a question, get the answer and cutout the middle man. (yes the answer may or may not be as good as the old google result, but for the sake of the argument lets say it is), Google was in danger of simply getting their arm cut off. so they focused on scaling so they could add LLMs to the search, which they largely have. You can't offer an opus like model on something as big as search (and which is offered for 'free'), so they focused on that model, and the infrastructure to run it, because they cannot afford to lose search.

Meanwhile, they know the power of frontier models, they are working to have the infrastructure to be a huge player in them and I'm sure they will have a frontier capable model, eventually. They are playing a longer game, because they can, and I think it's going to work out very well for them.

LLM coding isn't even close to plateauing. Right now, the major players are in a consolidation step, focusing more on economic efficiency but still not at the point where we're ready to start burning models to hardware and freezing the line.

They are straddling the line between pushing it forward, and justifying the business case. It's hard to do both at the same time.

Have you people ever read human generated code? Good grief, you act the like human code is not a disaster 9 times out of 10.

It's quite bad at role play in my (rather large) experience.

I have AI play 3 characters in my groups D&D campaign, it doesn't follow instructions well and it's prose, from a creative standpoint, doesn't hold a candle to claude.

It's more like saying, "and you may now only use the Porsche for 5 minutes out of every day."

There are ~7 born per minute. 95% of them are retail investors.

If you want actual reason, it's because he uses it as a money battery, i.e. funding xAI and SPACE DATA CENTERS.

The surprising thing here is that anybody would ever think it was random. Did they not notice the LLM reusing the same names over and over again too.

However, "make my a python script the generates a random password" works.

Skill issue.

Projects that deny AI contribution will simply disappear when an agent can reproduce their entire tech stack in a single prompt within a couple years. (not there yet, but the writing is on the wall at this point).

Whatever the right response to that future is, this feels like the way of the ostrich.

I fully support the right of maintainers to set standards and hold contributors to them, but this whole crusader against AI contribution just feels performative, at this point, almost pathetic. The final stand of yet another class of artisans to watch their craft be taken over by machines, and we won't be the last.

> It was drawing on what gets engagement

I do not think LLMs optimize for 'engagement', corporations do, but LLMs optimize on statistical convergence, I don't find that that results in engagement focus, your opinion my vary. It seems like LLM 'motivations' are whatever one writer feels they need to be to make a point.

I have problem pulled out postgres 10 or more times for various projects at work. Each time I had to fight for it, each time I won, it did absolute everything I needed it to do and did it well.

I can't imagine why you would want a job processing framework linked to a single thread, which make this seem like a paid-version-only product.

What does it have over Celery?