local LLMs aren't there yet and probably won't for the forseable future for ordinary people. If you want to run a full model like DeepSeek v4.1 Flash, you need something like half a TB of RAM.

The open-source LLMs are a different threat: They enable a service industry independent of the large players. I could today get some venture capital, rent a few racks in a hosting center, install a bunch of beefy machines and offer the same service as Claude or ChatGPT, just on an open-source model. The differences in benchmarks are becoming irrelevant for 95% of common use cases. And if I can offer that service for $19/m while OpenAI wants $29/m then OpenAI has a problem.

And IMHO this is the chinese strategy: Undermine the US AI industry by breaking its business model.

Has everyone gone insane or are we witnessing a major PsyOps ?

Since AI isn't magical, for it to be able to "kill all humans", it would have to be able to acquire the means to do so. Which means that these already exist. It means someone is able to do it right now. And we're chill with that, but worried about AI?

No doubt a bunch of autonomous weapon systems linked into a C&C could cause considerable bloodshed. Given that most of the existing weapon systems of that kind are essentially suicide drones, it'll still be limited damage.

Human-killing virus? Still need a means of creating and delivering it.
Nuclear war? We have humans in the loop.
Drive us all insane with AI-slop TikToks? A few percent of humanity still don't use that.

So what is the actual scenario ? When someone shouts "AI will kill us all", why don't we ask them "how, exactly" ?

Popular opinion is poor evidence.

It's a research program so, yes "That doesn't mean LLMs *will* deliver AGI". But what are your grounds for being certain taht it won't?

Even if it were sentient, it would be acting as the agent of the company that was running it, so they would still be to blame.

If you don't like "reward", say "positive feedback". It means the same thing, except for being more formally defined.

LLMs cannot have inherent values, because they don't know that anything besides text exists. Specialized pixel editors have similar problems.
Robots will at least understand the the external reality exists, so perhaps they could have inherent values.

If the toaster has good brownness and heat-bounce sensors, I'm not sure AI is needed: just turn up or down the heat cells where needed to keep it even. Statistical analysis may be needed to manage adjacent cells, but once the formulas are known via lab testing it should be predictable.

nuf smelt.

The problem is an overly large proportion of them are creeps, and one may not be able to tell the difference.

...makes me want to buy it.

If things were to otherwise stay the same, then it would. They won't. Some descendant of "vibe coding" will become the dominant mode within 20 years. Probably a *lot* sooner. Next year wouldn't really surprise me.

Also, Rust is more complex to use than C, so a small program is much better in C. And a large program is probably better in either C++ or Python(with a lot of library calls).

I don't like Rust, so I'm probably not being fair to it, but I struggle to identify a good use case. (Personally, I'd rather use Forth than Rust.)

Note however "will be", not "is". It's not there yet.
Then you have the problem of getting the right standards.
Then you have the problem of getting the right specs.
Then you have the problem of getting the right problem. ...
There's probably an end to this somewhere, but I doubt that it will be in perfection.

Nobody can write safe code. People, can, however, test the code they write, and if there is a comprehensive test suite, fix it so that it works safely. Debugging is mandatory!