Sounds interesting, thanks for the link. It's a little over my head tbh but I'll definitely take a closer look.

I'm not aware of any realistic way to vet published model weights like that.

It works for some open-source software, because you can download the source and compile it yourself. But most of the "open" models don't publish their entire training set, or enough details on the training for it to be truly reproducible. DeepSeek doesn't publish their data sets, and they probably couldn't, legally, since they "collaborate with third-party data providers to obtain proprietary datasets". And even if they did, it would be prohibitively expensive to train it on your own, unlike simply compiling open-source code.

The actual code for training LLMs is relatively trivial. The secret sauce is the training data and fine-tuning.

It's still a risk. You can train an LLM to respond maliciously to a very narrow range of requests that would not be easy to spot in general testing. If you know how the LLM is used, you can target that very specifically. It doesn't have to be as blatant as "always deny the Tiananmen Square massacre ever happened".

Given how thoughtlessly people use AI, and how opaque some of the systems are, I think this is a legitimate concern.

And yes, every government outside America should ban the use of ChatGPT and Claude. Obviously.

Yes and yes.

I don't think TikTok is really comparable though, unless there are somehow people using it for important government work.

Honestly, reasonable.

I mean, I sure don't trust OpenAI or Anthropic any more than I trust DeepSeek, but that's because I don't have legal control over them. The US government does, and it is correct to ban tools that are controlled by adversaries.

They tested the fan on a sailboat on MythBusters, and were shocked that it actually worked. https://mythresults.com/blow-your-own-sail

It didn't work well, but it did work.

It's a matter of degrees, and of use case.

If your use case demands 100% accuracy, that's a dead end.

If you can't validate the output, then you need to go back to the drawing board.

I keep going back to the same rule of thumb: if you can't do it without AI, you can't do it, period. It's a time saver, not a magic wand.

If you're not an idiot, and you (nevertheless) use LLMs, they probably meet most of those criteria.

I don't like how the author buys into anthropomorphization. LLMs do not act on their own.

He's right that tools don't "go rogue". Neither do LLMs. That's just a lie to try to avoid accountability. ChatGPT didn't hack the Australian government; PEOPLE did, and those people belong in prison.

No problem until they make every other method more and more difficult. Which is already happening.

I only use passkeys when the alternative is an onerous song and dance.

I mean in great volume. I know AI video generation exists, but it's not very common compared to text, images, or music.

Just wait til AI video catches on.

If we're lucky it will also come with an improvement in video compression. But probably not, and new video codecs typically take 5-10 years to catch on anyway.

I've been lucky with my upgrade/build timings. Built my first PC right before the crypto madness, and did my last major upgrade right before the AI madness.

I'm going to run my current system until it crumbles to dust. With any luck, the market will have settled a bit by then.

As for projects, I have lots of old "useless" tech that I can work with. Like old laptops, phones, Raspberry Pis, even mobos and other spare PC parts. Building small is more interesting to me than building big.