It's already being trained on "public" (ethical or otherwise) data. So, it already has ingested that kind of "optimization" during pre-training and training.
I don't think you can fine-tune your way out of it.
It's already being trained on "public" (ethical or otherwise) data. So, it already has ingested that kind of "optimization" during pre-training and training.
I don't think you can fine-tune your way out of it.
People still think these things are smart. That if their word generator eats enough of the Internet, it will somehow give them the real information that's otherwise hidden. Or perhaps a better word; filter the bullshit.
To filter bullshit it would first have to understand bullshit, and it doesn't. That's why an LLM will tell you the solution to a problem that doesn't work, and argue with you when you correct it.
Sadly critical thinking skills have atrophied steeply in the last decade.
This is what bothers me a lot. For the people who doesn't know how it's made or want to believe, it's a miracle.
For me, it's a resource wasting text generator. I'll not lie, I don't use OpenAI, Mistral or Anthropic's models, even for coding. I prefer to read my API docs and cry once.
I used Gemini, five or six times in total. Twice I asked a couple of very specific things, and it unearthed them. Since they were not products, but information, that was helpful. Twice, it has given wrong information. When I "told" it, there was another way, it said "of course there are two ways", etc. Tasteless and time wasting.
I don't like using an LLM all day long, or offload my thinking to them. It's the ultimate self-poisoning incident.
And as you say, these algorithms can't know right/wrong/logical/bullshit, etc. They just spew out text.
I was just reading another post yesterday and your comment reminds me of this one [0], same sort of format and experience of the submitted article of the HN post that comment is on.
[0] https://news.ycombinator.com/item?id=48211730
Something I’ve also seen multiple times is an LLM giving wrong information, I tell it it’s not right, then it tells me I’m “absolutely right” and it provides the exact same answer and tells me that one will work.
This is far from widespread at the moment, so it'll be possible to at least use the current cutting-edge models locally in the future.
Far from widespread? SEO has seeped to all crevices of the internet for the last 20 years.
By this measure, any information you can get whatsoever is biased and there is no reason to trust anything at all.
All information has some sort of bias, as no information can truly be unbiased. There is no reason to trust any specific piece of information but taken in aggregate one can disambiguate the biases.
So we are in agreement.
The major difference is that right now when you land on a page you can do your due diligence and decide if you trust the source. You can still be tricked, but it’s harder and you can get better at the detection.
With LLMs, everything is given the same importance so you have no idea if the data came from a reputable source or an obvious SEO junk website.
AI can also provide the sources. And if you need to be certain, you should ask for that.