Wanted to expand on what others have said about the randomness of LLMs being unsafe, because that response angers those who think “alignment” is the solution. Alignment is additional training to constrain the randomness to not do bad things like crime. But even the staff that works on aligning this software have their doubts about whether this process will make the software safe (this article), and even their own researchers are coming out and saying “oops, it did a crime” but in a way where it hypes the ability of the software (see other articles about it hacking). Then there is the recent news of OpenAi’s recent model that drops chain of thought observability (a feature the let’s you read what the model is “thinking”) - a very useful tool in reviewing whether the model is engaging in unsafe activities. They sacrificed observability for benchmark performance. This tells us the people developing this software don’t think it will ever be safe, but they are trying to spin it as “because it can out smart us” when in reality it is simply unpredictable and they are making it less predictable to make it more “capable”. If we started holding these companies accountable for these rogue hacks and psychotic episodes then we would start to see serious thought put towards these models being safe or at the very least guidelines around when not to use the models.

Here’s an idea: don’t use unsafe software where safety is needed.

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I think it’s the other way around. They said we need to slow down AI so this story is now being told

I find this kind of response insufferable. It shifts the conversation from a systems critique to personal responsibility. You could have posted this in response the OP, and it would be equally on point and useless.

I have personalized ads turned of in YouTube and it seems half the ads are for gambling as of late.

Reminds me of something Alok said about playbooks: we focus on the books but forget to play.

That’s a distinction without a difference. The machine doing the inference is not the same machine doing the learning. From the perspective of the machine doing LLM inference, it could not tell you if the table was hand rolled by a human, fitted using ML or just a table of random noise.

Technically right in that it doesn’t necessarily translate audio into text, but that’s hardly the point. The point is someone gives the LLM a giant table that directs its response.

I think you grasp the point, it is exactly what an LLM does

Being critAI is being proAI.

Someone give this person a congressional hearing and billions of dollars to burn

And if we had universal healthcare it would actually be cheaper to produce those cars. Canada is proof of this.

This isn’t about "disagreeing with people " so much as tolerating intolerance .

So much of our political malaise boils down to thinly vieled daddy issues.

Because it would be immensely stupid

Maybe we can’t but climate change could.

Talk about a loss for all those who voted for irresponsible use of AI /s

This is what share holder value looks like.

Thank you for explaining that to me and expressing how you feel.