[Eufrat]

I feel like the promise of these models is to help people make more informed decisions. Improving the knowledge economy and general understanding.

The problem is these are just statistical models at the end of the day, so you need to know something to be able to identify the errors. You can’t let them really be autonomous and you also can’t really have people turn into glorified approvers. If the machine is correct 89% of the time, you cannot make people responsible for that 11%. It’ll just cause automation fatigue.

tl;dr: the actual use cases of these LLM (or generative AI in general) is rather limited, so it is offensive how much hay has been given to them eating the entire capitalist system. They are not fit for purpose.

[anon84873628]

Why should we not expect a computer vision model to outperform humans on reading medical images?

The human experts are literally just a trained biological neural network. In this domain they are not capable of anything a computer can't already do.

[Eufrat]

> Why should we not expect a computer vision model to outperform humans on reading medical images?

Humans can identify. A computer vision model can return a statistical value. Both can make errors, but these errors are orthogonal to how we work and what is being asked of them. I think a CV model can absolutely provide value as augmentation. Identifying possible misses or a different diagnosis worth considering, but that is not what is being asked of them here. The pitch by Altman and Amodei is not to say, “This tool that might cost $1,000/month can help increase the accuracy of your diagnoses by 10%,” instead it’s, “This tool can allow you to keep 10% of your workers to monitor it and you can fire the rest. Also, the workers carry all the liability.”

> The human experts are literally just a trained biological neural network. In this domain they are not capable of anything a computer can't already do.

People need to stop making this baseless claim. Human beings are not stochastic computing devices, we are not neural networks. We don’t fully understand human cognition and intelligence. I have the highest confidence we will figure it out one day, though.

Yes, neural networks were based on a superficial view of the human brain, that’s it. For instance, it is biological impossible for the human brain to do backpropagation, which is kind of important for a modern neural net.

This really rubs me the wrong way because it's objectively false, but people keep bring it up because I think people want it to be true rather than accepting generative AI for what it is: a tool with a bunch of caveats.

[augment_me]

Whether brains do gradient descent is irrelevant to a CFO deciding whether to staff one radiologist or three. The market doesn't care if the model "identifies" versus "returns a statistical value", it cares what the error rate costs versus what the salary costs, and it prices liability into contracts either way, same as it already does with autopilot and compliance software.

Also disagreement among human radiologists has been documented for decades, so the clean expert baseline you're defending doesn't actually exist outside this argument.

When the identifiers pass human-detection-rate percentages, it will most likely be cheaper to hire a fall-guy for the liability with a much smaller salary, I think this will be a big market in fact.

[anon84873628]

Thank you. I think my comment was careful to specify "in this domain" and "computer vision model"; I didn't say anything about generative AI. The reference to neural networks was hopefully an obvious rhetorical flair, rather than a one-line assertion that computers and brains are actually equivalent.

I also didn't say anything about whatever Altman or any specific company is doing.

The simple fact is that we send humans to school for years to learn to read and classify these things. It's something computers will be able to do strictly better.

[Eufrat]

> It's something computers will be able to do strictly better.

I don’t think there’s any evidence that’s true.

[anon84873628]

Really? What about the use of computer vision for satellite imagery? Facial recognition?

The premise seems to be proven, just not extended to the medical domain yet.

[Eufrat]

I think you’re conflating detection with interpretation.