What I see are people returning to the same categorical errors in medicine.
Drawing medical conditions from an urn occasionally yields a true diagnostic, even more so if conditions are weighed in the urn according to their prevalence in society. But disease lottery is no medical practice.
Two essential errors exist in medicine:
1. Delivering a wrong intervention.
2. Failing to deliver an intervention at the right time due to misdiagnosis.
These are the sins of harm and distraction. The metric for judging a system is not whether it gets things right on one occasion, but whether it makes those mistakes on the others.
Doctors err because people and institutions are imperfect, biology is messy, and human variability is immense. But the former can be attenuated by a plurality of opinions and greater resources (including time), while statistical systems are inherently vulnerable to the latter two.
Language models hallucinate and deliver both essential errors - all while speaking in a very confident and convincing manner. What OpenAI is advertising is a system that nudges vulnerable people to abandon, distrust, ignore, or simply avoid seeking true medical practitioners to rely on a statistical system out of an unjustified, naive trust in the machine.
As a reminder to those concerned with healthcare accessibility, picking the wrong solution to a problem for lack of a right one does not solve the problem. That reasoning was the basis of practices such as bloodletting and lobotomy. Time after time again, medical science teaches us the limits of this kind of thinking.
Agreed. Another example in the first minute of the "Attention is all you need" one.
"[Transformers .. replaced...] ...the suspects from the time.. recurrent networks, convolution, GRUs".
GRU has no place being mentioned here. It's hallucinated in effect, though, not wrong. Just a misdirecting piece of information not in the original source.
GRU gives a Ben Kenobi vibe: it died out about when this paper was published.
But it's also kind of misinforming the listener to state this. GRUs are a subtype of recurrent networks. It's a small thing, but no actual professor would mention GRUs here I think. It's not relevant (GRUs are not mentioned in the paper itself) and mentioning RNNs and GRUs is a bit like saying "Yes, uses both Ice and Frozen Water"
So while the conversational style gives me podcast-keep-my-attention vibes.. I feel a uncanny valley fear. Yes each small weird decision is not going to rock my world. But it's slightly distorting the importance. Yes a human could list GRUs just the same, and probably, most professors would mistake or others.
But it just feels like this is professing to be the next, all-there thing. I don't see how you can do that and launch this while knowing it produces content like that. At least with humans, you can learn from 5 humans and take the overall picture - if only one mentions GRU, you move on. If there's one AI source, or AI sources that all tend to make the same mistake (e.g. continuing to list an inappropriate item to ensure conversational style), that's very different.
It then goes on to explain right afterwards that the key thing the transformer does is rely on a mechanism called attention. It makes more sense in that context IMO.
I recently listened to this great episode of "This American Life" [1] which talked about this very subject. It was released in June 2023 which might be ancient history in terms of AI. But it discusses whether LLMs are just parrots and is a nice episode intended for general audiences so it is pretty enjoyable. But experts are interviewed so it also seems authoritative.
This is the very next sentence, so it is a little odd that "hence the title" comes before, and not after, "...using something called self attention."
My take is these are nitpicks though. I can't count the number of podcasts I've listened to where the subject is my area of expertise and I find mistakes or misinterpretations at the margins, where basically 90% or more of the content is accurate.
Drawing medical conditions from an urn occasionally yields a true diagnostic, even more so if conditions are weighed in the urn according to their prevalence in society. But disease lottery is no medical practice.
Two essential errors exist in medicine:
1. Delivering a wrong intervention.
2. Failing to deliver an intervention at the right time due to misdiagnosis.
These are the sins of harm and distraction. The metric for judging a system is not whether it gets things right on one occasion, but whether it makes those mistakes on the others.
Doctors err because people and institutions are imperfect, biology is messy, and human variability is immense. But the former can be attenuated by a plurality of opinions and greater resources (including time), while statistical systems are inherently vulnerable to the latter two.
Language models hallucinate and deliver both essential errors - all while speaking in a very confident and convincing manner. What OpenAI is advertising is a system that nudges vulnerable people to abandon, distrust, ignore, or simply avoid seeking true medical practitioners to rely on a statistical system out of an unjustified, naive trust in the machine.
As a reminder to those concerned with healthcare accessibility, picking the wrong solution to a problem for lack of a right one does not solve the problem. That reasoning was the basis of practices such as bloodletting and lobotomy. Time after time again, medical science teaches us the limits of this kind of thinking.