Exactly - context is everything in art, in how it's experienced and how it is created.
I think it's important to note that a jpg of Monet is not fully experiencing the painting in any sense. Colours will not be accurately captured, the texture, the framing, the scale - it's sort of like getting a heavily watered down version of the expensive wine, saying it's cheap wine, and asking what people think.
I'd be a little bit careful here - being a jerk is quite different to non-conformity / red sneaker effect in surgery and it is not a quality you should look for.
The truly compassionate surgeons will want to improve their skills because they care about their patients. They care if they develop complications and may feel terrible if they do, the jerk may not. Being a jerk may mean that the surgeon can rise to the top, but it may not be due to surgical skill at all, they may be better at navigating politics etc.
I'm surprised at both the article and the paper - both seem very hyperbolic. This is LLMs competing against doctors in a way that is heavily weighted in the LLMs favour, which does not represent clinical practice. These reasoning cases are not benchmarks for doctors, they are learning tools.
I think it's important to note that diagnosis also relies on accurate description of the patient in the first place, and the information you gather depends on the differential diagnosis. Part of the skill of being a doctor is gathering information from lots of different sources, and trying to filter out what is important. This may be from the patient, who may not be able to communicate clearly or may be non verbal, carers and next of kin. History-taking is a skill in itself, as well as examination. Here those data are given.
For pattern recognition from plain text, especially on questions that may be in the o1's training data, I'm not surprised at all that it would outperform doctors, but it doesn't seem to be a clinically useful comparison. Deciding which investigations to do, any imaging, and filtering out unnecessary information from the history is a skill in itself, and can't really be separated from forming the diagnosis.
Ah amazing - thank you for the response! I have a couple of related questions - is it that the non 2 pi frequencies exist, but they destructively interfere so we can't see them? My understanding is that the radial function for the electron is zero at the nucleus - there is no possibility of it being found there - but why is that the case?
This is really great. I always saw those harmonic shapes as electron orbitals, I had no idea they could be used in lighting too - so cool.
It made me wonder - why do the electron orbitals take those shapes in say a hydrogen atom? Is there a constraint on the electron and proton together that make it fit only to spherical harmonic functions?
I've just started to try and learn the basics of RL and the Bellman Equation - are there any good books or resources I should look at? I think this post is beyond my current level.
I'm most interested in how the equation can be implemented step by step in an ML library - worked examples would be very helpful.
I would love if I don't have to port my whole iOS app to Android manually. How exactly would this integration work if say business logic is handled by Swift - I'm guessing UI and SwiftUI would not be supported initially?
My app [0] uses a lot of metal shader code - I'm guessing there's no easy way to bring that across?
I'm a doctor too and would love to hear more about the rationale and process for creating this.
It's quite interesting to have a binary distinction: 'concerned vs not concerned', which I guess would be more relevant for referring clinicians, rather than getting an actual diagnosis. Whereas naming multiple choice 'BCC vs melanoma' would be more of a learning tool useful for medical students..
Echoing the other comments, but it would be interesting to match the cards to the actual incidence in the population or in primary care - although it may be a lot more boring with the amount of harmless naevi!
This was my concern too - as a little project, it's interesting but if it's a replica of XP it has been done before and much more accurately.
As a portfolio, I think it doesn't work at all and is detrimental to what you're trying to do. I think now in design, it is more important than ever for your work to cut through the noise and show at least some attempt to create something original.
I think sometimes graphic design is seen as competence with certain programs, which I guess includes genAI now, or making something cool - but really it is visual communication that responds to a set of constraints - e.g. a brief, tailored to a target audience, communicating a product or emotion. There are no shortcuts - study what has been done, work on communicating what you want to say with colour, layout, typography and images. Draw and paint; avoid genAI until you are competent without it. Currently as a graphic design portfolio, I'm sorry to say it is memorably bad and there is a lot of work to do.
That said, well done on finishing something, and making it to the top of HN. I hope the attention leads somewhere and that you continue making things.
I think it's important to note that a jpg of Monet is not fully experiencing the painting in any sense. Colours will not be accurately captured, the texture, the framing, the scale - it's sort of like getting a heavily watered down version of the expensive wine, saying it's cheap wine, and asking what people think.