HAHAHAH don't even get me started on how bad anaconda is.
On how slow the installer + interpreter, how they avoided being a part of the usual pip workflow, bloated environment, cross platform inconsistencies, extremely slow dependency resolution, etc etc etc...
Posit has solved similar problems with their Package Manager as well, the benefit being that it's hosted on-prem, but the user has to build wheels for their desired architecture (if they're not on pypi).
That is not correct. The EU AI Act has no such provision, ans the data mining excemption does not apply as the EU has made clear. As for Switzerland copyrighted material cannot be used unless licensed.
Exactly. The study has been set up to produce this exact result. They essentially limited the human doctors to bare essentials, on specialist cases(!), while providing the LLMs with all sorts of help, including discussion among several AIs.
That's like letting one group of students have a strict closed-book exam, while another group can take the test as a group exercise and accessing any material they like, then claiming that closed-book exams lead to worse outcomes.
In a nutshell the study is just slop designed to get attention. The headline result is what they really want people to hear, and that's all the media will be repeating.
As any AI researcher knows, if you have a model that does 4x better than the naive baseline (the humans, in this case), you are likely looking at overfit, not real-life performance. This study is just slop, and you can tell so by the mere fact that they did not submit a paper, but just published a PR article.
In the paper, they say they used the most recent 56 cases (from 2024–2025) as a holdout set. The majority of those cases happened after the o4 training cutoff of May 31, 2024.
To fly means "to soar through air; move through the air with wings" (etymonline)
That is pretty much an accurate discription of what planes and birds do.
To plan means "to reason with intent".
That is very much not what LLMs do, and the paper does not provide evidence to the contrary. Yet it uses the term to give credence to it's rather speculative interpretation of observed correlation as causation.
Interestingly enough there is no definition of the term, which at least would help to understand what the authors actually mean.
I would be more inclined to take a more positive stance to the paper if it used more appropriate terms, such as call observed correlations just that. Granted that would possibly make for much less of a fancy title.
Very much in support of this. The use of anthropmorphic or even biological terms are entirely misguided. All they do is drive a narrative that is very much belitting natural intelligence.
