recommended reading. strongly recommended reading.
i really like the pain avoidance angle. slots into my "paon/friction is when you learn" angle. when combined > cognitive debt.
https://t.co/clzPIgXaSU
🧵 1/ How well do LLMs actually do on Olympiad-level math?
We evaluated frontier models on 455 problems from the IMO Shortlist.
Unlike most benchmarks, we emphasize proof validity, not just final answer correctness.
Here’s what we found 👇
@daniellellecco I second the proposals on consulting and working for the public sector, or in a small to medium company operating on a specific frontier. Lots of opportunities to transpose or transfer tools and methods, and sometimes truly invent.
@JoeMayo Explicit typing, clean inheritance, docstrings should help. Hopefully best practices for humans will be easy to leverage for AI coding assistants, so we can all benefit.
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@daniellellecco I get less from this place than I used to, a few years ago. Informative content seems more hyped and less honest, overused words in repetitive constructions arranged to evoke attention-grabbing rhythms.
Your writing and posting is a comforting exception, so thanks.
@wotchey@davidytier@lamarsweb Ou encore cette devanture du plus bel effet posée hier devant l'illustre Maison Puget (1681), rue de Rome et sa colonne éponyme inscrite il y a deux ans aux monuments historiques
#BalanceTaDevanturePourrie
@samuelcolvin@astral_sh@quarto_pub addresses most of these issues for me (rich markdown, pure text so git friendly etc). Builds on years of experience from the Rmd community https://t.co/hg2GvwBwkj
Procès #RuedAubagne Quand Xavier Cachard dictait à l'expert Cardi une note afin de lui permettre de retarder "de deux ou trois ans" la procédure. Pendant ce temps-là, le mur mitoyen s'enfonce...
Un grand moment d'audience à lire ce week-end dans La Marseillaise
Part 2: Why do boosted trees outperform deep learning on tabular data??
@Jeffaresalan &I suspected that answers are obfuscated by the 2 being considered very different algs
Instead we show they are more similar than you’d think — making their diffs smaller but predictive!🧵1/n
A new paper about AI in Materials Discovery has gained a lot of attention - it reports a big increase in productivity of scientists using AI tools, and interesting secondary effects of using AI for science.
But do the technical claims stack up? Let's see...
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I'm sorry Noam, but a blog post does not come close to meeting the standards of reproducibility, methodology, acknowledgment of prior work, and fair comparison with the state of the art, that a technical paper has to satisfy.
Look, when you develop new technology under pressure to have short-term product impact, you just build the thing that you think is most likely to work as quickly as possible. If it's good enough, you deploy it. You may not care whether it's particularly innovative, whether it actually beats the state of the art, or whether it's a horrible kludge or The Right Thing to do in the long run. It's OK to delude yourself into thinking it's the best thing since slice bread, as long as your boss and the product people can also be deluded.
But you know that's not how research works.
@Stuk_89@lau_devil Si c'est le vocable "influenceur" qui vous gêne, remplacez ça par "bon client des médias", le fond est le même et reste juste. Impossible pour des scientifiques de faire entendre un discours fidèle à l'état des connaissances, qd le débat public est structuré par ces argumentaires
@Stuk_89@lau_devil L'argument serait recevable s'il pouvait s'appuyer sur une activité de publication dans des revues de science politique à comité de lecture.
#RechercheDataGouv a 2 ans ! 🎂
Consultez la rétrospective en images des principaux événements de Recherche Data Gouv, l'écosystème réunissant plus de 350 acteurs au service du partage et de l’ouverture des données de recherche ➡️ https://t.co/Kj1DAG3hUU #opendata#openscience
@DavidLaMars@lamarsweb Rdc non surélevé et grand stationnement souterrain sur une parcelle à risque d'inondation très élevé (cf. PPRI Huveaune, zonage 4) ?