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#distinction

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Une #distinction pour le Théâtre Royal de #La #Monnaie aux OPER ! AWARDS 2025 !

Les OPER! AWARDS 2025 ont été présentés récemment à La Monnaie, qui a eu l'honneur d'accueillir la cérémonie de remise des prix en tant que Meilleure Maison d'Opéra de l'Année 2025.Une belle distinction pour ce théâtre bruxellois.   La Monnaie a été récompensée par Ulrich Ruhnke, président du jury et fondateur des OPER! AWARDS, pour son « attrait considérable et une ouverture qui rassemble…

bruxelles-city-news.be/une-dis

Culture is a huge topic in companies. And wrongly so, to some extent! Experts like Ed Schein created a big mess with their writings about corporate culture, as they stubbornly confused #culture and #system. But by respecting the crucial #distinction between systems and culture, organizational transformation starts making sense again. In short: Forget about working the culture (or people). Stick with #WorkingTheSystem. Together.
A new article of mine on the culture topic: redforty2.com/post/your-compan

If scientists want to determine whether an LLM has formed an accurate model of the world, measuring the accuracy of its predictions doesn’t go far enough.
For example, a transformer can predict valid moves in a game of Connect 4 nearly every time without understanding any of the rules.
So, the team developed two new metrics that can test a transformer’s world model. The researchers focused their evaluations on a class of problems called deterministic finite automations, or DFAs. 
A DFA is a problem with a sequence of states, like intersections one must traverse to reach a destination, and a concrete way of describing the rules one must follow along the way.
They chose two problems to formulate as DFAs:
navigating on streets in New York City
and playing the board game Othello.

“We needed test beds where we know what the world model is. Now, we can rigorously think about what it means to recover that world model,” Vafa explains.
The first metric they developed, called #sequence #distinction, says a model has formed a coherent world model it if sees two different states, like two different Othello boards, and recognizes how they are different. Sequences, that is, ordered lists of data points, are what transformers use to generate outputs.
The second metric, called #sequence #compression, says a transformer with a coherent world model should know that two identical states, like two identical Othello boards, have the same sequence of possible next steps.
They used these metrics to test two common classes of transformers, one which is trained on data generated from randomly produced sequences and the other on data generated by following strategies.
Surprisingly, the researchers found that transformers which made choices randomly formed more accurate world models, perhaps because they saw a wider variety of potential next steps during training. 
“In Othello, if you see two random computers playing rather than championship players, in theory you’d see the full set of possible moves, even the bad moves championship players wouldn’t make,” Vafa explains.
Even though the transformers generated accurate directions and valid Othello moves in nearly every instance,
the two metrics revealed that only one generated a coherent world model for Othello moves,
and none performed well at forming coherent world models in the wayfinding example.
news.mit.edu/2024/generative-a

MIT News | Massachusetts Institute of TechnologyDespite its impressive output, generative AI doesn’t have a coherent understanding of the worldBy Adam Zewe | MIT News

|#research|#distinction|#academiedessciences|#inserm | 📢 NATHALIE ROUACH @CirbCdf a reçu le PRIX DE LA FONDATION SICARD🎉 👏2024, Ce prix annuel créé en 2023 de 100 000€ 🏆 vise à récompenser un chercheur(se), en France et à l’étranger, pour des découvertes dans le domaine des neurosciences. Cette année, le prix annuel concernera la biologie des réseaux de neurones. @collegedefrance

▶️ college-de-france.fr/fr/actual

#Distinction 🏆| L'académie des sciences récompense Laurent Chevillard. Il reçoit le prix Servant 2024. Félicitations!
Laurent développe des modèles de la #turbulence des #fluides, observée dans les expériences et les simulations des équations de Navier-Stokes. Bénéficiant d’un tissu collaboratif étoffé, il a construit des champs aléatoires qui rendent compte de la structure statistique fine de ces écoulements, et a proposé une dynamique stochastique simplifiée permettant de les réaliser.

Replied to Estelle Platini

How do you show your social value in a way that’s instantly recognizable?

"The meaning ascribed to race in the nightclub setting was related to perceptions of safety. The bouncers (many of whom are Black or Latino) claimed that letting Black or Latino Americans in might jeopardize safety at the club. However, Rivera says she saw fights between white customers frequently."

A field study by Lauren A. Rivera, 2010: insight.kellogg.northwestern.e @sociology

Kellogg Insight · Sizing Up the NightlifeA study of status distinction
Replied to Susan Larson ♀️🏳️‍🌈🏳️‍⚧️🌈

#ShadyVance had better buckle up: His #debate might go as badly as #Trump’s

Ninety minutes is more than enough time for #women to #remember why and how much they #dislike him. |

JD Vance has had the most disastrous #vicepresidential #run in memory, gaining the #distinction of having the worst net #approvalrating of the four #candidates on the two major party tickets.

washingtonpost.com/opinions/20

The Washington Post · Vance had better buckle up: His debate might go as badly as Trump’s By Jennifer Rubin