Tootfinder

Apple researchers maybe disprove ‘reasoning’ (vs. well-specified conventional algorithms):
https://machinelearning.apple.com/research/illusion-of-thinking
Analyses:
•

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Recent generations of frontier language models have introduced Large Reasoning Models (LRMs) that generate detailed thinking processes…

UNDERNEWS: Coffee ban recommended in three states
https://prorevnews.blogspot.com/2025/06/coffee-ban-recommended-in-three-states.html

Egyptian police violently obstruct the international Gaza Peace March.
Ocupación israelí | La policía egipcia impide con violencia la marcha internacional a Gaza - El Salto - Edición General
https://www.elsaltodiario.com/ocupacion-is

La policía egipcia impide con violencia la marcha internacional a Gaza
La marcha de 4.000 personas a Gaza es reprimida por la policía del régimen de Al-Sisi. La organización pide a las embajadas que reaccionen y protejan a sus ciudadanos.

A look at seven rebuttals to Apple's paper on limitations of Large Reasoning Models, and why none make a compelling case (Gary Marcus/Marcus on AI)
https://garymarcus.substack.com/p/seven-replies-to-the-viral-apple

Seven replies to the viral Apple reasoning paper – and why they fall short
Also: another paper that seals the deal

#silentSunday #RockyMountainNationalPark
View from Many Parks Curve. October 2016

Apple-Paper: Warum Reasoning-Modelle wohl nicht denken
Sie brauchen viel Leistung, liefern aber nicht immer bessere Ergebnisse: Large Reasoning Models sollen die KI revolutionieren. Eine Apple-Studie kritisiert das.

How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts?
Sohee Yang, Sang-Woo Lee, Nora Kassner, Daniela Gottesman, Sebastian Riedel, Mor Geva
https://arxiv.org/abs/2506.10979

How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts?
Recent reasoning models show the ability to reflect, backtrack, and self-validate their reasoning, which is crucial in spotting mistakes and arriving at accurate solutions. A natural question that arises is how effectively models can perform such self-reevaluation. We tackle this question by investigating how well reasoning models identify and recover from four types of unhelpful thoughts: uninformative rambling thoughts, thoughts irrelevant to the question, thoughts misdirecting the question a…

Ach ne, das kann doch nicht sein… oder oder… oder doch?! Marketing #Propaganda ist ja nicht neu:
»Ist Reasoning ein #Marketing-Trick? Apple-Forscher zeigen gravierende Probleme von #KI-Modellen:

Ist Reasoning ein Marketing-Trick? Apple-Forscher zeigen gravierende Probleme von KI-Modellen - t3n – digital pioneers
Apple-Forscher:innen haben ein neues Paper veröffentlicht, das die Fertigkeiten von Reasoning-Modellen infrage stellt. Demnach sollen aktuelle Modelle von OpenAI, Google und Anthropic nur in Benchmarks zuverlässig funktionieren, aber an echten Aufgaben grandios scheitern. Immer mehr KI-Unternehmen setzen ihren Fokus auf Reasoning-Modelle, die in der Lage sein sollen, komplexe Gedankengänge zu haben. Doch selbst OpenAI musste […]

douban: Douban friendship network (2009)
A friendship network among users on Douban.com, a Chinese website providing recommendations for books, music, and movies.
This network has 154908 nodes and 327162 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/douban…

Mistral launches its first reasoning models: Magistral Small, on Hugging Face under an Apache 2.0 license, and Magistral Medium, in preview on Mistral's Le Chat (Kyle Wiggers/TechCrunch)
https://techcrunch.com/2025/06/10/mistral-releases-a-pai…

Mistral releases a pair of AI reasoning models | TechCrunch
Like other reasoning models, Magistral works through problems step-by-step for improved consistency and reliability across topics such as math and physics.