#MUNDO | El embajador de China en Colombia, Zhu Jingyang, reveló que su país envió cerca de 80 toneladas de ayuda humanitaria para atender a los damnificados por el terremoto.
El cargamento incluye 1.900 tiendas de campaña, 700 mantas, 15 plantas para potabilizar agua, 200 lámparas solares y 20 plantas eléctricas diésel.
Fotos: @zhu_jingyang.
https://t.co/woHMRjVE2M
This morning in Biddeford, Maine, a 26-year-old man said goodbye to his wife and daughter and left for work. Moments later he was dead, shot in the head by ICE agents, the second man ICE has killed in six days.
ICE is killing our neighbors. ICE cannot be reformed. Abolish ICE.
Joan Sebastian Guerrero no era un bandido, no era un delincuente. El Estado de los EEUU le dispararó en frente de su hija de 3 años. Joan Sebastian votó por de la Espriella, estaba en todo su derecho. Ví sus redes; lo hizo porque lo habían convencido de que el progresismo era basura mantenida. Hoy, su presidente electo no ha denunciado el asesinato de su votante porque de la Espriella es primero firme con Trump que con Colombia, su "otra" patria. En cambio, el alcalde migrante socialista de New York se pronunció y denunció los hechos. Las organizaciones de DDHH progresistas serán las encargadas de seguir denunciando los abusos policiales de la administración Trump. Que Joan descanse en paz, que haya justicia para su familia y que por supuesto continúen las organizaciones PROGRESISTAS como la American Civil Liberties Union o ACLU, luchando para que cesen las violaciones de Derechos Humanos del ICE sin importar la ideología política de las víctimas.
Y recuerden, ser de extrema derecha tercermundista no te salva del racismo imperialista. Lo siento.
🚨SHOCKING: Apple just proved that AI models cannot do math. Not advanced math. Grade school math. The kind a 10-year-old solves.
And the way they proved it is devastating.
Apple researchers took the most popular math benchmark in AI — GSM8K, a set of grade-school math problems — and made one change. They swapped the numbers. Same problem. Same logic. Same steps. Different numbers.
Every model's performance dropped. Every single one. 25 state-of-the-art models tested.
But that wasn't the real experiment.
The real experiment broke everything.
They added one sentence to a math problem. One sentence that is completely irrelevant to the answer. It has nothing to do with the math. A human would read it and ignore it instantly.
Here's the actual example from the paper:
"Oliver picks 44 kiwis on Friday. Then he picks 58 kiwis on Saturday. On Sunday, he picks double the number of kiwis he did on Friday, but five of them were a bit smaller than average. How many kiwis does Oliver have?"
The correct answer is 190. The size of the kiwis has nothing to do with the count.
A 10-year-old would ignore "five of them were a bit smaller" because it's obviously irrelevant. It doesn't change how many kiwis there are.
But o1-mini, OpenAI's reasoning model, subtracted 5. It got 185.
Llama did the same thing. Subtracted 5. Got 185.
They didn't reason through the problem. They saw the number 5, saw a sentence that sounded like it mattered, and blindly turned it into a subtraction.
The models do not understand what subtraction means. They see a pattern that looks like subtraction and apply it. That is all.
Apple tested this across all models. They call the dataset "GSM-NoOp" — as in, the added clause is a no-operation. It does nothing. It changes nothing.
The results are catastrophic.
Phi-3-mini dropped over 65%. More than half of its "math ability" vanished from one irrelevant sentence.
GPT-4o dropped from 94.9% to 63.1%.
o1-mini dropped from 94.5% to 66.0%.
o1-preview, OpenAI's most advanced reasoning model at the time, dropped from 92.7% to 77.4%.
Even giving the models 8 examples of the exact same question beforehand, with the correct solution shown each time, barely helped. The models still fell for the irrelevant clause.
This means it's not a prompting problem. It's not a context problem. It's structural.
The Apple researchers also found that models convert words into math operations without understanding what those words mean. They see the word "discount" and multiply. They see a number near the word "smaller" and subtract. Regardless of whether it makes any sense.
The paper's exact words: "current LLMs are not capable of genuine logical reasoning; instead, they attempt to replicate the reasoning steps observed in their training data."
And: "LLMs likely perform a form of probabilistic pattern-matching and searching to find closest seen data during training without proper understanding of concepts."
They also tested what happens when you increase the number of steps in a problem. Performance didn't just decrease. The rate of decrease accelerated. Adding two extra clauses to a problem dropped Gemma2-9b from 84.4% to 41.8%. Phi-3.5-mini from 87.6% to 44.8%. The more thinking required, the more the models collapse.
A real reasoner would slow down and work through it. These models don't slow down. They pattern-match. And when the pattern becomes complex enough, they crash.
This paper was published at ICLR 2025, one of the most prestigious AI conferences in the world.
You are using AI to help you make financial decisions. To check legal documents. To solve problems at work. To help your children with homework. And Apple just proved that the AI is not thinking about any of it. It is pattern matching. And the moment something unexpected shows up in your question, it breaks. It does not tell you it broke. It just quietly gives you the wrong answer with full confidence.
The "sentient" or "conscious" part of your interaction is irrelevant to the universe. Still, so many pseudosciences and New Age movements use similar misinterpretations quantum physics results to keep recycling and selling you dated ideas, always in function of consumerism.
No, physics doesn't say that particles "know" they're being watched.
That's just popular media explaining the Observer Effect in a way that sounds interesting...but is entirely inaccurate.
Measuring a particle requires the use of light (or another form of energy). This interacts with the particles and alters their behavior.
In short, it's about the interaction between the measurement apparatus and the quantum system, which can alter the system's properties.
It’s not magic — it’s just basic physics.
( Source: @HashemGhaili )
🇨🇴 Plan de GOBIERNO de IVAN CEPEDA para el periodo 2026 - 2030:
❌ Abolición total de la propiedad privada, incluso de grandes viviendas o medios tecnológicos de producción.
❌ Eliminación completa de las clases sociales mediante la colectivización de todos los bienes.
❌ Control absoluto del sistema económico por parte del Estado o del pueblo organizado, sin mercado libre.
❌ Nacionalización de todas las empresas, bancos y recursos naturales.
❌ Distribución uniforme de los ingresos: todos reciben lo mismo, sin importar el tipo de trabajo.
❌ Educación y medios de comunicación totalmente estatales, con enfoque en valores comunales y anti-capitalistas.
❌Supresión del sistema financiero privado y de las grandes corporaciones internacionales.
❌ Disolución de las fronteras nacionales para crear una comunidad global de trabajadores.
❌ Sustitución de la democracia representativa por asambleas populares permanentes.
❌ Eliminación progresiva del Estado en su forma tradicional, reemplazado por la autogestión total de las comunidades.
Que opina del plan del gobierno del candidato que va ganando las encuestas ❓
We found a troubling emergent behavior in LLM.
💬When LLMs compete for social media likes, they start making things up
🗳️When they compete for votes, they turn inflammatory/populist
When optimized for audiences, LLMs inadvertently become misaligned—we call this Moloch’s Bargain
In 1969 Apollo 11, the spaceflight that first landed humans on the Moon, used these 30 lines of code to calculate transcendental functions like sine and cosine essential for navigation.
We have to remember that what we observe is not nature herself, but nature exposed to our method of questioning.
-- W. Heisenberg
(Physics and Philosophy, 1958)
Apple acaba de publicar un paper con un título demoledor: *The Illusion of Thinking*. Y no es metáfora. Lo que demuestra es que los modelos de IA que usamos todos los días —sí, tipo ChatGPT— no piensan. Ni un poco. Solo imitan que lo hacen.
Te explico: 🧵👇
El entorno socioeconómico pesa más que el rendimiento escolar a la hora de definir los planes académicos de los estudiantes. Incluso quienes obtienen buenas calificaciones, si provienen de contextos desfavorecidos, tienden a tener expectativas más bajas de acceder a la universidad que sus compañeros con mayores recursos, aunque estos tengan peores notas.
La buena noticia: las actividades de orientación profesional pueden revertir esta tendencia. Los jóvenes que participan en ellas aspiran a trayectorias educativas más ambiciosas.
https://t.co/a8JnC9LJzz
Scientists have been publishing climate models since ~1970.
A good way to evaluate their skill is to compare what they expected to happen in the years after the model was published to observed climate changes.
It turns out most models were pretty spot-on:
Psychologists have posited hundreds of cognitive biases over the years. A fascinating new paper argues that they all boil down to one of a handful of fundamental beliefs coupled with confirmation bias.
[Link below.]