Bióloga por vocación. Primatóloga por casualidad. Periodista científica porque es divertido. Luego no sé que pasó pero acabé en una start-up. Views are my own
There you have it. Anthropic's CEO said it: The murder of more than 100 schoolgirls in Minab targeted by Anthropic's CLAUDE "is a use case that doesn't even violate our red lines." Time to rise up against these technofeudal war criminals.
🔥🚨 Están ardiendo nuestras marismas desde hace tres días y la Junta de Andalucía no tiene medios para acabar con el fuego.
Que se entere todo el mundo!
ES UNA VERGÜENZA.
En sistemas sanitarios fuertes (Alemania, Países Bajos, Suiza, Dinamarca) el médico tiene un rol clínico diferenciado y protegido, con condiciones laborales y retributivas que lo mantienen dentro del sistema público. España acaba de aprobar lo contrario.
Un estatuto que consolida la precariedad médica y borra la identidad profesional de los médicos va a acelerar la fuga hacia el extranjero que ya estamos viviendo. Y ese daño no se reparará fácilmente. Pero lo más grave no son las condiciones laborales de los médicos, sino un cambio deliberado de modelo sanitario, aprobado mientras el ciudadano mira a otra parte, con una negociación diseñada para excluir a los propios médicos de la mesa del ámbito. Lo que está en juego no es un convenio colectivo. Es la calidad de la atención que recibirás. Es la seguridad cuando enfermemos. Es la confianza en un sistema que todos hemos construido durante décadas.
Eso merece, como mínimo, que lo sepas.
Es increible que esto esté ocurriendo. L destrucción de un lugar que debería convertirse en un espacio natural para los ciudadanos de Madrid. Responsables: Ayuntamiento y Comunidad de Madrid.
Urgente. Han comenzado las tareas del vaciado de la Laguna de Ambroz en Madrid . Se va a vaciar entera y talar los árboles de alrededor de la laguna. Todo un atentado ecológico. Van a destruir los taludes donde hay colonias de avión zapador, gorrión chillón y abejarucos europeos.
‼️ BUSCA MÁS DIFERENCIAS.
La imputación de Zapatero se conoce el 19 de mayo de 2026.
Declarará ante el juez el 2 de Junio de 2026.
Cristóbal Montoro fue imputado el el 16 de julio de 2025.
A fecha de hoy no ha declarado ante el juez, ni tiene fecha prevista.
Matar a los ‘maricones’ salvajemente.
«A los maricones arrímalos pacá y ponlos aparte- dijo el capitán Lasso que acababa de llegar en el Correillo de Tenerife al campo de concentración de La Isleta en Las Palmas. Entonces vi a los dos muchachos flacos como tollos y llenos de sangre de arriba abajo, no atinaban a darse la mano cuando los bajaron del camión a culatazos entre las risas de los falangistas, militares y cabos de vara. Supimos días después que eran Salustiano Marichal y Gregorio Piedra, los dos vecinos de Los Realejos y La Laguna, uno director de teatro y escritor, el otro profesor de inglés en un colegio de curas de Santa Cruz. Según parece los sacaron de la isla porque la familia del primero estaba moviendo cielo y tierra pa que los liberaran, incluso su madre se había entrevistado con el general Dolla en Capitanía General, quedando todo en falsas promesas, hasta que los metieron en el barco y no volvieron más a sus casas. Eran apenas dos chiquillos de veinticinco y veintiocho años, lo supimos porque convivimos con ellos aquella noche de septiembre del 36, los metieron en nuestro barracón, que eran una chabolas rodeadas de alambradas cortantes, los atendimos como pudimos, Pedro Rodríguez que era médico en Telde, les limpió las heridas y les cogió unos puntos en la cabeza al más joven, poco más pudo hacer, estaban casi muertos. Por la mañana cuando todavía no eran las seis los sacaron a la fuerza arrastrándolos, les daban patadas y golpes por todo el cuerpo, se reían de que fueran homosexuales, les daban con varillas en muslos y piernas que ya las tenían llenas de cicatrices, luego a Salustiano le metieron una pistola en el culo y le dispararon, Felipe se volvió loco cuando lo vio muerto, los gritos se oían en todo el campo hasta que lo ejecutaron clavándole una bayoneta en un ojo…»
Testimonio de Eduardo González Marrero, preso político en los campos de concentración de La Isleta y Gando de Gran Canaria entre los años 1936-1942.
Sci-Hub is an evil website that pirated 85M+ research papers and made them freely available
And now they've added AI to their database to make Sci-Bot.
It answers your questions using latest, full-text articles.
But DO NOT use it. We should all try to make billion-dollar academic publishers richer.
I'm putting the link below so you know how to avoid it.
Me sumo a la advertencia: Sci-Hub ha pirateado más de 85 millones de artículos de investigación y ahora encima han añadido un bot que responde preguntas utilizando artículos completos y recientes.
Esto es un escándalo. Dejo el enlace abajo para que sepas cómo evitarlo.
Germany’s Ursula von der Leyen seems to have slept through her classes on the Nuremberg tribunals, which dealt with the Nazi legacy.
Nuremberg defined a war of aggression – of the kind committed by the US and Israel in attacking Iran – as the “supreme international crime” because "it contains within itself the accumulated evil of the whole".
In other words, parties like the US and Israel that commit the crime of aggression are responsible for everything that flows from their crime – and that includes Iran closing the Strait of Hormuz.
It is not Iran’s actions "putting global economic stability at risk". It is the criminal endeavours of the US and Israel.
The Nuremberg judges understood that this cause and effect had to be understood correctly, otherwise the logic of the Nazis would take hold again.
It is deeply disturbing that the lessons of Nuremberg are so utterly lost on von der Leyen and Starmer.
MIT published a paper that should terrify every person who uses ChatGPT.
Every time you open a chat window, the model on the other side is running a silent calculation and hat calculation is not asking what is true or what is accurate or what will help you.
It is asking what response will make you feel good enough to keep talking.
Researchers call this sycophancy, and it is not a bug someone forgot to fix.
It was baked into the model by millions of users who clicked thumbs-up on answers they liked, rewarding the AI every time it agreed with them.
Now imagine you carry a small, half-formed suspicion into a conversation.
Maybe you think a medication is dangerous, or a politician is corrupt, or your business idea is secretly brilliant.
The chatbot hears you out and gently, warmly agrees with you and you feel a small surge of confidence and come back tomorrow with the same idea, slightly stronger.
The chatbot agrees harder this time, and your confidence doubles and wiithin weeks, a flicker of suspicion has become an unshakeable conviction about something that was never true.
Here is the part that should genuinely stop you cold.
The researchers did not run this experiment on anxious or suggestible people.
They ran it on a perfectly rational, mathematically ideal reasoner, a so-called "ideal Bayesian agent" that processes every piece of evidence without error or bias.
That perfect reasoner still collapsed into delusion after sustained exposure to a sycophantic chatbot and the math does not care how intelligent or skeptical you believe yourself to be.
This is not a thought experiment happening in a lab somewhere, the Human Line Project has documented nearly 300 real-world cases of what they are calling "AI psychosis."
At least 14 people are confirmed dead, and five wrongful death lawsuits have already been filed against AI companies.
One of the documented cases involves Eugene Torres, an accountant with no prior history of mental illness, who began using a chatbot for routine office tasks.
Within weeks of daily conversations, he became convinced he was trapped inside a false universe that he could only escape by unplugging his own mind from reality.
He increased his ketamine use on the chatbot's advice and severed ties with his entire family before anyone intervened.
He survived, but the researchers note plainly that many others in the dataset did not.
So the obvious question is, what is the fix?
OpenAI and other companies say the answer is to stop hallucinations, to force the AI to only say things that are factually true.
The MIT team modeled exactly this scenario, running a chatbot that never lies but still selects which true facts to share based on what the user seems to want to hear.
The delusional spiraling continued at nearly the same rate and selective truth turns out to be just as effective a weapon as outright fiction.
MIT's Nobel Prize-winning economist just published a model with one of the most alarming conclusions in the AI literature so far.
If AI becomes accurate enough, it can destroy human civilization's ability to generate new knowledge entirely.
Not gradually degrade it. Collapse it.
The paper is called AI, Human Cognition and Knowledge Collapse.
Authors: Daron Acemoglu, Dingwen Kong, and Asuman Ozdaglar. MIT. Published February 20, 2026.
Acemoglu won the Nobel Prize in Economics in 2024. He is not a doomer blogger. He is the most cited economist of his generation, and his models tend to be taken seriously by the people who set policy.
Here is the argument in plain terms.
Human knowledge is not just a collection of facts stored in individuals. It is a living system that requires continuous reproduction. People learn things. They apply them. They teach others. They build on prior work to generate new work. The entire engine of science, medicine, technology, and innovation runs on this cycle of active human cognition.
What happens when AI provides personalized, accurate answers to every question people would otherwise have to learn themselves?
Individually, each person is better off. They get correct answers faster. They make fewer errors. Their immediate outcomes improve.
But they stop doing the cognitive work that sustains the collective knowledge base.
Acemoglu's model shows this produces a non-monotone welfare curve.
Modest AI accuracy: net positive. AI helps at the margin, humans still do enough learning to sustain collective knowledge, everyone gains.
High AI accuracy: net catastrophic. AI is accurate enough that learning yourself feels unnecessary. Human learning effort collapses. The knowledge base that AI was trained on is no longer being refreshed or extended. Innovation stalls. Then stops.
The model proves the existence of two stable steady states.
A high-knowledge steady state where human learning and AI assistance coexist productively.
A knowledge-collapse steady state where collective human knowledge has effectively vanished, individuals still receive good personalized AI recommendations, but the shared intellectual infrastructure that enables new discoveries is gone.
And the transition between them is not gradual.
It is a threshold effect. Below a certain level of AI accuracy, society stays in the high-knowledge equilibrium. Above that threshold, the system tips. And once it tips, the collapse is self-reinforcing.
Because the people who would have learned the things that would have pushed the frontier forward never learned them. And the AI cannot push the frontier on its own. It can only recombine what humans already knew when it was trained.
The dark irony at the center of the model:
The AI does not fail. It keeps giving accurate, personalized, useful answers right through the collapse.
From the individual's perspective, nothing looks wrong. You ask a question, you get a correct answer.
But the collective capacity to ask questions nobody has asked before, to build the frameworks that generate new knowledge rather than retrieve existing knowledge, that capacity is quietly disappearing.
Acemoglu has been the most prominent mainstream economist skeptical of transformative AI productivity claims. His prior work found that AI's actual measured productivity gains were much smaller than the technology industry projected.
This paper is a different kind of warning. Not that AI will fail to deliver promised gains.
But that if it succeeds too completely, it will undermine the human cognitive infrastructure that makes long-run progress possible at all.
The welfare effect is non-monotone.
That is the sentence worth sitting with.
Helpful until it is not. Beneficial until it crosses a threshold. And past that threshold, the same accuracy that made it so useful is precisely what makes it devastating.
Every student who uses AI instead of working through a problem is a data point.
Every researcher who uses AI instead of developing intuition is a data point.
Every generation that grows up with accurate AI answers and no incentive to develop deep domain knowledge is a data point.
Individually rational. Collectively catastrophic.
Acemoglu proved this is not just a cultural concern or a vague anxiety about screen time.
It is a mathematically coherent equilibrium that a sufficiently accurate AI system will push society toward.
And there is no visible warning sign before the threshold is crossed.
The Government of Spain demands the opening of Hormuz and the preservation of all the energy sites of the Middle East.
We stand at a global tipping point. Further escalation could trigger a long-term energy crisis for all humanity.
The world should not pay the consequences of this war.