Anthropic's proposed AI safety bill sets "killing or seriously injuring more than 50 people" as the risk threshold for blocking the release of an AI model In contrast, when a single patient (Jesse Gelsinger) died in a gene therapy clinical trial in 1999: - The institute that ran the trial was dissolved - The senior scientist running the trial was banned from clinical work for 5 years - Gene therapy saw deep cuts in funding and research activity for a decade Tech and biotech have just profoundly different cultures of risk. As AI companies increasingly engage with biomedical research, a culture clash is inevitable politico.com/news/2026/10/16…

La Filosofía Experimental de John Stewart Bell culturacientifica.com/2026/0…

En una primera cita le preguntas por su libro favorito. ¿Con qué título te conquistaría de inmediato?

This is subjective but … Name three PERFECT movies. No argument. No explanation. Just three flicks you think are perfect. Here's mine: 1) Ghostbusters 2) Kind Hearts and Coronets 3) Super Troopers

Wow. I woke up to an impressive number of upset people who apparently don’t understand how LLMs work and can’t cope well with me pointing it out. An LLM is a statistical next-token prediction model. That’s how it works. It’s an extraordinarily sophisticated calculator performing math you could theoretically do by hand (if you were sufficiently masochistic). Math doesn’t know what it’s calculating. Pi doesn’t spend its evenings contemplating the nature of circles, and c doesn’t ponder the relationship between matter and energy. That doesn’t make the results any less accurate, impressive, or useful. Between inference requests, an LLM isn’t sitting around thinking. It isn’t reconsidering its answers, wondering whether it made a mistake, contemplating its existence, or questioning whether it’s conscious. Its weights remain fixed (it doesn’t learn), and computation resumes when it receives input. We know this because we designed these systems. The architectures, mathematics, implementations, and research are extensively documented. You can study them yourself. Of course, some people immediately lean into comparisons of biological intelligence or philosophical debates over consciousness because that is what they know. But biological intelligence and artificial neural networks are fundamentally different systems. Similar outputs don’t establish equivalent internal experiences. I experience consciousness directly. I infer that other humans do too because we share biological structures and processes. We don’t have equivalent evidence for an LLM, and nothing about its known operation gives evidence of conscious experience. Which brings me back to my original point. To me, understanding is conscious comprehension. It means being aware of information, recognizing its meaning, and experiencing that comprehension. If I wasn’t conscious I could not understand. We can perform actions unconsciously. We can produce correct results without knowing why they’re correct. But I distinguish those capabilities from consciously understanding what we’re doing. An LLM can solve complex problems, explain difficult concepts, and produce remarkably accurate information. I give it full credit for those capabilities. But producing an answer that we rationalize as understanding isn’t the same as experiencing understanding. You don’t have to agree with my definitions. We can debate functional understanding versus conscious comprehension all day, but that won’t establish whether an LLM actually experiences anything. The right debate is this… Could machines exhibit something different from human consciousness, something measurable, meaningful, and worth studying? I think so, absolutely! I’m entirely open to discussing “machine consciousness” in terms of observable, testable computational properties. We built these systems, we can instrument them, examine their internal mechanisms, and investigate what they’re capable of. That seems far more productive than endlessly arguing over whether a machine experiences life the way humans do. So here’s my question: How would you define machine consciousness, and more importantly, how would you measure it?

The existence of moral philosophy implies the existence of immoral philosophy

Dozens of masked Israeli settlers attacked Palestinian villagers trying to gather their autumn olive harvest. Heidi Levine, a veteran photographer for The Post, was also knocked her to the ground, kicked repeatedly and stripped of her camera and phone. wapo.st/4yY8dJw

Top comment on the YouTube thread of Megadeth's very non-political "Peace Sells" youtu.be/rdEupVsL07E?is=ygU3…

interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works already-clean.goodfire.com/

*En clases de español para extranjeros, mientras hablamos de partes del cuerpo* ALUMNO 🇺🇸 : Entonces, "hand" es "mano," "fingers" es "dedos", "foot" es "pie" y "feet" es "pies". YO: Exactamente. ALUMNO 🇺🇸 : Vale. Entonces, ¿cómo se dice "toes"? YO: Bueno... en realidad no tenemos una palabra para "toes". Los llamamos "dedos de los pies" ALUMNO 🇺🇸: ¿"Dedos de los pies"? ¿"Fingers of the feet"? YO: ... Sí. ALUMNO 🇺🇸 : ¿Me estás jodiendo? ¿Tienen como 17 tiempos verbales y no tienen una palabra para "toes"? ¡¿Es neta?! YO: Oye, oye, oye; aquí el único lenguaje inferior es el que no diferencia entre "ser" y "estar" ni entre "amar" y "querer".