Diego Rimer B. @diegorimer

🚨 ÚLTIMA HORA: Tras el ataque de Ucrania a un centro de datos ruso, las menciones de «genocidio» y «Free Palestine» se han desplomado en X. Todo este movimiento es una operación psicológica masiva.

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🇻🇪 Starlink in Venezuela! 🇻🇪

DogeDesigner @cb_doge

2 weeks ago

BREAKING: Venezuela’s telecom regulator, Conatel, has officially authorized Starlink to provide satellite internet nationwide. 🇻🇪 After June’s earthquakes damaged phone and internet networks, Starlink provided more than 1,600 kits to support rescue teams, medical staff and

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No es fácil encontrar este tipo de vídeos, pero a los fabricantes de robots no les va quedar más remedio que empezar a compartirlos. El robot de la imagen es el Figure 03, de la empresa Figure, trabajando en la sección de logística de la planta de BMW Group en Spartanburg (Carolina del Sur). Su tarea es la secuenciación: sacar piezas que llegan sin ordenar en contenedores grandes y dejarlas en el carro de secuencia en el orden en que las va a pedir la línea de montaje. Por cierto, dicen que NVIDIA está interesado en invertir 1.000 millones de dólares más en Figure y lo que está claro es que estas máquinas van a ser las responsables de la próxima gran demanda de computación.

Jensen Huang says AI token use flipped this year: from 70% or more on closed models to about 70/30 in favor of open models. "And because it's infrastructural, for many companies and many, many companies and countries, you need to have control over your own infrastructure." "I need open weights so that I can fine-tune them, put them into my data flywheel, make them better and better every day with my intelligence and my domain expertise." "And then I need to have control over it because I have a company to run, and I can't rely on somebody else's service." "At the beginning of this year, it was 70%, maybe even higher, closed model tokens and 20% open model tokens. And now it's running at about 70/30 the other way." - Jensen Huang, Nvidia founder and CEO, on The Ezra Klein Show (New York Times), uploaded September 23, 2026. He did not name the data behind the percentages. Nvidia sells the chips companies use to run models on their own infrastructure.

🚨🇺🇸 | GOLPE JUDICIAL A ANTHROPIC: El tribunal federal de Washington ratificó la decisión del Gobierno de Donald Trump de excluir a Claude de la cadena de suministro del Departamento de Guerra por considerarlo un riesgo para la seguridad nacional. La disputa comenzó cuando Anthropic se negó a aceptar términos que permitieran “cualquier uso lícito” de su IA y mantuvo dos límites: armas autónomas letales sin supervisión humana y vigilancia masiva doméstica. La mayoría del tribunal sostuvo que esas restricciones podían hacer que Claude rechazara tareas legítimas en sistemas militares.

@__tinygrad__ Interesting assessment, can you please share the survey or survey link.

Prime Minister Benjamin Netanyahu addressing the UN General Assembly: “We are going to win because we have no choice.”

Mark Zuckerberg pushes back on Dario Amodei and Sam Altman’s calls for AI regulations saying, “There’s a lot of rhetoric that is filled with doom … and I don't think that we need industry-wide coordination to not mess this up.”

Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR. We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use. Read more: anthropic.com/news/claude-di…

AI is technology that is built and improved by people, who have a responsibility to develop and deploy it thoughtfully. And helping people benefit from AI means taking its challenges seriously. The technology industry needs to do that work.

Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out. It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend. The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans). More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains. In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries. Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology. I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

Anthropic @AnthropicAI

a month ago

Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR. We don’t yet understand what this system does, but only a handful of known

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🚨Jensen Huang just took a shot at OpenAI, Anthropic and AI doomers: "Nobody's building more compute than the people asking to be slowed down." and also attacked Geoffrey Hinton's 10% doom prediction: “All of his predictions have been wrong. Just because it comes from a scientist doesn't make it scientific.” he is clearly frustrated with these claims. this is such a good interview by @ezraklein, watch the full version: youtube.com/watch?v=HjurAW…

La genre me pregunta que: ¿Cómo escribir tanto y comienzo nuevos proyectos a un ritmo sin precedentes? Estiy usando Pocket: capturo ideas y citas en segundos y las recupero ordenadas y esquematizadas #publi #HeyPocket heypocket.com/?sca_ref=12389…

Jensen is basically saying: stop hiding behind AI doomsday theories and enforce the laws we already have. Unauthorized cyber access? Illegal. Product causes harm? Liability. Break a service contract? Existing law applies. His sharpest point: “Don’t talk about the theoretical without doing the practical.” OpenAI and Anthropic are no longer just research labs. They are becoming huge product companies with massive revenues. Jensen’s argument is simple: Hold them accountable for real incidents first. Then debate hypothetical superintelligence laws.

.@SecScottBessent: "It is humans who are responsible, not the AI. The Hugging Face incident — that is the responsibility of the OpenAI management, not a bunch of agents... These labs need to take responsibility for themselves."

“0% chance” AI will end humanity by 2030. They must be doing it (the fearmongering) for ulterior reasons. Maybe it's political, maybe it's just attention grabbing." - Jensen Huang's new interview with CBS News, with Jo Ling Kent (@jolingkent ) He pushed back strongly against warnings that increasingly capable AI could escape human control this decade. --- From 'CBS News' YT channel (full video link in comment)

EXCLUSIVE: AI actress Tilly Norwood glitches and starts speaking CHINESE during her interview with Piers Morgan and real-life actor Tom Conti... Watch the full interview at 7pm (BST)👇 📺 youtube.com/piersmorganunc… @piersmorgan | @TillyNorwoodX

@DataOfStats The Esequibo is missing from the map simulation selection.