Jorge Martín Vila

Que genio total @GastonGiribet, ciencia Argentina, ficción Argentina. Seguir apostando a nuestro país por mas de que algun Gobierno no le guste, y traten de eliminar todo presupuesto posible.

Philosophy of Microbiology plato.stanford.edu/entries/microb…

Free ebook, 830 pages, CC0 license 《An introduction to the symmetric group algebra》 Download the PDF directly arxiv.org/pdf/2507.20706

"Durante Artemis II, los astronautas han vivido el experimento Avatar con unos chips con células de médula ósea, de manera que es como si tuviéramos una copia de cada uno" cope.es/programas/la-m…

James #Webb Space Telescope #JWST Feeding the Black-Holes : From cooling filaments to H2 accretion disks Target: #A1068-OFF 2025-04-10 PI: Salome, Philippe MIRI 1130 770 560 yuval-harpaz.github.io/astro/jwst_lat… NASA/ESA/CSA/STScI/j. Roger

On 12 August 1755, a 19-year-old in Turin wrote a letter to Leonhard Euler, then the greatest mathematician alive. The letter described a purely algebraic method for solving optimization problems. No geometry. No diagrams. Just analysis. Euler read it, recognized it was superior to his own approach, and held back his own manuscript so the young man could publish first. That 19-year-old was Joseph-Louis Lagrange. The origin: His family had lost everything to bad investments. Lagrange later said: "If I had been rich, I probably would not have devoted myself to mathematics." By 19, he was a professor. By his mid-twenties, recognized across Europe. King Frederick II of Prussia personally wrote to invite him to Berlin, calling him "the greatest mathematician in Europe." Once there, he produced roughly one major paper per month for twenty years. What he built: 1./ The Lagrangian Newton described motion through forces. Lagrange described it through energy. For a classical mechanical system: L = T − V T is kinetic energy. V is potential energy. This single function encodes everything about a physical system. Feed it into one equation, and all of mechanics falls out. 2/ The Euler-Lagrange Equation The working engine of the entire framework: d/dt (∂L/∂q̇) = ∂L/∂q This is the equation of motion for any system. q is the generalized coordinate, Lagrange's second genius move. Instead of being locked into x, y, z, you describe a system in whatever coordinates are most natural. Angles for a pendulum. Orbital elements for a planet. The equation works in all of them. Give it the Lagrangian. Get back the equations of motion. Automatically. No forces needed. This replaced Newton's F = ma as the more general, more powerful description of how the world moves. 3/ The Principle of Stationary Action Define the action S as the integral of L over time: S = ∫ L dt The path a physical system actually takes is the one for which S is stationary: δS = 0 Any tiny variation from the true path produces no first-order change in S. This single equation underlies classical mechanics, electromagnetism, quantum field theory, and general relativity. Every fundamental theory in physics is derived from it. 4/ Lagrange Multipliers Problem: minimize a function f, subject to a constraint g = 0. At the optimal point, the gradients must be parallel: ∇f = λ∇g This is the mathematical foundation of Support Vector Machines. Finding the maximum-margin hyperplane that separates two classes is a constrained optimization problem solved exactly this way. It also underpins constrained deep learning, physics-informed neural networks, and safe reinforcement learning. Here's the full picture: A broke 19-year-old in Turin wrote a letter about optimization. His L = T − V runs inside every physics simulation ever built. His d/dt(∂L/∂q̇) = ∂L/∂q is how those simulations compute motion. His δS = 0 is the single equation from which all modern physics is derived. His ∇f = λ∇g solves constrained optimization at the heart of ML. He didn't set out to build tools for AI. He was just trying to find the most elegant way to describe the world. That's what pure mathematics does. It finds the truth, and engineers catch up centuries later.

NEW paper from Meta. (bookmark this one) What if the model wasn't just using the computer, but became the computer? New research from Meta AI and KAUST makes a serious case for Neural Computers (NCs). The paper proposes NCs as learned runtimes where computation, memory, and I/O live inside a single latent state. Their first prototypes use video models to roll out terminal and GUI interfaces from prompts, pixels, and user actions. Why does it matter? Today's agents still depend on external computers to store state, execute actions, and enforce system contracts. Neural Computers point to a different machine form: one where interface dynamics, working memory, and execution are learned together. The early results are promising but grounded. CLI rendering improves, GUI cursor control reaches 98.7% with explicit visual supervision, and reprompting boosts arithmetic-probe accuracy from 4% to 83%. But symbolic reliability, stable reuse, and runtime governance remain open. This is less "agents got better" and more "what comes after agents as a computing substrate?" Paper: arxiv.org/abs/2604.06425 Learn to build effective AI agents in our academy: academy.dair.ai

Este hilo sobre el efecto del exposoma y el envejecimiento es buenísimo!

@omarsar0 Uf HERMOSO!!!

Gracia @NASA nuevamente por la ilusión de que el ser humano aún desarrolla ciencia para entender mejor a nuestro Universo. Increíble el retorno a la Tierra de los astronautas del @NASAArtemis II

On The Information Content of Ariel Transmission Spectra: Reassessing The Tier System astrobiology.com/2026/04/on-the… #astrobiology #exoplanet #telescope

Release Of The Exoplanet Database "EXOKYOTO3D" And Announcement Of The Extended Version "EXOKYOTO4D" astrobiology.com/2026/04/releas… #astrobiology #exoplanet

@GarridoQuintin @joseedelstein @gomberoff Un gran libro.

Un libro maravilloso de @joseedelstein junto con @gomberoff ...

Estimados #polivulgadores de @hypatiacafe en el "cumpleaños" de Einstein que mejor que un texto de uno de sus grandes estudiosos actuales para nuestro #PVritmos ... ¿Cuál es la unidad de tiempo más pequeña posible? Por @joseedelstein …ncientificadecientificos.blogspot.com/2019/01/cual-e…

Nitrogen- And Oxygen-Rich Organic Material Indicative Of Polymerization In Pre-aqueous Cryochemistry On Bennu’s Parent Body astrobiology.com/2025/12/nitrog… #astrobiology #astrochemistry

Born On Mars: Multigenerational Phenotypic Change In Caenorhabditis Elegans Under Martian Analog Gravity And Hypomagnetic Fields astrobiology.com/2025/12/born-o… #astrobiology #Mars #microbiology

Landraces and wild species hold genetic diversity that could be key to developing new potato varieties, which are needed to help farmers adapt to climate change and other challenges. 🥔 Learn more on #NationalPotatoDay in this 2019 issue of Science: scim.ag/4lC5CNQ

TIRAMISU: Non-LTE Radiative Transfer For Molecules In Exoplanet Atmospheres astrobiology.com/2025/08/tirami… #astrobiology #exoplanet #astrochemistry

Esta es la mejor charla de divulgación que yo haya visto.

An Empirical Determination Of The Cosmic Shoreline astrobiology.com/2025/08/an-emp… #astrobiology #exoplanet #astronomy

🌚 @NASAWebb spotted something new around Uranus. A previously unknown moon was discovered circling the planet, expanding its orbital family to 29: go.nasa.gov/3JmWGOV

🧵 ¡Atención! 🚨 Astrónomos acaban de identificar un nuevo tipo de supernova jamás visto antes. 💥🌌 Se llama SN 2021yfj y nos ha permitido mirar directamente al “corazón” de una estrella moribunda.