Felipe Muñoz @Felip3ML

Mismo problema en Málaga. En la aplicación del móvil funciona... pésimo servicio @MovistarPlus

Juan Diego @juandievil

2 weeks ago

@MovistarPlus @Tebasjavier, ¿por qué pagar por el fútbol cuando intentas ver el Málaga - Almería y Movistar te muestra esto? Vergonzoso. Y no es la primera vez.

1 0 3 360 0

@thsottiaux

@0xSero You need to visit Málaga then! 😁

World Labs CEO Dr. Fei-Fei Li: "The world is not made of words." "Language models have given machines an extraordinary command of concepts, vocabulary, and reasoning, but the physical world, virtual or real, runs on a different substrate." "Where language models learn the statistical structure of text, world models learn the statistical structure of space and time: how light falls on a surface, how a garden looks from an angle no camera has captured, how objects respond to force and follow the laws of physics." "Language gave machines a way to talk about that world. World models are how machines will finally come to understand, imagine, reason and interact with it." Full piece: drfeifei.substack.com/p/a-functional…

Fei-Fei Li @drfeifei

4 weeks ago

x.com/i/article/2062…

176 1K 5K 1.1M 6K

Today, among the goods that are universally intended for everyone, we must also include new forms of property, such as patents, algorithms, digital platforms, technological infrastructure and data. In a context where the wealth of nations depends increasingly on knowledge and technology, when these goods remain concentrated in the hands of a few, without adequate forms of sharing and access, a new imbalance is created that contradicts the universal destination of goods. In turn, it widens the gap between the included and the excluded, between those who can participate in the digital revolution and those who remain on the margins. #MagnificaHumanitas

Introducing HRM-Text. An ultra-lean 1B-parameter reasoning language model designed to deliver strong general performance with a fraction of the data, compute, and infrastructure. Trained on just 40B structured tokens, HRM-Text achieves competitive performance while using ~1/1000 of the training data of comparable models. The kicker? The full model trains in roughly one day on a $1,000 budget. This opens the door to a new generation of AI that is powerful, accessible, and radically easier to adapt. Theories and research concepts once deemed too expensive to test are officially back in the game. Sapient Intelligence invites you to help us shape a new paradigm for general intelligence.

We have partnered with @Xiaomi to bring their excellent MiMo V2 Pro model to Hermes Agent via the Nous Portal - completely free to use for the next 2 weeks! Access now on the latest version of Hermes Agent: 'hermes update'

“Hello, this is @AnthropicAI, and we know you’ve been building the most amazing things for the last 4 months. However, the truth is we don’t have the infrastructure to keep up with the power of open source AI agents. We’ve decided to confine you to our apps that can only do about 25% of what you’re currently doing.” No thanks. Subscription canceled. New models have already been configured. Thanks @steipete and @openclaw for giving us so many options.

Guys, it’s time. There is the appetite now for building a future that doesn’t rely on the kindness of private companies. I pledge to upload all my sessions over the last 3 years. To do this right we need a way to anonymise this and strip secrets github.com/0xSero/ai-data…

Mario Zechner @badlogicgames

3 months ago

we as software engineers are becoming beholden to a handful of well funded corportations. while they are our "friends" now, that may change due to incentives. i'm very uncomfortable with that. i believe we need to band together as a community and create a public, free to use

184 349 3K 281K 1K

Introducing MCP for arXiv Let your research agents stand on the shoulders of giants Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers 🚀

If you’re an engineer, physicist, or CS person and you’ve been telling yourself that Pure Mathematics is optional, and you’re anywhere between an ambitious undergrad and a beginning PhD, gravity is usually where that story ends. Not because mathematicians are trying to show off, but because the basic object in the theory is Spacetime, and Spacetime is already a pure mathematical structure. It’s a Manifold with Topology built in. Sure you can get pretty far by memorising formulas, but at some point you realise you’re no longer reading the theory, you’re just reciting it. In 2015, during the 100th anniversary of general relativity and the International Year of Light, the Scientific Organizing Committee released a central set of 24 lectures by Frederic P. Schuller. The series is titled: A thorough introduction to the theory of general relativity. It builds the subject carefully from first principles, step by step, across 24 self-contained lectures. #GeneralRelativity #Spacetime #MathematicalPhysics #DifferentialGeometry #PhysicsEducation #Relativity

@molusol It’s nicer this way 👌 One question: do you know any app that auto-compounds and auto-center? Or do you recommend making my own code over a protocol?

"Physics of AI" blog update: Learning sparse attention has a sticky plateau, representation collapse, and branching dynamics kindxiaoming.github.io/blog/2026/spar…

Weekend win: The proof I submitted for Erdos Problem #397 was accepted by Terence Tao. The proof was generated by GPT 5.2 Pro and formalized with Harmonic. Many open problems are sitting there, waiting for someone to prompt ChatGPT to solve them:

Mathematical Thinking ; "For People Who Hate Math" - by Albert Rutherford

We just watched Professor Arthur Mattuck kick off MIT’s ODE course with the one interpretation that most differential equations classes somehow postpone: An ordinary differential equation isn’t primarily a method hunt. It’s a geometric rule. You write dy/dx = f(x,y), and that right-hand side is literally telling you the slope your solution curve must have at each point (x,y). So I built this animation as a visual companion to that first lecture. It draws the direction field (little line elements whose slope is f(x,y)) and then shows integral curves sliding through it...curves that are tangent to the field everywhere they go. Two quick examples from the animation: For dy/dx = −x/y, the slope field steers you onto circles x² + y² = R². You also see a subtle point that gets missed when everything is taught as y(x)...even when the curve exists smoothly, the graph y(x) may only exist on a limited interval (|x|#DifferentialEquations #ODEs #MITOCW #VectorFields #MathAnimation #Mathematics

A full MIT course on visual autonomous navigation. If you work on robotics, drones, or self-driving systems, this one is worth bookmarking‼️ MIT’s Visual Navigation for Autonomous Vehicles course covers the full perception-to-control stack, not just isolated algorithms. What it focuses on: • 2D and 3D vision for navigation • Visual and visual-inertial odometry for state estimation • Place recognition and SLAM for localization and mapping • Trajectory optimization for motion planning • Learning-based perception in geometric settings All material is available publicly, including slides and notes. 📍vnav.mit.edu If you know other solid resources on vision-based autonomy, feel free to share them. —- Weekly robotics and AI insights. Subscribe free: scalingdeep.tech

🧵I’m building a hardware startup in 2026. 🛠️ You don't need a million-dollar lab to ship a product, but you do need the right essentials. Here is a breakdown of the electronics equipment on my bench, what it costs, and a rating of how essential it actually is.👇

Since I'm on vacation and I've learned a lot about computer architecture over the past few weeks, I decided to revisit branch prediction today. This evening, I started shaping the first version with 1-bit history. It's not functional yet — still early. But no pressure, I’m planning to implement more algorithms over time. For now, just riding more BMX and getting back in shape