Rodrigo Alejandro (@_Taysuu) header
Rodrigo Alejandro (@_Taysuu) profile picture

AI ✨| Neurotech 🧠 | Futurism Passionate about the intersection of technology, neuroscience & innovation.

Barcelona, Spain
Joined November 2011
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Rodrigo Alejandro retweeted
🤖 WILD: China just deployed a humanoid POLICE ROBOT alongside armed officers for patrols in Shenzhen. This video of EngineAI's T800 deployed in Nanshan District for community patrols is going viral.
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Rodrigo Alejandro retweeted
This is GPT-6 Astra. Anything you can do on a computer, Astra can do for you. Fast.
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Rodrigo Alejandro retweeted
We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all. I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand. Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.
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Rodrigo Alejandro retweeted
China's DR02 humanoid robot is carrying firefighting gear now. Walking into emergency-response work with heavy equipment. Robots are moving from demos to dangerous jobs.
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Rodrigo Alejandro retweeted
Attention, all you geniuses with products, but no marketing skills. Today we’re launching the Founder Starter Kit—4 skills that will help you look and sound like a legit company, including: > Build-a-Brand > App Screens > Product Sizzle > Founder Video Available for Claude via the Pika MCP.
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Rodrigo Alejandro retweeted
We're publishing our 4th Anthropic Economic Index report. This version introduces "economic primitives"—simple and foundational metrics on how AI is used: task complexity, education level, purpose (work, school, personal), AI autonomy, and success rates.
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Rodrigo Alejandro retweeted
Alright, here's my 2026 AI Predictions (What did I miss?): -All meaningful progress benchmarks shift to code gen capabilities. Models write looong systems, debug themselves, and ship real applications. Your dad will proudly show you an app he made. Short prompts expand into thousands of lines of production-ready software. Judgment improves. Gap-filling looks senior, not synthetic. -AGI never arrives cleanly. The definition keeps moving. Even super-expert systems fail to trigger consensus. Capability compounds while debate stays semantic. -English-language capability has converged. New models no longer feel meaningfully better in conversation. Gains continue in deep-research modes, but they are invisible to most users. -Compute prices rise before they fall. GPU costs increasing signal demand still ahead of supply. Subsidies will be a gigantic government debate. Efficiency and scale arrive later. -Video is still the shock vector for 2026. Longer-form output will exist, but higher-quality short form will prevail. Consistent characters, real voices. Video creation adapts to what you consume. What you watch shapes tone, pacing, framing, and narrative style. Output feels personally authored rather than generic. -Apple will go through a leadership change and ink a deal with a major model producer for complete iOS integration. -Fully unsupervised driving arrives. Robo-taxis reprice the whole idea of personal transportation and the Podcast Class proudly gets rid of their cars. -X continues its rise and begins to rival Instagram in usage. The platform becomes a primary distribution surface for content generation, prediction markets, P2P money transfer, and idea distro. -xAI becomes the dominant AI model for conversation. Grok is fully embedded in Teslas. Passengers sit hands-free, talking, learning, and consuming while the car drives itself. -The EU remains the regulatory drag on deployment and iteration. -Human taste becomes more valuable.
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Rodrigo Alejandro retweeted
2026: Everyone releasing their own Agent – autonomous AI that acts, learns, and evolves in the real world. Buckle up!
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Rodrigo Alejandro retweeted
This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to right, but all at once. You start with noise and gradually denoise into a token stream. Most of the image / video generation AI tools actually work this way and use Diffusion, not Autoregression. It's only text (and sometimes audio!) that have resisted. So it's been a bit of a mystery to me and many others why, for some reason, text prefers Autoregression, but images/videos prefer Diffusion. This turns out to be a fairly deep rabbit hole that has to do with the distribution of information and noise and our own perception of them, in these domains. If you look close enough, a lot of interesting connections emerge between the two as well. All that to say that this model has the potential to be different, and possibly showcase new, unique psychology, or new strengths and weaknesses. I encourage people to try it out!
We are excited to introduce Mercury, the first commercial-grade diffusion large language model (dLLM)! dLLMs push the frontier of intelligence and speed with parallel, coarse-to-fine text generation.
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5-10 years from now?
Introducing NEO Gamma. Another step closer to home.
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Rodrigo Alejandro retweeted
Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: genesis-world.readthedocs.io…). The Genesis physics engine and simulation platform is fully open source at github.com/Genesis-Embodied-…. We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: github.com/Genesis-Embodied-… Project webpage: genesis-embodied-ai.github.i… Documentation: genesis-world.readthedocs.io… 1/n
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Rodrigo Alejandro retweeted
Let’s have a good old fashioned GenAI steak-off! 🥩 This test is very challenging for AI models. Hands, consecutive slicing physics & movement, interpretation of ‘steak done perfectly’, steam, juices, etc. Who did it best? Who’s your top three?
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In a not too distant future all this actions and events will happen in the background, a simple prompt will lead to a full website running.
Anthropic just announced Computer Use It allows Claude to control your computer screen based on a prompt and take actions on your behalf The use cases in agentic coding with automated debugging, customer support, and education are going to be INSANE
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Should everyone have access to this?
Sam Altman: by 2030 you will be able to walk up to a piece of glass and ask it to do something that previously would have taken humans months or years and it will do it in dynamically or in an hour
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Can you imagine being offered the option to merge with a Giant AI system so you can catch up with the evolving world? #singularityAI
Some people may Merge with AI... Ilya Sutskever predicts that Interacting with AGI could help us see the world better and improve ourselves. However, as the world changes, some may choose to merge with AI to understand these changes and solve tough problems.
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Rodrigo Alejandro retweeted
It's so over... Monna Lisa Arcade made with: CharacterLora + Runwaygen3 + Elevenlabs
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