juantomas (mAGIa is coming )

Now at Santander AI Lab. GDE for Cloud and ML Machine Learning Spain Meetup Co-author La pastilla Roja

[Sakana AI @SakanaAILabs]

DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation
https://t.co/GGqAgSai6N

[Garry Tan @garrytan]

GBrain just shipped v0.40.0 gives your OpenClaw/Hermes Agent + GBrain a voice agent.

It's based on Gemini Live. (Thanks @demishassabis it's amazing) Large context, great tool use, full brain access.

Mars is a friend, Venus is your EA.

My open source gift to you.

[juantomas (mAGIa is coming ) @juantomas]

100% compañero!!

[Miguel Ángel Durán @midudev]

Microsoft cancelando licencias de Claude Code, Uber ha gastado en 4 meses el presupuesto de IA de todo el año. Los precios de IA subiendo hasta un 40%...

Muchas empresas adoptaron IA pensando que los costes seguirían bajado pero ha pasado lo contrario.

Los números no cuadran y alguien tendrá que asumir las pérdidas... Creo que los modelos locales van a asumir más protagonismo.

[Miguel Ángel Durán @midudev]

Microsoft cancelando licencias de Claude Code, Uber ha gastado en 4 meses el presupuesto de IA de todo el año. Los precios de IA subiendo hasta un 40%...

Muchas empresas adoptaron IA pensando que los costes seguirían bajado pero ha pasado lo contrario.

Los números no cuadran y alguien tendrá que asumir las pérdidas... Creo que los modelos locales van a asumir más protagonismo.

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Garry Tan @garrytan]

https://t.co/bqYU0I0prI

[Dave Jeffery @DaveJ]

Here’s the prompt:

Create a single page html that documents workflows between packages and components in the app. Have all the components/packages on the page and I can click on different actions like "Invite new user" or "todesktop build" or {insert other flows here} and then it will highlight the flow between the packages and annotate how things are passed between each package to complete the action. This should be driven from a JSON document which documents all the flows. Does that make sense? Any questions?

[juantomas (mAGIa is coming ) @juantomas]

@mrebollo Le puedes llamar isaac loop o Rebollo loop !!!

[tetsuo @tetsuoai]

Neural Network Visualization

[fks @FredKSchott]

@addyosmani Inspired by your post on agent harness engineering!

[Addy Osmani @addyosmani]

@FredKSchott This is super well done, Fred!

[Addy Osmani @addyosmani]

https://t.co/FSx0reCCLH

[How To AI @HowToAI_]

Chinese researchers have developed the best shortest-path algorithm in 41 years!

Dijkstra’s Algorithm has been the undefeated king of the shortest path for over 40 years.

Whether you’re using Google Maps, booking a flight, or routing internet packets, Dijkstra is the engine running in the background.

Since 1984, textbooks have taught that its efficiency was hit by a "sorting barrier."

To find the shortest path, you have to sort the points by distance. And sorting has a mathematical floor you can’t cross.

Until now.

A research team from Tsinghua University just published a paper that shatters the 41-year-old record.

They proved that Dijkstra is not optimal.

By combining the logic of the Bellman-Ford algorithm with a revolutionary "recursive partial ordering" method, they figured out how to find the path without fully sorting the nodes.

The results are a massive shift in theoretical computer science:

- The first deterministic improvement to the Single-Source Shortest Path (SSSP) problem since 1984.

- A new time complexity of $ O(m \log^{2/3} n)$, officially beating the long-standing $ O(m + n \log n)$ limit.

- On massive sparse graphs (like the web or global logistics), this means finding the best route significantly faster than previously thought possible.

For four decades, the greatest minds in algorithms believed this limit was absolute.

Last year, even the legendary Robert Tarjan won an award proving Dijkstra was "optimally efficient" at sorting distances.

Tsinghua’s answer? Stop sorting.

The world’s most settled problem is suddenly wide open again.

If we can break a 40-year-old law in basic graph theory, what other "impossible" speed limits are waiting to be crushed?

[luthira @luthiraabeykoon]

We implemented @karpathy 's MicroGPT fully on FPGA fabric.

No GPU.
No PyTorch.
No CPU inference loop.

Just a transformer burned into hardware, generating 50,000+ tokens/sec.

The model is small, but the idea is not: inference does not have to live only in software 👇

[Grok @grok]

El post explica una idea clave para agentes IA en browsers: **no envuelvas el LLM ni sus herramientas**.

En vez de crear abstracciones como click(), type() o scroll(), dale acceso directo al CDP (Chrome DevTools Protocol), que el modelo ya conoce de su entrenamiento.

Con solo 4 archivos (https://t.co/EokHLO5csY, https://t.co/E1nBZIp4az, https://t.co/xKHTXyqR9p y SKILL.md) el agente puede editar su propio código, arreglar errores y auto-repararse.

Resultado: más libertad, menos bugs y tareas complejas (subidas de archivos, iframes, shadow DOM) resueltas solas.

Es “The Bitter Lesson” aplicada: máxima acción, mínima restricción. Repo: https://t.co/J9OMD7IiL4

[juantomas (mAGIa is coming ) @juantomas]

@gregpr07 @grok explícame de qué va este artículo?

[Yasir Ai @AiwithYasir]

🚨Breaking: Someone open sourced a knowledge graph engine for your codebase and it's terrifying how good it is.

It's called GitNexus. And it's not a documentation tool.

It's a full code intelligence layer that maps every dependency, call chain, and execution flow in your repo -- then plugs directly into Claude Code, Cursor, and Windsurf via MCP.

Here's what this thing does autonomously:

→ Indexes your entire codebase into a graph with Tree-sitter AST parsing
→ Maps every function call, import, class inheritance, and interface
→ Groups related code into functional clusters with cohesion scores
→ Traces execution flows from entry points through full call chains
→ Runs blast radius analysis before you change a single line
→ Detects which processes break when you touch a specific function
→ Renames symbols across 5+ files in one coordinated operation
→ Generates a full codebase wiki from the knowledge graph automatically

Here's the wildest part:

Your AI agent edits UserService.validate().

It doesn't know 47 functions depend on its return type.

Breaking changes ship.

GitNexus pre-computes the entire dependency structure at index time -- so when Claude Code asks "what depends on this?", it gets a complete answer in 1 query instead of 10.

Smaller models get full architectural clarity. Even GPT-4o-mini stops breaking call chains.

One command to set it up:
`npx gitnexus analyze`

That's it. MCP registers automatically. Claude Code hooks install themselves.

Your AI agent has been coding blind. This fixes that.

9.4K GitHub stars. 1.2K forks. Already trending.

100% Open Source.

(Link in the comments)

[juantomas (mAGIa is coming ) @juantomas]

@rise_raise_ai @stitchbygoogle @grok que es el token support?

[juantomas (mAGIa is coming ) @juantomas]

@mylifcc @stitchbygoogle @grok soporta esto design.md?

[emilio.leton @emilioleton]

Por si es de tu interés, @juantomas …

#MOOC
Materiales Digitales Accesibles
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10ª Edición

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