Rodolfo

[Superman @thesupermannx]

Microsoft open-sourced a 4B model that turns any image into a production-ready 3D asset in 3 seconds.

It’s called TRELLIS.2, a fully textured, physically accurate 3D models with PBR textures out of the box.

→ Full PBR (base color, roughness, metallic, opacity)
→ Handles hair, cloth, glass, non-manifold geometry
→ Exports .glb ready for Unity/Unreal/Blender
→ Runs locally, ships in 3 seconds

It's not a demo or a research preview. The full training codebase is public.

You can fine-tune it on your own asset library and get a model that generates in your studio's exact style.

100% Open Source

[VECERT Analyzer @VECERTRadar]

🚨 INTELLIGENCE ALERT: Massive Leak of 500,000 SAT Records – Mexico 🇲🇽📉

Our Analyzer platform has detected a high-impact security breach targeting Mexico's tax infrastructure. Threat actor s1ethx7z has put up for sale a database containing detailed information on half a million taxpayers registered with the Tax Administration Service (SAT).

Victim: SAT Taxpayers (Mexico) 🏛️.
Threat Actor: s1ethx7z 🎭.
Volume: 500,000 RFC records.
Date: March 26, 2026 🗓️.

📋 Compromised Data (PII and Tax Profile)

This leak is extremely dangerous because it combines official identifiers with details regarding the citizens' economic activity:

🔹 Legal Identifiers: Full names, CURP, and RFC.
🔹 Contact Information: Physical addresses and phone numbers.
🔹 Tax Profile: Tax regime, economic activity, email address, and SAT status.

Monitor:

https://t.co/wk9bZJ3laQ

#CyberSecurity #Mexico #SAT #RFC #DataBreach #s1ethx7z #IdentityTheft #FiscalSecurity #InfoSec #CyberAlert #HackingNews #CURP #SATMexico

[Bo Wang @BoWang87]

Today my X feed is overflowing with actual medical breakthroughs:

🇲🇽 Mexican scientists eliminated HPV
🇪🇸 Spanish researchers cured prostate cancer in mice
🇯🇵 Japan restored motor function in paralyzed patients via regenerative medicine
🇰🇷 Korean scientists report reversing colon cancer
🇻🇳 Vietnamese clinicians show blood cancer can be completely treated

Biomedical science is advancing at an unprecedented, accelerating pace.

A genuinely great day for medicine. 🧬🚀

[Rodolfo @70d01f0]

Oye @BanamexContacto , la sucursal Narvarte está negando el servicio para realizar transferencias interbancarias argumentando que el servicio cierra a las 3:00, lo dice la gerente. Usaría la aplicación si me funcionara.

[Greg Brockman @gdb]

New model in our API — GPT-4.1. It's great at coding, long context (1 million tokens), and instruction following.

[Hunter Kallay @lazukars]

MIND-BLOWING: You can now build a real, functional iOS app with one sentence.

Rork writes the code, designs the UI, and publishes to TestFlight automatically.

Here are 7 WILD examples:

[Matt Dancho (Business Science) @mdancho84]

🚨 BREAKING: Microsoft launches a free Python library that converts ANY document to Markdown

Introducing Markitdown. Let me explain. 🧵

[Esenachoman @EseNachoman]

Esto está pasando ahora, ayúdenme a viralizar @LaSEMOVI @SSC_CDMX @adn40 @Excelsior @Milenio

[Sakana AI @SakanaAILabs]

Introducing The AI CUDA Engineer: An agentic AI system that automates the production of highly optimized CUDA kernels.

https://t.co/DoloC7BGHq

The AI CUDA Engineer can produce highly optimized CUDA kernels, reaching 10-100x speedup over common machine learning operations in PyTorch. Our system is also able to produce highly optimized CUDA kernels that are much faster than existing CUDA kernels commonly used in production.

We believe that fundamentally, AI systems can and should be as resource-efficient as the human brain, and that the best path to achieve this efficiency is to use AI to make AI more efficient!

We are excited to publish our paper, The AI CUDA Engineer: Agentic CUDA Kernel Discovery, Optimization and Composition. We also release a dataset of over 17,000 verified CUDA kernels produced by The AI CUDA Engineer.

Paper: https://t.co/Rn9ioA10As
Kernel Archive Webpage: https://t.co/hqXoQqAvdS
HuggingFace Dataset: https://t.co/Lh1xEYxZJv

The AI CUDA Engineer utilizes evolutionary LLM-driven code optimization to autonomously improve the runtime of machine learning operations. Our system is not only able to convert PyTorch code into CUDA kernels, but through the use of evolution, it can also optimize the runtime performance of CUDA kernels, fuse multiple operations, and even discover novel solutions for writing efficient CUDA operations by learning from past innovations!

We believe The AI CUDA Engineer opens a new era of AI-driven acceleration of AI and automated inference time optimization.

We (@RobertTLange, @_Aaditya_Prasad, @Floating_Martin, @maxencefaldor, @yujin_tang, @hardmaru) are excited to continue Sakana AI's mission of leveraging AI to improve AI.

[vittorio @IterIntellectus]

HOLY SHIT IT'S HAPPENING

AI can now write genomes from scratch.
Arc Institute an NVIDIA just published Evo-2, the largest AI model for biology, trained on 9.3 trillion DNA base pairs spanning the entire tree of life.

it doesn’t just analyze genomes. it creates them
1/

[Satya Nadella @satyanadella]

A couple reflections on the quantum computing breakthrough we just announced...

Most of us grew up learning there are three main types of matter that matter: solid, liquid, and gas. Today, that changed.

After a nearly 20 year pursuit, we’ve created an entirely new state of matter, unlocked by a new class of materials, topoconductors, that enable a fundamental leap in computing.

It powers Majorana 1, the first quantum processing unit built on a topological core.

We believe this breakthrough will allow us to create a truly meaningful quantum computer not in decades, as some have predicted, but in years.

The qubits created with topoconductors are faster, more reliable, and smaller.

They are 1/100th of a millimeter, meaning we now have a clear path to a million-qubit processor.

Imagine a chip that can fit in the palm of your hand yet is capable of solving problems that even all the computers on Earth today combined could not!

Sometimes researchers have to work on things for decades to make progress possible.

It takes patience and persistence to have big impact in the world.

And I am glad we get the opportunity to do just that at Microsoft.

This is our focus: When productivity rises, economies grow faster, benefiting every sector and every corner of the globe.

It’s not about hyping tech; it’s about building technology that truly serves the world.

[AshutoshShrivastava @ai_for_success]

This is 🤯 crazy...
Now your AI avatar can take Zoom calls in real-time, and you don’t even have to sit in front of the camera. Imagine giving an online interview now.
What is real anymore??

5 examples 👇

https://t.co/mfNUjmrDi3

[Nikki Siapno @NikkiSiapno]

Load balancing algorithms you should know.

Effective load balancing is crucial in system design, providing high availability and optimizing resource utilization.

Let's look at how some of the most popular load balancing algorithms work.

🔹 Static Algorithms

1) Round robin

It distributes requests sequentially between servers, ensuring equitable distribution.

Despite its simplicity, it does not account for server load, which might be a drawback when demand changes significantly.

2) Random

Implements a simple way of distributing requests regardless of server load or capability.

This form of load distribution is basic, less precise, and suitable for less complicated applications.

3) IP hash

Uses a consistent hashing method depending on the client's IP address to route requests.

This technique is one way to ensure session persistence by consistently directing requests from the same client to the same server.

4) Weighted round robin

Improves round robin by assigning requests based on server capacity, aiming to better utilize resources by allocating more requests to higher-capacity servers.

This approach seeks to optimize resource use, though actual results can vary with request complexity and system conditions.

🔹 Dynamic Algorithms

5) Least connections

Intelligently sends requests to the server with the fewest active connections, adapting to changing loads.

This technique aims to better reflect current server utilization, potentially leading to more efficient resource consumption.

6) Least response time

Targets performance by routing requests to the server with the quickest response time.

By considering both current server load and performance, this technique supports faster processing, potentially reducing response times for users.

While these are some of the most popular load-balancing strategies, there are other algorithms that also address specific needs and challenges. Choosing the right algorithm is very important to ensuring your application remains scalable, reliable, and efficient.

~~
Thank you to our partner Postman who keeps our content free to the community.

📣 Postman has a special online event. The CTO is discussing AI & APIs.

Secure your seat before they run out (it’s free): https://t.co/75LouY0nPO

[Vaibhav (VB) Srivastav @reach_vb]

Open Source AI/ML is on fire today! 🔥 Multilingual (29) Qwen 2.5 just dropped w/ 128K context too! The 72B rivals Llama 3.1 405B and beats Mistral Large 2 (123B) ⚡

> Trained on an extensive dataset containing up to 18 trillion tokens

> It surpasses its predecessor, Qwen2, with significantly higher scores on MMLU (85+), HumanEval (85+), and MATH (80+) benchmarks

> Excels in instruction following, generating lengthy texts (over 8K tokens), and understanding structured data like tables. It also shows significant progress in generating structured outputs, particularly JSON.

> Supports over 29 languages, including major global languages, and can handle up to 128K tokens, with a text generation capacity of 8K tokens.

They release specialised models as well:

1. Qwen2.5: 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B

2. Qwen2.5-Coder: 1.5B, 7B, and 32B on the way

3. Qwen2.5-Math: 1.5B, 7B, and 72B.

Kudos to @Alibaba_Qwen team for shipping high quality model checkpoints! 🐐

[Java Guides @GuidesJava]

Linux commands:

[Sasha Rush @srush_nlp]

You use GPUs everyday, but do you (actually) know how they work?

GPU-Puzzles (v0.1) - 14 short puzzles in Python with a visual debugger. No background required. Do puzzles, learn CUDA.

Link: https://t.co/Yk1lWRqilN

[Rodolfo @70d01f0]

@recorcholis Continuo esperando el contacto, por whatsapp ni correo responden.

[Rodolfo @70d01f0]

https://t.co/7SVjW2ymQi

[Danny Weber @dannywf]

https://t.co/SVXPRMe97D