Jay Walia

Programmer

[Nori @NoriRobotics]

Introducing Nori L2

The most capable robot under $1288

Made in America, shipping right now.

[NVIDIA AI @NVIDIAAI]

We took a 30B model and split it in two to write tokens in parallel instead of one at a time.

Introducing Nemotron-Labs-TwoTower: a diffusion language model from NVIDIA Research adapted from Nemotron-3-Nano-30B-A3B. Here’s how it works: one half holds the context, the other writes the tokens, with both reusing the pretrained model instead of training a new one from scratch.

We found it kept 98.7% of the original model’s quality at 2.42× faster generation.

[OpenAI @OpenAI]

We’ve designed and built our first AI chip: Jalapeño.

Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalapeño is purpose-built for the LLM workloads powering ChatGPT, Codex, the API, and future agentic products.

Chips are foundational to the AI economy. Building our own expands our full-stack platform from products to models to infrastructure, and will help us scale intelligence, serve more people, and expand access to AI.

[Google Gemma @googlegemma]

16 parallel runs of Gemma 4 26B A4B on a single NVIDIA DGX Spark!

Pushing 18 tok/s per instance and a 300 tok/s aggregate. It can even hit 32 parallel runs.

This level of concurrency highlights how efficient the architecture is.

[NVIDIA AI @NVIDIAAI]

Today we're shipping Nemotron 3 Ultra.

A 550B MoE frontier-intelligence open model built for long-running agents.

It delivers 5x faster inference and lowers the cost of complex agentic tasks by up to 30% versus other open frontier models.

[Google AI Developers @googleaidevs]

Download the weights on @HuggingFace today:
https://t.co/p09Oggsrbg

[Google Gemma @googlegemma]

We just dropped Gemma 4 Quantization-Aware Training (QAT) checkpoints on Hugging Face!

All Gemma 4 model sizes and their drafters are now optimized with QAT to cut memory requirements and maximize on-device performance!

[Demis Hassabis @demishassabis]

Celebrating the milestone of a massive 150+ million downloads of Gemma 4 with the release of the new Gemma 4 12B model! It's incredibly powerful for such a small model and it’s tiny enough to run locally on a laptop with just 16GB VRAM. Apache 2.0 license - happy building!

[trish @TrisH0x2A]

in 2019 a researcher at Microsoft wrote a paper called "Free List Sharding in Action" and proved that malloc has been slow this whole time

he built a drop-in replacement called 'mimalloc' and published the numbers

you have been using malloc since you started writing C

it works, it is fine, and it is leaving performance on the table

glibc malloc was designed to be general purpose across every possible allocation pattern that generality has a cost

it uses a single global free list per size class, protected by a lock

under any real multithreaded workload every thread is contending on the same lock

the fix is simple instead of one big free list per size class, give every 64KiB page its own free list each page also gets two separate lists: one for thread-local frees, one for frees coming from other threads

cross-thread frees become a single atomic compare-and-swap with no lock thread-local allocation never touches a lock at all

on the larson server benchmark mimalloc is 2.5x faster than tcmalloc and jemalloc under heavy multithreaded workloads on Linux it runs 5.3x faster than glibc malloc with 50% less resident memory

it is used in Death Stranding, Unreal Engine, NoGIL CPython 3.13, and Microsoft Bing Redis ships jemalloc by default but mimalloc benchmarks faster than jemalloc across most workloads

the fast path in the source is 7 instructions on x64 with a single conditional the comment in the source file says exactly this

[Maarten Grootendorst @MaartenGr]

A Visual Guide to Gemma 4

With almost 40 (!) custom visuals, explore the new models from Google DeepMind. We explore various techniques, ranging from Mixture of Experts and the Vision Encoder all the way up to Per-Layer Embeddings and the Audio Encoder.

Link below 👇

[Pratyush Kumar @pratykumar]

📢 Open-sourcing the Sarvam 30B and 105B models! Trained from scratch with all data, model research and inference optimisation done in-house, these models punch above their weight in most global benchmarks plus excel in Indian languages.

Get the weights at Hugging Face and AIKosh. Thanks to the good folks at SGLang for day 0 support, vLLM support coming soon. Links, benchmark scores, examples, and more in our blog - https://t.co/DcCG3zlN8p

[Sundar Pichai @sundarpichai]

Helpful update for students, you can now take full practice SATs for free in the @GeminiApp.

It uses vetted content from @ThePrincetonRev and gives you feedback straight away. Starting with the SAT today, but more tests are on the way!

[Nano Banana 2 Lite @NanoBanana]

Turn anything into an info graphic with Nano Banana Pro 🍌

[AI at Meta @AIatMeta]

Today we’re excited to unveil a new generation of Segment Anything Models:

1️⃣ SAM 3 enables detecting, segmenting and tracking of objects across images and videos, now with short text phrases and exemplar prompts.

🔗 Learn more about SAM 3: https://t.co/CjMnf7fspz

2️⃣ SAM 3D brings the model collection into the 3rd dimension to enable precise reconstruction of 3D objects and people from a single 2D image.

🔗 Learn more about SAM 3D: https://t.co/yXcvts8Ogc

These models offer innovative capabilities and unique tools for developers and researchers to create, experiment and uplevel media workflows.

[Varun Mohan @_mohansolo]

Excited to launch Google Antigravity, our next generation agentic IDE, now powered by Gemini 3!

[Ashok Elluswamy @aelluswamy]

Full video of the ICCV '25 presentation

[Google Cloud Tech @GoogleCloudTech]

The 5-Day AI Agents Intensive course with @kaggle is live! Learn about autonomous AI agents and create your first systems using the Agent Development Kit (ADK), powered by Gemini.

Plus, check out our new Introduction to Agents whitepaper → https://t.co/MGhDGplrbr

[Skild AI @SkildAI]

We built a robot brain that nothing can stop.

Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body.

Meet the omni-bodied Skild Brain:

[Go @golang]

🎉 Go 1.25 Release Candidate 3 is released!

🏃‍♂️ Run it in dev! Run it in prod! File bugs! https://t.co/Ul1xGhvlkf

🔈 Announcement: https://t.co/ydKjUjp8iU

📦 Download: https://t.co/bnBGhlSRTf

#golang

[MIT CSAIL @MIT_CSAIL]

#otd in 1991 Tim Berners-Lee first posted on an online newsgroup about a project he was working on called "The World Wide Web."

https://t.co/HEUDIzVYh5