Toaster studio

[Rok | Tadafy @rok_tadafy]

The trailing layers act as a visual echo — reinforcing the action through motion.

Cloneable in Webflow → https://t.co/ci4QFiPuxH

[World of Science @Science_TechTV]

Brain cells making friends with each other on a grid:

[Argona @Argona0x]

i'm not fine after reading this

a guy with a laptop got his own silicon chip manufactured with software Google gave away.

the commercial version of that software rents for up to $1,000,000 a year.

he never signed a vendor contract and never paid for a seat. he wrote the logic, pushed it to GitHub, and nine months later a wafer came out of a fab. getting silicon with your name in it used to take a company. now it takes nine months.

his slot was 160 by 100 microns: about 1,000 logic gates, 8 inputs, 8 outputs, clocked past 50 MHz. more than 600 designs have already come back this way.

this is the open silicon stack. Google and SkyWater published a complete 130nm manufacturing process, DARPA funded the software that turns code into a fab-ready file, and all of it sits in public repositories.

turns out the whole flow fits in a git push:

- write the logic in Verilog, or drag gates around in a browser if you have never done this
- push to GitHub, an action runs synthesis, placement, routing and sign-off on the commit
- OpenROAD finishes place-and-route with no human in the loop, code to fab file inside 24 hours
- SKY130 carries the fab's real design rules, so passing the checks means it is manufacturable
- a few hundred designs share one wafer, which is the only reason a person can afford the masks

nobody puts this part in the thread: 130nm is roughly where the industry stood in 2001, and you wait six to nine months for silicon. this does not get you a GPU. it gets you a real object with your logic inside it.

bookmark this. the video is one of those designs opened layer by layer, and every rectangle in it exists in the file that was sent to the fab.

[Charly Wargnier @DataChaz]

Getting high-quality robot training data is slow and painfully costly.

Human labelers cost ~$50/hour, making it a nightmare for robotics labs to scale.

Today, @perceptroninc just completely changed the math.

They just launched Egocentric, the first in a series of new 'Embodied Reasoning' offerings.

Basically it turns raw video into policy-trainable supervision for 10-15x cheaper than human annotation.

Instead of asking a VLM to guess actions from flat screenshots, it tracks actual physical movement:

→ Extracts 21-keypoint skeletons per hand
→ Tracks persistent left/right hand identity
→ Maps boundaries to actual contact and release

The result?

A new SOTA on the WGO-Bench:

→ +77% jump in end-to-end F1 (0.280 vs 0.158)
→ Outperforms the best pipelines built on Gemini 3.5 Flash & Gemini Robotics-ER 1.6 💥

Watch these 3 awesome examples of Embodied Reasoning in action across home, manufacturing, and assembly tasks.

1/ Home cleaning 👇

[Matthias Niessner @MattNiessner]

📢 FaceAnything (ECCV 2026) Code Release 📢

Turn any image sequence into high-fidelity 4D face reconstructions, without controlled capture rigs.

Try it on Hugging Face & reconstruct your face in 4D!

🔗https://t.co/1t9msPtfHw
🤗https://t.co/zzoRyurIlM
🌐https://t.co/qRqh3rZaOB

[Reid Hannaford @reidhannaford]

Seedance 2.0 is insane.

Blender previs is having a moment in AI filmmaking for a reason.

I wanted to see how far I could push the workflow beyond a simple camera move in an ambush scene.

The workflow:

1. Make a start image in Midjourney

2. Block it out in Blender, animate the camera

3. Feed both to Seedance

The more I test this pipeline, the more convinced I am that hybrid pipelines are the future. The conversation is moving fast but previs is one of the clearest unlocks so far.

Seedance still isn't perfect at matching the reference but it's close.

You can experiment with staging, timing, and camera movement before you ever touch the video model.

Solve the scene before you generate the shot.

[Grummz @Grummz]

Unreal Engine 5.8 has AI integration with Claude and Codex.

Runs in terminal beside the engine, connected via MCP to fully control the Editor.

Place props, generate cities procedurally, and even art direct the lighting.

Unreal Engine 5.8 available today.

Pretty much any Unreal game from now on is gonna need an AI label.

[つきのこ | 🇺🇸AIスタートアップで働く25歳 @Tsuki_RobotAI]

ロボットハンドって、どうやって動いてるの？

その鍵を握るのが「駆動方式」。 大きく3種類あります。
① 直接駆動関節にモーターを直接搭載。 高精度・高応答性だけど、指が太くなりやすい。
② ロープ駆動ワイヤーで遠くのモーターから引っ張る。 細くて軽い指が作れる反面、摩擦や伸びの管理が難しい。
③ リンク機構駆動剛体のリンクバーで力を伝達。 シンプルで堅牢、高出力だが、自由度に制限が出やすい。

AIロボットが人間の作業を学習するためには、まず人間の手に近い動きができるハンドが必要。テレオペのデータ品質も、ここにかかっています。

[3Dgamedev @unity3dvfx]

This is seriously inspiring 🤯
Love how Makan Gilani focuses on movement, shape, and reusable procedural systems instead of relying on flashy visuals. That “AAA feel” with simple forms is such a powerful reminder that great game feel starts with strong animation and design.

[Vaibhav Sisinty @VaibhavSisinty]

This is actually insane. 🔥

NVIDIA built a single AI that replaces decades of animation technology.

15,000 frames per second. 2 milliseconds of delay. For robots and games.

It's called MotionBricks. One neural network trained on 350,000 motion clips. You tell it: go here, pick up this sword, do it in zombie style.

It generates everything else foot placement, balance, transitions, follow-through in real time.

No animation graphs. No hand-crafted transitions. No per-task training. One model does it all.

In the demo, a character navigates a space, picks up a sword, vaults over a bench, sits down, and switches between zombie, injured, and skipping styles. Every single frame generated live by the AI.

And here's the part that matters most.

This is now the core motion engine inside NVIDIA's GR00T the stack powering humanoid robots used in research globally.

Same AI that animates game characters is now teaching robots how to move their entire body.

vc: @NVIDIARobotics

[Massimo @Rainmaker1973]

Mori3 is a modular robot made of triangular modules that reshape on demand, forming arms, walkers or tracks and saving space in spacecraft.

[Anže @anzeznidarsic]

3D point cloud (classified LiDAR) with density between 10 and 40 points m2 and 15 cm true ortophoto is available for viewing and download for entire Slovenia. https://t.co/FTUhfZYevb

3D oblak točk (klasificiran LiDAR) gostete med 10 in 40 točk na m2 in pravi ortofoto z resolucijo 15 cm je na voljo za pregled and prenos za celotno Slovenijo.
https://t.co/FTUhfZYevb

[0xMarioNawfal @RoundtableSpace]

NVIDIA CEO JUST SHOWED A $249 DESKTOP AI COMPUTER THAT CAN RUN LARGE LANGUAGE MODELS LOCALLY

[HOUSE LOVERS @hutdesigns]

Hidden deep in a Norwegian forest is a museum that looks like it's from the year 2077

[Andrea Intg. @andreintg]

I was a bit hesitant about showing stuff like this just a month ago 😅

When we started showcasing real-time AI + SDF sculpting, I was afraid professionals would laugh if I showed no effort on the input models. The shape strength slider was also hidden in our first iteration, so I had no choice but to at least try and knock some more interesting shapes together.

Now that we're starting to focus on more powerful features and shape strength is finally unlocked, I'm starting to appreciate just playing with simple shapes.

Different stages of production have different needs. Sometimes you want full authoring over your creations, while other times you just want to quickly explore new ideas.

[Toaster studio @BolaricAndrej]

@theoscarhoole Claude

[Toaster studio @BolaricAndrej]

@lorenzo_pravata Map

[0xMarioNawfal @RoundtableSpace]

ANY CITY ON EARTH CAN NOW BE TURNED INTO A 3D WORLD

* Open-source tool generates full 3D city maps from real OpenStreetMap data
* Exports directly to GLB for Unity, Blender, AR, drones, and simulations

Crazy.

[Lukas Ziegler @lukas_m_ziegler]

End of dancing humanoids era.

Beginning of calisthenics humanoids era.

Atlas is more physically capable than majority of humanity