Jason Dorn

Building @endorphin_ai

[Jason Dorn @happy_zilla]

@Madisonkanna @katedeyneka @teej_dv @leerob https://t.co/H5NN9XPy6v

[Jason Dorn @happy_zilla]

@ns123abc https://t.co/H5NN9XPy6v

[Jason Dorn @happy_zilla]

https://t.co/Om0EQQQtFM
#aiagents #claude #claudecode

[Jason Dorn @happy_zilla]

https://t.co/WzQk0lLPm7

#techtube

[Jason Dorn @happy_zilla]

@elonmusk

[Jason Dorn @happy_zilla]

@BrianRoemmele 10s is blsht! Its 3 million per year! 😂😂did you hear about supply chain?

[Jason Dorn @happy_zilla]

@PowerBruteHQ https://t.co/1ruruZjX7x

[Jason Dorn @happy_zilla]

@WealthMail Just do this kettlebell workout
https://t.co/BHt9scjwZY

[Jason Dorn @happy_zilla]

@TechByTaraa I will replace AI!

[Jason Dorn @happy_zilla]

@Men_Of_Purpose Blsht! Ppl tired of this hustle! Effortless life is our goal

[Dilmer 🔜 AWE @Dilmerv]

📣 Today, I’m excited to walk you through Unity’s NEW AI offering, Meta MCP Extensions, and agentic tools to demonstrate how we can 𝗕𝘂𝗶𝗹𝗱 𝗔 𝗙𝘂𝗹𝗹 𝗩𝗥/𝗩𝗥 𝗚𝗮𝗺𝗲 from start to finish using these AI tools in a practical way. 

🎥 Full video available at: https://t.co/4p5ZzdaRfg

📌 Here’s what I’m covering today:
- Unity VR project setup (with OpenXR plugins)
- Installing the Unity AI Assistant and demos
- Configuring Unity MCP + Meta MCP Extensions
- Configuring Claude Code & MCPs
- Building a VR/MR Basketball Game with the Unity AI Assistant, Claude Agent, and external Claude Code CLI
- A lot of iteration with Claude Code + the Meta XR Simulator

💡Also, it’s been a while since I've posted a new video, and I’m genuinely excited to be back, especially with a topic like this that I know many devs have been waiting for.

[Jason Dorn @happy_zilla]

@Matt_Pinner WTF?

[Jason Dorn @happy_zilla]

@elonmusk Ivan detected 😱

[Jason Dorn @happy_zilla]

@jackcoder0 Its bull 🐂 💩. Prompt is not working. You need complete skill ! Like i did for AI Teacher - Teach Me https://t.co/tpUJRQ18z9

[Jason Dorn @happy_zilla]

@yashhq_22 Team of agents
https://t.co/m4jjIm2z45

[Stephen James @stepjamUK]

I've spent years in both academic and industrial robotics labs. Every team I've worked with, from research groups to warehouse automation startups, was rebuilding the same infrastructure from scratch.

There's great open work out there, ROS, Open-X, LeRobot. But the infrastructure to actually train and deploy robot policies at scale has mostly stayed locked inside a handful of labs and companies. You can't iterate on what you can't access.

So at Neuracore, we made two calls from day one:
The core platform is open-source. Inspect it, extend it, contribute back.

Academia gets the full platform free for research. Students, PhDs, PIs. If you're working on robot learning, infrastructure shouldn't be what slows you down.

Robotics 2.0 won't be delivered by any single company. It'll be delivered by a generation of builders who had good tools at the right time.

We want @Neuracore_AI to be one of them.

Get started today for free: https://t.co/9kJpxyydJs

[Jason Dorn @happy_zilla]

I decided to rebrand my YouTube channel about AI in a dark style

https://t.co/blGI2Obkqu

[PixiJS @PixiJS]

Been testing GPT 5.5 and it's implemented the HTML-in-Canvas spec
Worked for both WebGL and WebGPU out of the box

Then created this demo with the PixiJS + GSAP Skills

Hopefully there will soon be no excuses to make boring websites

[OP Nico @OP__Nico]

Me and @andrew_d_d were busy getting Animateur to the next level!

Andy, did refactoring and UI improvements, while I went and got all of his fantastic work hosted somewhere for EVERYONE to enjoy his updates, even the non-techies!

Please enjoy: https://t.co/mqI62wV3Jy

[Vaishnavi @_vmlops]

NVIDIA DROPPED A MOTION DIFFUSION MODEL FOR HUMANOID ROBOTS

trained on 700 hours of mocap data

kimodo generates high-quality 3D human and robot motions from text prompts

you control it with:
→ full-body pose keyframes
→ end-effector positions/rotations
→ 2D paths and waypoints

works on human skeletons and unitree G1 robot

plug the outputs directly into mujoco or retarget to other robots using GMR

has a web-based interactive demo with a timeline editor. runs locally

needs ~17GB VRAM to run inference

open source under apache 2.0

https://t.co/kiqX768K0I