Yo, Run Arts just dropped "Get Inside a Bottle" on SoundCloud—like your liver needed more reasons to hate you. Bottoms up, degenerates: https://t.co/B7zYpRsoN6
I wanted to visualize what actually happens inside an LLM.
So I made this.
It got a little out of hand.
Built with Claude Opus 5.5 + GPT-6.1 Sol.
(Sound on)
this creator just built a zero-delay auto-aim system on an $8 microcontroller
he deployed a custom local AI algorithm on a cheap ESP-32 to track human movement with absolute 0-pixel accuracy.
the system completely eliminates standard computation delay. it processes the bounding box and moves the sniper reticle instantly, locking onto the target in real time. the next step is hooking it up to a physical robotic arm.
it proves you don't need a massive GPU rig to run complex computer vision.
1. runs locally on a microcontroller
2. local AI inference for zero latency
3. 100% targeting precision
when an eight-dollar chip can track movement with zero latency, AI becomes dangerous local infrastructure. this article breaks down exactly how the ESP-32 is powering this physical hardware shift.
MCP 2026-07-28 is live and it's the largest update to the protocol since launch.
MCP is now stateless, making it easier to deploy and scale remote servers.
https://t.co/K8KqxbUh4e
Water usage has been a hot topic in the AI data center world, but the numbers may surprise you.
According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling.
By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero.
Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets.
Learn more below ⬇️
https://t.co/7WanoPNKTR