Open Hardware and Hidden Bandwidth: JetKVM, Apple's Neural Engine, and the DIY Frontier
How this was made Verified AI
Every Intellegix briefing is generated from that day's broadcast and run through automated checks before it publishes — with a human paged on any flag. Here is the trail for this edition.
John Carmack posted a thread this week warning against behaving like what he called an 'out-of-touch kung fu master' — the pattern in which experienced engineers dismiss AI coding tools the way a traditional martial artist might dismiss mixed martial arts techniques, only to be outcompeted by someone who adopted everything useful regardless of origin. The post drew 141 upvotes and 171 comments, with Carmack's credibility on the question reinforced by decades of documented frontier work in performance optimization and his reputation for avoiding hype.
The JetKVM Mini — 157 upvotes, 75 comments — is a small, open-source, affordable KVM-over-IP device aimed at the prosumer and homelab market. KVM, short for keyboard-video-mouse, enables control of a computer at the hardware level, below the operating system, meaning it functions even during a kernel panic or a BIOS error where software remote access cannot. Professional KVM switches from vendors such as Raritan or Aten can cost hundreds to thousands of dollars; the JetKVM project is building equivalent functionality at a fraction of the price, with open hardware and open firmware.
The Apple Neural Engine reverse engineering story drew 156 upvotes and 27 comments, and represents a meaningful technical achievement. Apple's Neural Engine — the dedicated machine learning accelerator in all modern Apple Silicon chips — is partially inaccessible through Apple's official Metal and Core ML APIs, which constrain which operations can be run on it. A researcher reverse-engineered the direct memory access interface to the Neural Engine and extracted 50 gigabytes per second of memory bandwidth that Apple's frameworks were not exposing. To contextualize that figure: it is roughly the full memory bandwidth of a GPU tier that cost thousands of dollars in 2022, extracted from a chip found in a laptop or a phone. The finding suggests Apple's M-series chips contain ML capability that has not been surfaced through official channels, whether because the APIs are immature, because Apple is preserving the bandwidth for its own applications, or because exposing it would require opening hardware security boundaries the company prefers closed.
Homebrew 7.0.0 shipped this weekend with 62 upvotes and only 17 comments — the low comment count being characteristic of a smooth release. The package manager underpins the development environment of most macOS engineers. Separately, a developer who built a build visualizer for the Bun JavaScript runtime — 139 upvotes, 28 comments — produced the tool while investigating unexpected compile-time behavior, and the project's existence signals ecosystem maturity: developers are invested enough in Bun to build observability infrastructure around it rather than simply using the default path.
A post about integrating a non-Wi-Fi Mitsubishi air conditioner into the Home Assistant smart home platform drew 93 upvotes and 46 comments. The author reverse-engineered the serial communication protocol between the AC unit and its wired remote control, then built a bridge translating those signals into Home Assistant commands. The comments accumulated accounts from people who have applied the same methodology to different appliances — a community systematically adding intelligence to hardware that was never designed for it.