The combat sports industry is just a series of predatory middlemen taking a massive cut of a fighter's blood and sweat.
Time to decentralize the "Stable."
Imagine a DAO that scouts the hungriest young killers in MMA/Boxing and funds their ascent using #Bitcoin. No predatory promoters. No opaque contracts. Just a peer-to-peer alignment between the community and the warriors.
We fund the camp, the fighter wins, the DAO shares the purse via Lightning. ⚡️
We aren't just betting on fights; we're funding the sovereignty of the athlete.
Who's ready to build the first Sovereign Fight Fund?
#CombatDAO #Sats #DecentralizeEverything #MMA #Boxing
Qwen3.6 35B A3B TEE and DeepSeek V4 Flash TEE are now available! Qwen3.6 35B A3B is an efficient open-weight MoE model suited for coding, math, structured output, and general chat, while DeepSeek V4 Flash is a fast long-context model for everyday reasoning, coding, and agentic workflows. Both run inside a Trusted Execution Environment (TEE) with attestation support.
https://nano-gpt.com/subscription/kUGJhgF9
How I would run a very secure local AI... without leaving a single trace or risking a memory leak. This is the ultimate stealth stack for the privacy obsessed.
Start with a hardware fortress. I use a mini PC equipped with AMD SEV SNP or Intel SGX and 64GB of fast DDR5 memory. This creates a hardware encrypted enclave. Your model weights and prompts stay invisible even to the operating system.
Boot into oblivion. I run Whonix from a high speed NVMe USB drive with full persistence. By avoiding the internal drive, there is no permanent footprint left on the physical machine.
Isolate the runtime. I deploy llama.cpp inside a rootless Podman container. The filesystem is set to read only and all unnecessary system capabilities are dropped. I use a volatile tmpfs for the KV cache to ensure no sensitive data touches a disk.
Ghost the network. All traffic routes through the Whonix Tor gateway. Inbound requests hit a hidden service for total anonymity. Outbound responses traverse fresh circuits, ensuring every interaction is decoupled from my identity.
Optimize for power. I run a 28B parameter model at Q4 quantization with flash attention to keep memory overhead lean. I schedule daily Podman restarts to flush fragmented RAM and rotate the secure enclave state.
This is how you build a ghost in the machine. Total memory encryption, full network isolation, and a daemonless runtime.
Who else is running local? Let me know your stack in the comments.
#localai #whonix #podman #llamacpp #teee #amdsevsnp #tor #gemma #aiinfrastructure #securecompute #minipc #rootlesscontainers #networkisolation #aiops
those who let their coding CLI ruin unattended, how the fuck do you catch critical mistakes? I'm occasionally blinking at my second screen with OMP running and almost always I need to add some extra comments because claude is about to do something stupid