- A San Francisco / Austin contact is offering free GPU hours specifically for open-source molecular-dynamics or protein-folding simulations, flagged as a rare opportunity for compute-heavy bio projects.  
- Diffuse.one post “d1-001” claims AI training is thermally capped by Earth’s heat-rejection limits; participants counter that nuclear or space-based radiators and direct-to-space GPU cooling remove the ceiling, making the “inevitable meltdown” argument moot.  
- Discussion revives 1980s-era speculation that efficient AI was already solved with binary {-1, 0, +1} (or even {-1, +1}) neural nets implemented directly in digital logic, bypassing back-prop and floating-point; cites the “icegods” archive and recent NeurIPS work on differentiable logic-gate networks.  
- A new training method dubbed “NoiseStep” is highlighted: 1.58-bit weights, 97 % less energy, 90 % less memory, no back-prop, and a 175 B-parameter model compressed to ≈ 20 MB—raising the prospect of ultra-low-power FPGA or ASIC inference.  
- Anecdotal self-experiments report that 3 g creatine taken at bedtime produces next-day “zero startup time” wakefulness and an internal “hydrostatic pressure” sensation, reminiscent of modafinil’s afterglow; placebo status undetermined.  
- Skepticism voiced toward using large-language-model text dumps as a “save format” for whole-brain state, with the counter-proposal to store raw binary state directly instead of tokenized natural language.