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How Geospatial Foundation Models let teams skip costly pretraining: compare finetuning vs vision–language zero‑shot, and see how LLMs can orchestrate imagery analysis.
Guide to reproduce the Neutrality Project Release 01: run 18 models on six political axes, record per-axis means, refusal rates, and 95% confidence intervals.
Practical guide to turning traces, logs, and metrics into compact incident packages so AI debugging agents reason, not filter noise—plus safe read-only and approval-first practices.
Guide to albedan/ai-ml-gpu-bench: clone a small harness to time Python ML training and local LLM inference on CPU vs GPU and export metrics to compare latency and cost.
A builder-focused breakdown of Agentic RL for GPT-OSS: what changed, what to implement first, and how founders can decide if the economics work.