The NotebookLM clone open-notebook assumes Docker and cloud APIs by default. I installed SurrealDB natively, ran four processes in tmux, and wired everything through Ollama's qwen3.6:35b and bge-m3. I fed it the Qwen3.6 benchmark article I wrote this morning, and it answered with the correct numbers.
A dev.to post about building a Moon Patrol-style 80s game in a few days with AI for an internal AWS Summit contest. The Phaser 3 + TypeScript + Vite stack, combined with splitting into three role-specific AI skills instead of one giant prompt, turned out to be a practical workflow.
A hub for the 5-article series that organizes math symbols in AI and LLM articles for reading, not solving. Covers equations, vectors and matrices, probability and statistics, derivatives, and gradient descent with backprop, plus a reading-order guide for different backgrounds.
Gradient descent, SGD and Adam, backpropagation, vanishing/exploding gradients with residual connections, and learning rate schedules — organized around what each piece is doing at a high level. The goal is reading training logs and model card numbers, not computing anything.
A minimum set of calculus for reading AI and LLM articles — d/dx, e, the chain rule, partial derivatives, and gradients. Focus on what the symbols are doing, not on solving the formulas.
A minimum set of probability and statistics for reading AI and LLM articles — conditional probability, cross-entropy, perplexity, and temperature are the main ones; rigorous Bayes and MLE derivations stay out of scope.
A minimum set of vectors and matrices for reading AI and LLM articles — the dot product and matrix product are the main two; determinants, inverses, and eigenvalues stay out of scope.
A minimum set of math for reading AI, LLM, and image-generation articles — the aim isn't to derive anything, just to recognize weighted sums, S-curves, probabilities, and the 'nudge toward the answer' step of training.
Tested WAI-Anima v1 on Windows + RTX 4060 Laptop GPU (8GB VRAM). Headless execution via ComfyUI API hit a tqdm OSError on startup, but launching ComfyUI normally generates a single image in 55 seconds. Includes the workaround and timing notes.
Tested WAI-Anima v1, Anima preview3-base, and WAI-Illustrious v160 side by side on M1 Max 64GB ComfyUI with same seed/prompt. WAI-Anima inherits Anima's atmospheric lighting and natural running poses but still loses to WAI-Illustrious on tag control and character consistency. Includes i2i pipeline test (denoise 0.5), ~275s generation times, and how the Anima derivative ecosystem (WAI-Anima, CottonAnima, Kirazuri, RDBT) expanded in two months.
Running local models and still getting refusals? LLM safety stacks five layers: input filter, system prompt, RLHF, Constitutional AI, output filter. Where abliterated and uncensored variants cut, and which blocks survive on Gemini, Claude, and local LLMs.
Google DeepMind's AI writing tool Fabula was demoed at CHI 2026 by Piotr Mirowski. Co-designed with 42 professional writers using convergent iteration for story structure. But the timeline shows Fabula was first demoed in May 2025 and entered early access in September 2025 — still a research prototype with no general availability.
