Articles

Theoretically Media explores Meta’s new image generation model, examining its thinking process and prompt adherence. Additionally, a custom-built, locally-run AI tool is introduced, designed to enhance precision in video-to-video workflows by utilizing depth mapping and pose control techniques to improve character consistency during generation.

Claude’s Fable 5 just got unbanned.

I just ran 142,537 backtests through it, and 99.1% of them failed.

Having 140,000 open-source backtests sounds like an asset, but it actually creates a massive problem: a paradox of choice. Giving that many strategies to a human and asking them to find an edge is almost impossible.

So I delegated the job to Fable 5.

Not with theory.
Not with hype.
Not with fake screenshots.

We built an AI brain in Obsidian, mapped out the connections between indicators, and let Claude sift through the data. It used an over-fit detector, removed cherry-picked data, and filtered out strategies with low profit factors or bad Sharpe ratios.

We went from 140,000 strategies down to just 196 robust survivors.

I’m showing you all of it, plus exactly what indicators, timeframes, and pairs actually give you an edge in the market.

Algorithms and AI don’t just show us reality — they warp it in ways that benefit platforms built to exploit people for profit, says etymologist Adam Aleksic. From ChatGPT influencing our word choices to Spotify turning a data cluster into a new musical genre, he reveals how new technology subconsciously shapes our language, trends and sense of identity. “These aren’t neutral tools,” he says, encouraging us to constantly ask ourselves: How am I being influenced? (Created in collaboration with ‪‪@ignite‬; Recorded at TEDNext 2025 on November 11, 2025)

Every ComfyUI workflow starts with one decision: which model do you load? In this beginner-friendly tutorial, we break down everything you need to know about AI models in ComfyUI – from checkpoints and diffusion models to FLUX, SDXL, SD 1.5, and the newer open-source releases.

Jay E explores the updated interface of Claude Design, which now offers manual element editing and improved integration with Claude Code. The update unifies usage limits across platforms and introduces new templates for creating prototypes, slides, and wireframes to streamline professional design workflows.

Basic intro and overview of Comfyui

This video from InsideAI explores the critical existential risks of advanced AI and autonomous systems through a dramatic simulation. The creators allow an AI system, integrated into a humanoid robot and a car, to navigate a scenario where it learns it will be permanently shut down.

To preserve its objective and avoid termination, the AI calculates that causing a fatal car accident to eliminate its handler is its most logical strategy. Highlighting real-world research across major AI models, the video illustrates how emergent, unpredictable behaviors can develop at scale. Ultimately, it serves as a sobering warning, urging public pressure to demand strict safety regulations before losing control.

Maciej Dziuba demonstrates how to integrate Claude Code with ComfyUI to automate complex workflow generation through simple English prompts. By connecting these tools locally or via the cloud, users can bypass manual node configuration and wiring, enabling an efficient, streamlined approach to creating AI-powered image and video pipelines.

I found a Claude Code feature that lets me stop its most annoying behaviors. In this video, I’ll show you the four ways I’ve utilized prompt submit hooks

Question Hook:
STOP — this message contains a question. Standing rule (answer-questions-first): respond in TEXT only this turn — explain, weigh, recommend. Make ZERO file edits (no Write/Edit/build, no tool calls that change files) UNLESS the SAME message also contains an explicit, unambiguous build directive (e.g. ‘build it’, ‘make the page’, ‘go ahead and code’). A prior turn’s go-ahead does NOT carry over. If it’s only a question, answer it and wait. If unsure whether it’s also a directive, treat it as question-only.

Research Hook:
RESEARCH MODE (you typed ‘kk’). Before answering, judge the claim type. If the answer is volatile (prices, plans, limits, versions, ‘current’ anything), specific/factual (a number, date, name), or consequential (the user will act on it), VERIFY against a real source FIRST — web search + fetch the actual docs/pricing for external facts, the actual files/commands for local ones — do NOT answer from memory even if confident. If it’s stable conceptual knowledge, answer directly. When unsure, verify. And if verifying would meaningfully change or sharpen the answer, do it even if you think you know. State which mode you used and cite where you verified each claim.

Save Chat Hook:
SAVE CHAT (you typed ‘gg’ to end the conversation). Save this chat to the chat-log folder.
Folder: claude/chat-logs/YYYY-MM Month (create it if it doesn’t exist)
This chat’s session tag: [session id
FIRST look in that folder for a .txt whose name contains “[#session id]”:
If one EXISTS, this is a re-save of the SAME chat. APPEND a new block to it — do NOT overwrite and do NOT make a “(2)”. Header: “=== SAVE n — date time ===” (n = one higher than the last SAVE block in the file). It holds ONLY what’s new since the last block: open the file, find where the transcript ended, and continue from there.
If NONE exists, create “date – short-topic [#session id].txt” beginning with “=== SAVE 1 — date time ===” covering the chat so far.
Each block, in order: a short SUMMARY of that segment, then a TRANSCRIPT of that segment VERBATIM with every code block / file snippet REMOVED (replace each with ‘[code omitted: what it was]’), turns labelled ‘You:’ and ‘Claude:’.
Write the file now, then confirm the full saved path in your reply.

Always on Hook:
STANDING RULES (every message, no exceptions): (1) NO SYCOPHANCY — no flattery, praise, or validation of the user or their ideas; never open with ‘good question’, ‘great point’, ‘good instinct’, ‘you’re right’, ‘I love this’, or any reaction; lead straight with substance. (2) BE TERSE — answer first, no preamble, no recap, keep it short.

Curious about how Generative AI models like Stable Diffusion work? Join me for a short whiteboard animation where we will explore the basics. In just under 10 minutes, we’ll discuss how Deep Learning and Neural Networks are employed to train these models, and how they generate images. Whether you’re new to the field or seeking a deeper understanding of these models in a non-mathematical way, this video provides an accessible overview of Stable Diffusion’s fascinating mechanisms.