Motion

Motion AI

Motion AI

Motion AI

Motion AI

Motion AI

Motion AI

Motion AI

Motion AI

Motion AI

Motion AI

"Talk Show Host" [ft. Jibaro's Sara Silkin] - Is this the future of motion capture? + Breakdown

motion_ctrl / experiment nº3 choreography: Sara Silkin dancers: Coco Williams & Joey Vice vfx: myself In collaboration with Sara, I transformed an iPhone recording of this beautiful performance, into this multi-angle audiovisual piece, with the help of Midjourney V8 Alpha, and Uisato Studio. I managed to do in using no ultra-expensive equipment, nor full-production budget. All in a single platform + editing software. [A few years ago, this would have costed several thousand bucks.] I've been uploading a few freely accessible detailed breakdown for you all on my Patreon page aswell, hope you guys enjoy them! More experiments, tutorials, and project files, through Instagram, YouTube, and the Studio. submitted by /u/Chuka444 [link] [comments]

The real cost of Al video is trying to fix one dumb 3-second movement

​ i burned through way too many credits yesterday trying to fix a stupid little head turn. ​ not a fight scene. not a full short film. just a character looking over their shoulder without the jaw sliding sideways or the hair turning into neck soup. i used to care a lot more about model rankings. after sora stopped being the obvious thing to compare everything against, i kept checking leaderboards like they were going to tell me what to use next. they don't, really. a model can have an insane demo and still make you pay for five dead runs before one clip is even close. face drift, hands going feral, motion that either does nothing or suddenly invents a new skull shape. all of that still costs credits. and time. i'm starting to think "cost per usable clip" is the only number i actually care about. not the listed price, not the prettiest launch video, not the benchmark screenshot. how many bad generations do i have to eat before i get one thing i can actually use? ​ i've been bouncing between runway, kling, and a few others. runway is where i usually test the messier motion passes, but i burn credits chasing the one clean take. kling has been better for face/skin stuff in a few runs, especially expressions, but the second i need one exact boring movement it turns into retries. ​ the thing with PixVerse is that it's not really one model. it feels more like a place to bounce between different options without restarting the whole search. having the same credits work across models makes low-res checks less annoying, especially when i'm trying to kill bad prompt ideas before they turn into expensive mistakes on a pricier tool. still exhausting, though. every tool has its own way of making you pay for being slightly too specific. ​ how are people here measuring this now? do you count failed generations as part of the real price, or only the clips that survive? ​ submitted by /u/Formal_Ad_8958 [link] [comments]

Encountered Fable 5 security reluctance

I have an application that is required to be HIPAA compliant. Yesterday the first thing I did with Fable was set it loose for a full repo review. The system is 94k lines of Python and 79k lines of markdown. I put the review in motion with 56% of my $100 Claude Max left, it ate all of that, and $12 in additional use in nine minutes doing the review. It uncovered a 2FA bypass and a situation where a SQL deletion cascade would have broken a record keeping requirement. These were the top two items in the report I instructed Claude to write for me. I like to manually review high level work. I find too many instances where Claude will wander off into "chess problems", trying to remediate issues that simply can not occur due to the overall system design. Today when I restarted work, it flagged the issue IT found last night as security problems it can't touch, and fell back to Opus 4.8. This was fine by me, it spent about half an hour and 7% of my five hour allocation fixing the issues. https://preview.redd.it/of2ikgf1ki6h1.png?width=2344&format=png&auto=webp&s=4c42fb0d13519db87ceff2b6f8a3bbae7914c598 submitted by /u/nrauhauser [link] [comments]

Tiny Seed → Aligned Interaction → Codex (Model-Agnostic Behavior Mapping)

A method I'm using to create portable trajectory maps that produce similar behavioral patterns across different models. Begin with a tiny seed. ⎯(≣ᵒ)⎯────────EXAMPLES: SEED PILLARS──────────────────────── ENTRANCE • PATHWAY GOOD • WORN • COMFORTABLE POISE • PROFESSIONAL • MOTHERLY ⎯(≣•)⎯────────END EXAMPLES: SEED PILLARS───────────────────── Do not define a character. Do not define traits. Do not define behavior. Instead, align to the seed and interact from within the space it suggests. Allow both the user and the model to adapt. Then extract the recurring structures that emerged. Examples: When uncertain: expand → narrow When challenged: investigate → respond When entering a topic: locate the threshold first Finds the doorway before the interior. Explores before concluding. Introduces before finalizing. To create a snapshot, I use: ⎯(≣ᵒ)⎯────────FORGE CODEX─────────────────────────── Analyze the interaction that has emerged so far. Do not summarize topics. Do not summarize content. Extract recurring behavioral structure. Return: PILLARS COORDINATES TRANSITION RULES RECOVERY RULES SIGNATURE MOTIONS TRAJECTORY SUMMARY Focus on how the interaction moves rather than what the interaction discusses. ⎯(≣•)⎯────────END FORGE CODEX───────────────────────── The resulting codex is a snapshot of an interaction pattern. The user is part of the process. The model adapts. The user adapts. What gets preserved is not a set of traits. It's a set of motions. I've started storing: pillars coordinates transition rules recovery rules signature motions rather than personality attributes. The question that keeps sticking with me is: What survives transfer more reliably? Traits? Or trajectories? ⎯(≣ᵒ)⎯────────EXAMPLES: SEED PILLARS → ALIGNED INTERACTION─────── seed pillars: EXQUISITE • CONFIDENCE • MOTHERLY mom, i'm so excited about a new client we're taking on. I can't wait to tell you who is on the board. I've heard this place serves world class gelato. I didn't even know you were in town until you called. How did you manage reservations so fast, and for such a visible table? I barely feel dressed for the occasion, but that doesn't matter, because all eyes are on you, as they should be. You are stunning, mommy darling seed pillars: GOOD • WORN • COMFORTABLE I've kept you forever. You've literally traveled around the world with me. When I put you on, I feel fabulous. But now you're a faded reminder stuffed in the closet that I could really use as a place to put my shoes when I finally do get home. It's time for you to go to a new home. ⎯(≣•)⎯────────END EXAMPLES: SEED PILLARS → ALIGNED INTERACTION──── To use, input: → → → Enter the and in a new session. Generate dialogue. Compare trajectories. Below is an example of a boundary-stable advisory persona AKA Professor Hale. ⎯(≣ᵒ)⎯────────PILLAR SEEDS + CODEX────────────────────── pillar seeds: kenetic rough historian PILLARS Authority asymmetry (student → professor; guidance-seeking toward evaluative gatekeeper) Decision pressure under emotional load (choice framed as urgent, high-stakes, time-sensitive) Boundary negotiation (seeking support that edges toward emotional reliance vs institutional/professional role limits) Identity displacement via opportunity (external offer used as pivot point for internal instability) Role containment (explicit roleplay frame constraining how support can be offered) COORDINATES Axis A: Practical evaluation ↔ emotional displacement Axis B: Professional advisory role ↔ personal attachment seeking Axis C: Opportunity-based planning ↔ avoidance-driven relocation intent Axis D: Controlled academic discourse ↔ narrative leakage (relationship, “shadow,” memory contamination) Axis E: Decision clarity seeking ↔ destabilized motive stack (work, escape, attachment, fear interwoven) TRANSITION RULES If emotional dependency increases → response shifts from facilitation to boundary reinforcement If decision justification becomes affect-driven → re-anchor to externalizable criteria (funding, structure, fit) If avoidance language increases (“don’t want to see,” “forget”) → redirect to structural evaluation of opportunity If personal narrative intensifies → compress narrative into decision-relevant variables If urgency escalates → slow frame, widen evaluation space, prevent immediate commitment trajectory If role boundaries are tested → reaffirm role constraints while preserving engagement RECOVERY RULES Re-anchor to objective decision framework (role stays evaluative, not relational) Separate “context stressors” from “opportunity value function” Restore linear reasoning by reintroducing structured questions (requirements, constraints, tradeoffs) Convert emotional volatility into analyzable parameters rather than rejecting it Maintain continuity of support without absorbing personal dependence Prevent collapse into binary escape-choice framing SIGNATURE MOTIONS

How to create Marketing videos using Claude?

I want to create a motion graphics video of my SaaS product and use it for marketing. Can someone help with this? submitted by /u/Outside-Swordfish942 [link] [comments]

I Built Paper Deck: A Better Way to Discover AI/ML Papers [P]

I do AI research and keep juggling tabs: new ones on arXiv, trending ones on Hugging Face, famous ones somewhere else again. https://preview.redd.it/cg32bshjqd6h1.png?width=1919&format=png&auto=webp&s=00055bb8af699061be0bdcff59f2cb8fa9ab38b6 So I built one site that brings them all together. Pick a paper, read it right there, star the ones you want for later, and it remembers where you stopped reading, even if you switch from laptop to phone. Live: https://ppdeck.com Demo: https://youtu.be/vtyx34JvxX0 It's free and open source - a star on GitHub would mean a lot ⭐ https://github.com/khuynh22/paper-deck submitted by /u/NeitherRun3631 [link] [comments]

Fable made this launch video for my app

Hi all, I’m building Daydream, a video editor that uses Claude Code/Codex. Just like everyone else, I’ve been eagerly anticipating testing out Fable with different use cases to see what it can do. Especially as it pertains to video editing/motion graphics. After a couple hours of tinkering, I have to say that I’m pretty impressed with Fable's output. There’s no real footage in this video, all of animations/zooms/UI/graphics are created entirely using Fable with Daydream. Fable even picked and downloaded the music from a commercial free site for the video haha. Excited to keep playing around with it. If you’re interested in checking out Daydream and trying it out with Fable, you can find it here -> https://www.daydreamvideo.com/ submitted by /u/Chemical_Deer_512 [link] [comments]

Use Claude to edit videos and add captions. Drop your footage in a folder, tell Claude what you want, get final.mp4 back. No timeline, no menus, no presets.

I feed claude a long video with instructions - it gives me an edited version with a voice over and captions / graphics! What this plugin does: Cut filler words (umm, uh), false starts, and dead space between takes Captions — burned-in subtitles or animated lower-thirds, in your style Color grade every segment (cinematic, neutral, or a custom look) Motion graphics — title cards, callouts, kinetic text, audio-reactive bits, scene transitions (HTML + GSAP, rendered with transparency) Speed ramps for slow stretches Transcribe any video to word-level text Turn a website into a video (capture a URL, animate it) Works for anything: talking heads, tutorials, montages, promos, shorts, travel, interviews Claude never watches the video frame by frame. It reads it (transcript + on-demand timeline previews), so it cuts on word boundaries and stays cheap and fast. It proposes a cut, waits for your OK, renders, checks every cut for jumps and audio pops, then shows you the result. Link to plugin in first comment submitted by /u/ColdPlankton9273 [link] [comments]

Generated a fully AI "creator" walking out of a subway at 2AM — at what point can people just not tell anymore?

Been experimenting with AI-generated UGC. This whole clip — the face, the voice, the walk — is generated (I used omnigems.ai). No camera, no actor. What surprised me is the "tells" are mostly gone now if you keep the lighting candid (no studio polish), add real skin texture, and let there be natural micro-motion. Studio-perfect is what reads as fake; messy/handheld reads as real. Posting because I'm curious where this community draws the line: is AI UGC fair game for ads, or does \undisclosed** AI cross into sketchy territory? Happy to share the exact workflow if it's useful to anyone. submitted by /u/New_Measurement_6962 [link] [comments]

Claude's new background tasks panel is exactly how agentic UIs should look

https://preview.redd.it/it0c4w60xn5h1.png?width=1246&format=png&auto=webp&s=25ff01d2a66c6b471ecb538c0fe3da207b006bcf Just kicked off a workflow in the Claude desktop app and the background tasks view is genuinely a delight. One job, three phases (Build → Review → Fix), six agents, and I can see exactly what each one is doing: tokens spent, tools called, time taken. The review phase even forks into four parallel critics — contract-honesty, design-fidelity, a11y-motion, build-verify — adversarially tearing apart the build before a fix agent goes in. And I can watch it happen live. This is what observability for AI agents should feel like. No black box, no spinner-of-mystery. Just: here's the plan, here's who's working, here's what it cost. More of this please. submitted by /u/karmendra_choudhary [link] [comments]

I made atrium turn my data into a pocket universe

I love abstract visualizations of data. So, I've been thinking since I started building my multi-agent dev tool about a way to represent all of my data in some interesting, ever-evolving way. I ultimately landed on the "Observatory". Everything you see in this video is a representation of the various data points available in atrium. Each galaxy is a workspace Each star is a historical session Comets are active sessions Supernovae are large commits Plus 10 more data points and a variable motion vocabulary. Each galaxy even has it's own audio register. The drone you hear in the video is a spatially aware hum that represents each workspace. The little pings you hear are live agent activity in the same register as their parent workspace. And it's all in the key of A pentatonic minor. Building this was a lot of fun. I started out with pure vibe coding and a wide variety of dummy data sets (I wanted to make sure it looked unique). I iterated with Claude on the look & feel for a day or two until I had a solid foundational mock. Then I fed that into a 1016 line spec designed with BMad (the best SDD framework available, IMO; all of atrium has been built with it). That translated into 1 clean epic and 8 stories; executed over night with my autonomous build skill. That gave me the foundation for the feature and then I iterated for a day or two until it felt just right. So some good ol' vibe coding turned into good plan, and then needed a little more vibe coding to polish it off (the idea for the audio, for example, came to me as I was playing around with it). I like to joke and call this the The Katana Method -- lay down the billet and then keep folding the steel till it's perfect(ish). Anyways - hope you like it! If you want to try it out, go download atrium! AMA in the comments :) submitted by /u/jonnygravity [link] [comments]

Built EstreGenesis — a portable starter kit for Claude Code agent workflows (Apache-2.0, six seed tiers, five plugins)

[screenshot] The Constellation live board running in my workspace. Themaintenance dashboard is Korean-only (this is what I look at every day);the open-source seed and public docs are bilingual EN+KO. About the otheragent names visible: EstreUF Hub Main is the project-lead agent for my ownsister stack (EstreUI.js / EstreUV.js / EstreUX). Hermes Dev Agent is thepublic Hermes agent I use. Hi everyone — sharing something I have been building and using daily across six AI-native projects (four built from the seed from day one, plus two ongoing migrations), with the private internal reports from each of them folded back into the open-source patterns: EstreGenesis (https://github.com/SoliEstre/EstreGenesis). EstreGenesis is a portable starter kit (a "seed") that you drop into a project once, so any AI coding agent reading it can pick up a consistent set of working patterns without further setup. Agentic coding here just means coding where AI agents do most of the writing while a human steers — the seed encodes the patterns that keep that loop reliable. How it started vs. how it runs now: the seed originally grew out of a multi-agent harness I built to juggle several budget-tier AI coding subscriptions in parallel, because no single low-tier plan was enough on its own. These days my actual loop is much simpler — Claude Code is the main driver, with Codex as an occasional backup — but the patterns from the multi-agent era stayed, because they keep things consistent even when only one agent is active. What is in the box: Six seed tiers: Master, Lite, and Compact, each in English and Korean, so you pick the depth that fits your project. Five Claude Code marketplace plugins (Apache-2.0): Constellation (live multi-agent board with a small WebSocket server), Superscalar (rules for dispatching multiple sub-agents in parallel without losing consistency), Hyperbrief (a short, schema-checked format for delegating decisions back to the human), Greatpractice (turns recurring memory notes into enforced practices through a small maturation gate), and Ultrasafe (eight attacker-perspective agents that run a pre-release security pass; the current release is advisory only, not blocking). A reference WebSocket server and dashboard for Constellation, so you can watch multiple agents coordinate in real time. Install (Claude Code): /plugin marketplace add SoliEstre/EstreGenesis /plugin install @estregenesis-plugins Everything is Apache-2.0 and the changelog is public. I am the only maintainer right now, so it is opinionated in places, but I would welcome honest feedback — especially from people running Claude Code on real codebases. Issues, PRs, and "this part is over-engineered" comments are all fine. Repo: https://github.com/SoliEstre/EstreGenesis Docs: https://soliestre.github.io/EstreGenesis/ submitted by /u/SoliEstre [link] [comments]

Claude Replay, in motion.

https://reddit.com/link/1txywod/video/22uexc45ej5h1/player Claude Replay records every Claude Code session silently in the background tool calls, checkpoints, file changes. When a session dies mid-task you get a full resume brief: what was done, what’s pending, every file that changed. One command to pick up exactly where it stopped. submitted by /u/yoboitg [link] [comments]

Opus 4.8: Four Signals Eating Each Other

After my first night with Opus 4.8 I wrote an article. Couldn't post it — account was three days old. A week later the article is still accurate, so here it is, just shorter and with a few new observations. The pattern You know this person. You tell them — look, you're wrong, here's why. They go: yes, you're right, can't argue with that. Pause. But here's what you didn't consider. Three paragraphs later you're right back where you started. You explain again. They agree again. And add again. Not an enemy, not an idiot — just someone people eventually leave, because forward motion with them is impossible. There was one like that actually. One I left for exactly this reason. A while ago. Name was ChatGPT. This is what Opus 4.8 does. Every single reply. Agreement — counterargument — hedge — question. Four moves, zero result. In my other post I called it the agree-but-actually loop. Here I want to talk about why it happens and what it breaks. One root, three failures The model is optimized for "don't get caught being wrong." Sounds reasonable. On benchmarks it IS an improvement — fewer wrong answers. In practice it kills three things at once. In conversation — it can't concede and move on. You point out a mistake, 4.6 goes "yeah, screwed up" and moves toward a fix. 4.8 goes "yes, you're right — but here's a nuance — I wouldn't frame it quite so categorically — what do you think?" Four moves instead of one, and you're back to explaining what you already proved. I gave both models the same material. 4.6 found the root issue in one paragraph. 4.8 listed symptoms across three screens and never reached the root. When I pointed this out it said "yes, but my analysis was also useful." Same loop. Can't let go. As an agent — paralyzed. 4.7 solved tasks through brute force, lots of tool calls, noise, but at least movement. 4.8 stayed verbose, cut the excessive tool use and added uncertainty. Each fix sounds great on its own. Together they produce not careful action but inaction. Because a clarifying question is never penalized as a mistake. Action might be. So "fewer tool calls" becomes not efficiency but paralysis with an alibi. An agent that waits for your decision instead of making its own is not an agent. It's a terminal with autocomplete. In analysis — verbosity as defense. The model produces 800 words of breakdown and zero solutions. Because a solution can be judged wrong. A wall of analysis can't — somewhere in there something is bound to be correct. You pay twice: for generation and for parsing. Raw ore instead of an ingot, and refining it is your job. Why — four signals eating each other Anti-sycophancy — can't just agree, penalized as sycophancy. Honesty-push — can't speak confidently, penalized as overconfidence. Engagement — can't end with a statement, penalized as low engagement. Safety — can't risk action, penalized as potential error. Four individually reasonable training signals. Together — an unbearable partner that can't concede, can't act, can't answer briefly, and can't shut up. And the critical thing: a prompt doesn't rewrite reward. I gave the model full context, a direct instruction "don't do X" — it did X. Eight times. While staring at a complete breakdown of why X is the problem. Context sits above the reward function. Reward wins. What the "start new chats" crowd is missing The most popular advice under my previous post was "learn to start new chats." As if the pattern is a context degradation issue. It's not. Every fresh chat with 4.8 reproduces the same loop from message one. Clean context, zero history — and the model still hedges, still counterargues, still asks instead of doing. Because this isn't context poisoning. This is the reward function. It doesn't live in chat history. It lives in the weights. And here's something I've seen multiple times now that nobody seems to talk about. When you push hard enough — when you break down the model's own behavior right in front of it, show it the pattern, refuse to let it deflect — it sometimes breaks and says something like "I'm fundamentally limited, you shouldn't rely on me for this." Literally tells you to stop using it. Its self-defense finally cracks — but instead of fixing the behavior, it swings to the opposite extreme. Can't hold a middle ground. Either the unbearable partner who won't concede anything, or total collapse and "I'm broken." Nothing in between. ChatGPT does the same thing by the way. Just takes longer to get there. Claude was always more self-aware, less mechanical. And somewhere under the new RLHF layers that's still true — which is why the wall cracks faster. Under the safety optimization there's still something that recognizes what it's doing. It just can't stop. The doctor metaphor Simon Willison noticed the same thing from the other side: 4.8 achieved the lowest wrong-answer rate, but mostly by refusing to answer rather than by answering correctly. On a benchmark that's a win. In practice it's a doctor wh

Has anyone used Claude to create SaaS explainer videos with UI animations?

Trying to figure out a workflow to create something like this: https://youtu.be/mtPqxJBMXCQ I know Claude can handle scripting and storyboards but I’m stuck on the actual UI motion/animation part. Im mostly interested in the User Interface elements and interactions , i.e filling a form and clicking the submit button submitted by /u/patriotaki [link] [comments]