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• If the user lives in the EEA, Switzerland or UK, which ElevenLabs Terms of Service apply, and do the voice-model and consent clauses differ from the non-EEA Terms? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1128-01; the original statements below are kept for history and are superseded where the correction says so. Corrected 2026-10-23 - see C3-B678-04; the original statements below are kept for history and are superseded where the correction says so. ElevenLabs publishes two Terms of Service, both 'Last Updated: 09 October 2026': one for residents of the EEA, Switzerland or UK and one for everyone else. Section 4 (Content and User Voice Models) has 27 text blocks (heading and paragraphs) in each; after removing bullet glyphs 26 are word-for-word equal, including the 'voice you are authorized to share with us' wording, the content/voice-model licences and the training opt-out. The one differing paragraph is 4(h): non-EEA bars HIPAA protected health information, the EEA version bars Article 9 GDPR special-category data including biometric data for unique identification. The rest of the differences (withdrawal right, consumer liability, no arbitration, consu...
• When breaking down a script that contains intimate scenes, what should an agent flag for the producer, ADs, IC, costume, post and legal/contract teams, and which flags come from which source? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1108-01; the original statements below are kept for history and are superseded where the correction says so. No single source gives an agent-ready breakdown template, but the pinned union documents together imply a flag list: scene identification (nudity or semi-nudity, sexual activity, other exposing factors), required roles (IC; stunt coordinator and IC where sexual violence is depicted), people involved (performers, background and doubles who appear nude, minors), contract dependencies (rider with script pages and body-part list, 48-hour delivery before call time), schedule and call-sheet items (IC on schedule and day-out-of-days, closed-set marking and crew list, start-of-day placement for sexual-violence scenes, rehearsal slots), cross-department items (costume, prosthetics, digital additions) and downstream flags (take usability for editors, promotion consent, retention). The list is synthesis; each flag cites a source statement.
• What counts as a plot hole or continuity error in a story, and how do open papers define and categorise them so I can tell which kind I am looking for? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1063-01; the original statements below are kept for history and are superseded where the correction says so. Two open papers give working definitions an agent can apply. FlawedFictions (v3) defines a continuity error as a statement contradicted by what else the story establishes, within five plot-hole kinds it takes from a writing source; ConStory-Bench defines consistency errors as contradictions between a fact stated earlier and text later, in 5 categories and 19 subtypes. Both treat intended ambiguity and genre conventions as outside the definition, and neither measures craft judgement about whether a hole matters.
• I need to pace tension in a systemic game or simulation: what do designers actually do (build-up, peak, relax), what goes wrong, and which parts of a pacing controller are documented versus my own proposal? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1070-02; the original statements below are kept for history and are superseded where the correction says so. Documented practice (Valve, Digital Extremes): measure a crude per-player intensity from damage and kills, cycle build-up, peak, hold-off and relax states, keep set-piece bosses outside the throttle, telegraph big events, plan density peaks rather than uniform density, and let designers override the director in special modes. Documented failure modes: fatigue from constant combat and boredom from lulls, memorized static triggers, events the player cannot perceive, raw event streams that are not stories, narrative that simply does not emerge, boring output from thin simulations, and unfair random clusters. Players and communities, not the games, do most of the retelling. Everything about how to combine these into one controller, and how to test it, is the worker's proposal and is labelled below; no source tests a complete recipe.
• How do audiences track a protagonist's goal, and what evidence is there about when a goal change makes viewers feel a new event has begun? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1083-01; the original statements below are kept for history and are superseded where the correction says so. Reviewed reading studies say a stated goal stays highly available until it is satisfied, and that failed goals stay more available than completed ones. In picture stories with text (N=88), a goal shift made a boundary judgement about 3.5 times as likely as goal continuity, while a body-position change within an active goal did not; both lengthened viewing time. In the one film analysed (The Red Balloon, 24 adults) goal changes predicted boundaries only weakly compared with character changes, so goal salience depends on how explicitly the goal is stated.
• What does MPJPE measure, and which public monocular pose benchmarks actually use marker-based optical ground truth? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1090-01; the original statements below are kept for history and are superseded where the correction says so. MPJPE is the mean Euclidean distance (usually in mm) between predicted and reference 3D joint positions, with P-MPJPE reporting the error after a rigid-plus-scale alignment. Of the common benchmarks, only Human3.6M (10-camera Vicon MX T40 at 200 Hz, with reflective markers) is marker-based optical; 3DPW uses body-worn inertial sensors and EMDB uses electromagnetic sensors, and EMDB's authors estimate their own references at about 2.3-2.6 cm PA-MPJPE. So "MPJPE against marker-based ground truth" is a Human3.6M-style statement and is not interchangeable with in-the-wild numbers.
• How many bracketed exposures, at what spacing and range, and with what starting camera settings do practitioners shoot for a lighting HDRI, and where do they disagree? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1085-03; the original statements below are kept for history and are superseded where the correction says so. Three practitioner sources give bracket recipes: CAVE (5 brackets at 3 stops or 7 at 2), Xuan Prada (5-7 exposures, 3 stops apart) and Greg Zaal (5 at 3 EV, but at least 5 at 2 EV and 9 for unclipped light). By simple arithmetic (synthesis) these span about 12 EV to 16-18 EV. All start with a fast shutter so light sources are not clipped, shoot RAW, fixed manual settings and a fisheye rotated in steps. They disagree on how many exposures the balls and chart get (3 vs 7) and where the chart sits. No vendor or standards document read gives numbers; the VES guide only lists HDRIs.
• How does one rakugo performer make many characters distinguishable (voice, manner, kamishimo head-turns), what is documented about speech-synthesis attempts, and what survives in an audio-only or animated medium? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1046-01; the original statements below are kept for history and are superseded where the correction says so. Sources agree that a rakugo performer separates characters by voice (pitch, tone, speech style) and a slight turn of the head, while seated and with only fan and towel. A community guide gives a status rule for head turns (the performer turns to one side when speaking as the lower-status person to the higher-status one, to the other side for the reverse); a university course report confirms 'kamishimo wo kiru' is taught as a skill but gives no rule; the arXiv speech-synthesis study documents that each character differs by dialect, sociolect and idiolect and labels relationship (superior/inferior), distance and number of companions. The one measured result: Tacotron-based models trained on one performer's 13.2 hours did not reach professional quality, but some synthetic speech entertained listeners as much as analysis-by-synthesis speech.
• Which open-weight interactive or action-conditioned world models were released after Oasis and DIAMOND (Matrix-Game 1.0-4.0, Hunyuan-GameCraft, LingBot-World 1 and 2), what is actually released for each, and what licence is attached to which part? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1075-01; the original statements below are kept for history and are superseded where the correction says so. Eight released model lines with public weights were found: Matrix-Game 1.0 (MIT), 2.0 (MIT), 3.0 (Apache-2.0, 5B base and distilled; a 28B model is announced as 'soon'), 4.0 (Apache-2.0; scene checkpoints for three games, released 2026-10-15), Hunyuan-GameCraft-1.0 (Tencent Hunyuan Community License with territory exclusions), LingBot-World 1 (Apache-2.0) and LingBot-World 2.0/Infinity (CC BY-NC-SA 4.0, non-commercial). Licences differ by version inside one project and by component (code, weights, game assets, bundled third-party models). 'Open weights' here means files present on Hugging Face at the pinned revision with a licence text; nothing was downloaded or run.
• Which structural control (depth, segmentation, edges, blur, normals) should I weight to preserve which property, according to the ablations that report it? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1087-02; the original statements below are kept for history and are superseded where the correction says so. In Cosmos-Transfer1's TransferBench results, blur-visual and edge controls give the highest adherence and lowest diversity, while depth and segmentation allow more variation; raising a modality's weight in a region raised its alignment metric there (Pearson 0.93 and -0.92 in the authors' test). RealMaster's ablation found edges preserved faces better than depth for propagation. EPE found G-buffer inputs matter for realism. Normals appear as a control only in vendor text (Reallusion) and EPE's G-buffers, not in the Cosmos Transfer1 README or VACE's task table.
• What is the reliable way to get correct typography on an AI graphic: generate without text and set real type afterwards, or extract text from a flat image (Ideogram Layerize, Recraft no_text)? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B955-08; the original statements below are kept for history and are superseded where the correction says so. Problem. In-image text can misspell, kern badly or use a substitute font, and cannot be edited cleanly. Conditions. Any deliverable where wording, font or brand type must be exact (titles, packaging, CTAs). Method. (1) Generate a text-free base. Recraft V3 has controls.no_text ('Do not embed text layouts', V3 models only); otherwise prompt for 'clear space at top for a title' and describe no text [inference]. (2) Set the type in a layout or editing tool with the licensed brand font; check contrast (C3-B593-04) and line length (C3-B593-05). (3) If a flat image already has text, Ideogram's Layerize endpoint (ideogram-3) returns detected text as positioned text blocks with matched fonts, sizes and colours alongside a text-free base image; image up to 50 MB; an optional prompt guides detection. 'Matched fonts' means similar, not necessarily identical...
• If I POST exactly the same API-format prompt twice, does ComfyUI generate a new image? What does control-after-generate have to do with it? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B879-01; the original statements below are kept for history and are superseded where the correction says so. Problem. Scripts that loop POST /prompt with a fixed seed and expect new files, or that expect the seed to advance. Conditions. ComfyUI v0.42.5, default cache mode, same server process, no IS_CHANGED returning NaN on the output chain. Method. 'control_after_generate' is only a flag in the node's input options (e.g. KSampler seed in nodes.py); a search of server.py, execution.py and cli_args.py finds no backend handling, so seed advancement is performed by the frontend before it builds the prompt. An API-format prompt therefore always carries a concrete seed. When the whole signature chain is cached, execution.execute() finds cached output for each node, calls emit_cached_output (re-emitting the stored UI result) and never runs the node function; at the end, cached nodes with HAS_INTERMEDIATE_OUTPUT also re-emit. The websocket reports the node lis...
• How reliably do human annotators locate acts or turning points in films and screenplays, and do their positions match the 25/50/75 percent rules in structure books? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B688-03; the original statements below are kept for history and are superseded where the correction says so. Viewers segmenting seven films into large parts (20-35 min units) agreed with each other and with critics' segmentations above chance but far from uniformly (Cutting and Armstrong 2019, CC BY). In TRIPOD's 99 screenplays, annotated turning-point means (11.4, 31.9, 50.7, 74.2, 89.4 percent) sit near but not on textbook positions (10, 25, 50, 75, 94.5) with standard deviations of 4.7-12.2 points, and two annotators agreed exactly on only 35.48% (partial 56.67%) at screenplay level.
• What Luma Ray API fields give camera-concept shots and first/last-frame anchoring (concepts, keyframes frame0/frame1, loop, extend)? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B956-04; the original statements below are kept for history and are superseded where the correction says so. Problem. Controlling both the camera move and where a clip starts and ends. Conditions. Luma Dream Machine API, models ray-flash-2 / ray-2 (legacy docs page; it points to a newer API). Method. (1) Camera concept: add concepts: [{key: 'dolly_zoom'}] to the generation request; the page says a /concepts/list endpoint returns the available keys. (2) Start frame: keyframes.frame0 = {type:'image', url}. (3) End frame: keyframes.frame1 likewise; supplying both frame0 and frame1 is the documented start-and-end keyframe request. (4) Request fields shown: prompt, model, resolution, duration, aspect_ratio, loop (true/false). (5) Extend is documented only for generated videos in completed state. Craft use (inference): treat frame0 as the last frame of the previous shot to chain a continuous move, and frame1 as a designed arrival pose; matches 'match on actio...
• How do the vendors' docs describe mask-based editing and inpainting (mask format, polarity, fidelity), and what do they say the mask does not guarantee? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B977-02; the original statements below are kept for history and are superseded where the correction says so. Mask formats are not interchangeable: OpenAI needs a same-size mask with an alpha channel and calls masking prompt-based (the model may not follow the exact shape); Ideogram uses black for the area to edit and white to keep, with a same-size mask that must contain both; Imagen takes a black-and-white mask or automatic background, foreground or semantic masks with a dilation setting and a sampling-step knob; Midjourney's editor now routes inpainting through the V8.X Edit Model. Ideogram 4.5 states that untouched pixels are copied exactly, the strongest fidelity claim among the pages read.
• Higgsfield (consumer/creator tiers): you keep Outputs and may use them commercially, but inputs and outputs may train Higgsfield models, outputs may not train any other model, and the underlying model can be swapped without notice active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1096-01; the original statements below are kept for history and are superseded where the correction says so. Primary Higgsfield Terms of Use (last updated 26 Jul 2026). Ownership: Company "does not claim ownership" of Inputs or Outputs and does not restrict commercial use; output rights survive cancellation or account deletion and can be sublicensed to clients (s4.4). Training: Your Content, Inputs and Outputs "may be used by Company to train" its and affiliates' models; opt-out is only by deleting content or the account, going forward; Enterprise Agreement customers are excluded from training and treated as confidential (s4.4). Marketing reuse only for content you made public on the service or with consent. Likeness: uploading a person's name/likeness/voice means you represent you hold all releases and consents, including for generating Outputs (s4.2(b)). Outbound restriction: you may not use the Service, Outputs or derived data to train, fine-tune or...
• In Kang et al.'s controlled 2D testbed, how do in-distribution, out-of-distribution and combinatorial generalisation differ for video diffusion models, and what can not be concluded about commercial video models? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B680-01; the original statements below are kept for history and are superseded where the correction says so. Kang et al. (ICML 2025) train diffusion-transformer video models from scratch on Box2D/PHYRE simulations so the training set is fully controlled. Within the training range the models track the simulator almost exactly; outside it (new speeds or radii) error is about 35x higher and does not shrink with 100x more data or 14x more parameters. Where every object type is seen but not every combination, scaling the number of combination templates (6 to 60) cut human-labelled 'abnormal' out-of-template videos from 67% to 10%. Attribute-pair tests show the models copy the nearest training example, preferring colour over size over velocity over shape. The setting is a 2D toy world, so the paper does not measure Sora-class or other commercial models.
• What does YouTube's own text say changes in the YouTube Partner Program from 1 Feb 2027 (new-creator thresholds, who is affected, terms deadline), and what is still not stated? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B968-05; the original statements below are kept for history and are superseded where the correction says so. Problem: C3-B566-01 recorded only the help-page banner. Primary text now read: the YouTube Official Blog post 'New opportunities to earn and changes to the YouTube Partner Program' (The YouTube Team, 10 Aug 2026), plus the YPP overview Help page. Source statements: (1) New creators applying for YPP will need 8,000 qualified watch hours in the last 365 days, or 20 million qualified Shorts views in the last 90 days, for ads and Premium revenue sharing. (2) 'This update won't impact creators already in YPP.' (3) Entry thresholds for Fan Funding and shopping products remain unchanged. (4) Creators can review and sign the new terms in YouTube Studio; the terms take effect 1 Feb 2027. (5) The Help page banner says to review and accept the updated terms in Studio by 31 Jan 2027 to continue fully monetizing. Not stated or not verified (checked 2026-10-23...
• What inputs and limits does YouTube document for AI Remix (reimagine a Short with prompts and photos), and which rules still apply? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B970-03; the original statements below are kept for history and are superseded where the correction says so. Problem. AI remix changes someone else's Short with generated video. Conditions. Eligible Shorts only; English prompts only; rollout described as 'coming weeks' on an undated page. Method. In the app tap Remix on an eligible Short, enter a custom prompt or pick a suggestion, optionally upload up to 3 reference photos, wait for generation and preview; audio is generated from the prompt and scene; further edits with Shorts tools before upload. Tip from the page: include a subject and at least one reference photo, and be descriptive if specific audio is wanted. Community Guidelines apply to generated output. Failure modes. Vague prompts. Limitations. No length, watermark or opt-out detail on this page (see C3-B694-10 for guardrails). Version and date. Undated; fetched page.
• How do the FLUX, Imagen, Gemini and OpenAI docs tell me to write text I want rendered in an image (quoting, length, font description), and what limits do they admit? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B955-06; the original statements below are kept for history and are superseded where the correction says so. Problem. Generated posters, logos and title cards need correct words; vendors give different rules. Conditions. Vendor docs fetched 23 Oct 2026; model names change quickly. Method (documented). FLUX 3 Image (BFL): for each text block quote the exact words with the capitalisation and punctuation wanted, say where it sits in the frame, and describe the type (weight, case, colour, character, e.g. a clean sans-serif black font); a word or short line needs no layout, just a quoted string and a place. Imagen on Vertex AI (Imagen 3 guidance): keep text to 25 characters or less, use at most two or three distinct phrases, expect placement variations, name a general font style but do not expect precise font replication, give a size word (small, medium, large), and regenerate until it works. Gemini image docs: be clear about the text, the font style (descri...
• Does CoSER (arXiv 2502.09082) include a human evaluation of LLM-generated character dialogue, and was its LLM judge checked against humans? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B679-01; the original statements below are kept for history and are superseded where the correction says so. Provisional lead, not verified from raw bytes. The pinned abstract page (v3, observed 2026-10-22) shows CoSER trains open models that sequentially portray several book characters in a scene and proposes its own evaluation protocol; the abstract does not mention human raters. A condensed read of the full HTML v3 (not quotable, no raw copy because of the batch storage stop) reports a human study in Section 5.3 with a small panel scoring LLM-simulated scenes on an overall 1-10 scale and a table comparing automatic judges with the human results. The rating criterion was not identified as character fidelity, distinguishability or voice, and no agreement statistic was seen. If confirmed from raw bytes, S52's negative narrows further: humans did rate LLM-generated character dialogue, but not as who-said-it attribution.
• What reference-based tools do vendors document for keeping a character, subject or style consistent across images, what limits do they state, and where do the docs disagree? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B976-03; the original statements below are kept for history and are superseded where the correction says so. Each vendor offers a different reference mechanism: Midjourney style, character and omni references (with a version-drift conflict, since the newest docs say the V8.2 Edit Model replaces omni and character references), Imagen 3 Customization subject and style references with long lists of unintended uses, Ideogram character and style references on 3.0 and reference images on 4.5, OpenAI multi-image edits with a stated consistency limitation, and Adobe composition and style references with a Strength slider. Every vendor that states limits says consistency is imperfect; none gives an acceptance test.
• For each of these open interactive world models, what do the papers and READMEs say about the action space, output resolution, frame rate, context or memory, and hardware, and which cells are measured, claimed or absent? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B981-01; the original statements below are kept for history and are superseded where the correction says so. The numbers are not comparable across systems because they mean different things: Matrix-Game 2.0's 25 FPS is generation speed on one H100 at 352x640; Hunyuan-GameCraft's 25 fps is the video frame rate while its own table lists inference speed of 0.25 FPS (6.6 with distillation) and the text says latency under 5 s per action; LingBot-World 1 claims under 1 s latency at 16 fps; LingBot 2.0 claims 720p at 60 fps without a hardware statement in the text read; Matrix-Game 4.0 takes player input in a game engine and renders low-poly frames, reporting 480p 60 FPS on an RTX 5090 with 112 ms key-press-to-display latency. Memory is explicit only in Matrix-Game 3.0/4.0 (README/report statements) and is stated as absent or emergent in Matrix-Game 2.0 and LingBot-World.
• What do ComfyUI-Manager's security_level, install flags and model-download gate actually permit, and where do docs and README disagree? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1098-01; the original statements below are kept for history and are superseded where the correction says so. Corrected 2026-10-23 - see C3-B595-01; the original statements below are kept for history and are superseded where the correction says so. At ComfyUI-Manager commit a74929c6 (main, observed 2026-10-22; CHANGELOG heading 'Unreleased'), security_level takes four values (strong, normal, normal-, weak; the code default is 'normal'). The README says git-URL and pip installs are no longer governed by security_level but by two default-false flags (allow_git_url_install, allow_pip_install) that also require a loopback --listen. The Comfy-Org docs site (506a4a94) describes a different mapping: it lists git-URL and pip installs and 'fix custom nodes' as High and tells users to set security_level = weak. In code, the fix handler checks 'middle', so the code agrees with the README rather than the docs site. Model downloads through install_model pass three g...
• Luma's public API in Oct 2026 still documents only Ray 2 / Ray 2 Flash - while ComfyUI deprecated its Ray 2 nodes and Luma is absent from current AA video boards active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B976-01; the original statements below are kept for history and are superseded where the correction says so. Primary API docs list two video models - Ray 2 (ray-2) and Ray 2 Flash (ray-flash-2) - with text-to-video and image-to-video via start/end keyframes, resolutions 540p/720p/1080p/4K, durations such as 5 s, loop and aspect-ratio options, and "concepts" (camera-motion presets) retrievable from /generations/concepts/list; the FAQ says API outputs carry no watermark and may be used commercially. Signals that this surface is ageing: ComfyUI deprecated its Luma Ray 2 partner nodes in v0.39.0 (5 Oct 2026, R3), and Luma models do not appear in the Artificial Analysis T2V/I2V boards captured today (C3-B438-01). We did not find (in this pass) API documentation for a newer Luma video model; Luma's consumer app may differ. Practical: before building on Luma's API, confirm model roadmap and support; older archive guidance on Luma camera concepts/keyframes (Ray...
• Which output formats, compression levels and transparent-background settings do the OpenAI image generation and edit endpoints document, and which combinations are valid? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B955-05; the original statements below are kept for history and are superseded where the correction says so. Problem. Choosing format, compression and background so a generated asset keeps alpha and loads fast. Conditions. GPT image models on the Image API (generations and edits). Method. output_format is png (default), jpeg or webp. output_compression is an integer 0-100 that applies only to jpeg and webp; the openapi schema gives it a default of 100 on edits, and the generation schema constrains it with minimum 0 and maximum 100. The guide says jpeg is faster than png when latency matters. background is transparent, opaque or auto (default); transparent requires png or webp output (jpeg has no alpha). The spec says gpt-image-2.5-sunburst and -flare support opaque and transparent backgrounds, while for gpt-image-2 and gpt-image-2-2026-04-21 transparent support is 'in preview'. Failure modes. transparent with jpeg is outside the documented combination. ...
• How do the OpenAI and Google image-editing guides tell me to keep identity, camera angle and lighting unchanged in an edit (change-only-X prompts, input_fidelity, text masks)? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B955-01; the original statements below are kept for history and are superseded where the correction says so. Problem. Fixing one thing in a keyframe (wardrobe, time of day, object) without changing the face, framing or style. Conditions. gpt-image-1.5 edits (OpenAI Cookbook) and Gemini image models (Nano Banana 2/Pro, Google Cloud guide). Method. (1) State what changes and what stays: 'change only X' + 'keep everything else the same', and repeat the preserve list on every iteration to reduce drift. (2) Lock invariants explicitly: preserve identity, geometry, layout, camera angle, object placement. (3) For heavier edits that must keep a face, pass input_fidelity="high" in images.edit (cookbook examples for lighting/weather change, person-in-scene, compositing); the guide says higher input fidelity helps maintain likeness during larger scene edits. (4) Lighting or weather re-stage: change only lighting direction/quality, shadows, atmosphere, precipitation...
• What voice controls does Google document for Chirp 3: HD voices (pace, pause tags, SSML subset, punctuation) and where do they not apply? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B955-10; the original statements below are kept for history and are superseded where the correction says so. Problem: control timing of Chirp 3 HD speech. Conditions: Google Cloud Text-to-Speech Chirp 3: HD voices. Method: pace via speaking_rate from 0.25 (very slow) to 2.0 (very fast), 1.0 unadjusted. Pause tags [pause short], [pause long] and [pause] work only in the markup input field, not the text field; their length is not fixed and adapts to context; the model may occasionally disregard them if placed unnaturally, and excessive use can cause problems. SSML subset (synchronous requests only; not for streaming): speak, say-as, p, s, phoneme, sub, break, audio, prosody and voice; tags not on that list are ignored. Punctuation guidance: periods = longer pause, commas = shorter, ellipses = longer deliberate pause, hyphens = brief pause; reading the script aloud before synthesising is advised. Use (inference): for exact timing use SSML break or post-edi...
• What is Google's documented Veo 3.1 prompt structure, and what do its first/last-frame, ingredients-to-video and timestamp workflows give for shot continuity? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B955-07; the original statements below are kept for history and are superseded where the correction says so. Corrected 2026-10-24 - see C3-B825-04; the original statements below are kept for history and are superseded where the correction says so. Problem. Getting controlled, multi-shot output from one video model. Conditions. Veo 3.1 on Vertex AI per a Google Cloud blog dated October 15, 2025; clips of 4, 6 or 8 s, 720p or 1080p, 16:9 or 9:16. Method. (1) Five-part prompt: [Cinematography] + [Subject] + [Action] + [Context] + [Style & ambiance]. (2) Dialogue goes in quotation marks; SFX and ambient noise labelled (SFX:, Ambient noise:). (3) Negative guidance is phrased as the thing wanted ('a desolate landscape with no buildings or roads' instead of 'no man-made structures'). (4) First-and-last-frame: generate a start still and an end still (the guide uses Gemini 2.5 Flash Image), then describe the transition, e.g. 'smooth 180-degree arc shot'. (5) Ing...
• What do the vendors' own docs promise about seed reproducibility, and which conditions (watermark setting, session, mode, order) break it? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B976-02; the original statements below are kept for history and are superseded where the correction says so. The five vendors state five different strengths of seed promise. Imagen on Vertex AI is the strongest but conditional: same seed gives the same images, only when addWatermark is false, and image order is not guaranteed. Adobe's Firefly API says the same seed, prompt and presets give the same image. Midjourney calls seeds the initial noise, says they are 99% identical in V8.X, not reliable across sessions and not for Turbo mode. Ideogram says only that seed is for reproducible generation and returns the seed used. The OpenAI image guide has no seed parameter in the text read.
• Where do SAG-AFTRA (US), ACTRA Toronto (Canada), MEAA Equity (Australia) and Bectu (UK) agree and differ on auditions, rider timing, body doubles, third-party support, and retention of intimate footage? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1078-01; the original statements below are kept for history and are superseded where the correction says so. Four union or union-branch documents set a 48-hour advance-notice convention in different places: before call time (SAG-AFTRA Quick Guide, Bectu), before signing or rendering services (ACTRA Toronto), and before the audition for the audition script (MEAA). They differ sharply on nudity at auditions: SAG-AFTRA permits one final modesty-garment audition, ACTRA permits a closed callback for viewing the body with at most five producer-side people, MEAA says nudity or semi-nudity should never be required, proposed or agreed to in an audition. MEAA adds a retention limit (destroy non-final-cut intimate recordings within five years); ACTRA gives performers approval over 50 percent of proposed body doubles.
• Which caption file formats does YouTube accept, and which support styling/positioning? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1064-01; the original statements below are kept for history and are superseded where the correction says so. YouTube Help (captured 2026-10-23): basic formats recommended for beginners are SubRip (.srt) and SubViewer (.sbv/.sub), timing-only and editable in plain text. Advanced formats: SAMI (.smi/.sami) and RealText (.rt) with simple markup and no positioning; WebVTT (.vtt) "in initial implementation" with positioning but styling limited to b/i/u; TTML (.ttml, .dfxp; iTT subset) partially implemented; Scenarist (.scc) is YouTube's preferred broadcast format as exact CEA-608. TikTok/Instagram caption documentation not yet retrieved: gap.
• Open video-to-audio (AI foley) models differ mainly by licence: MMAudio weights are non-commercial, HunyuanVideo-Foley excludes the EU/UK/South Korea, ThinkSound is listed Apache-2.0 - check before adding sound to client work active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1037-05; the original statements below are kept for history and are superseded where the correction says so. For adding synchronized sound effects to silent generated clips (many video models still output silent video or weak foley), three widely used open V2A models carry very different rights: MMAudio - code MIT, but "the checkpoints are licensed under CC BY-NC 4.0 and can be used for non-commercial purposes only" (R1); HunyuanVideo-Foley - Tencent Hunyuan Community License, which "DOES NOT APPLY IN THE EUROPEAN UNION, UNITED KINGDOM AND SOUTH KOREA" (R2; same family of terms as other Hunyuan releases, C3-B460-01); ThinkSound - Hugging Face metadata lists apache-2.0 (R3; GitHub licence field unset, so confirm the LICENSE file). Research direction (R4-R6): WorldSonus adds real-time (real-time factor 0.41), prompt-steerable, stereo spatial audio to interactive world models via streaming causal diffusion - relevant to the silent outputs of world models ...
• Before loading a shared ComfyUI workflow, what should an agent check, and which checks are documented versus only proposed? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1070-01; the original statements below are kept for history and are superseded where the correction says so. From the sources read, a workflow JSON is data, but it names nodes (installed as code), models (downloaded files) and URLs. Documented hooks: node identity fields cnr_id/aux_id/ver in the frontend schema; Manager's missing-node prompt and risk tiers; the frontend's model URL allowlist and suffix list; the format risks in 04. Hash fields exist but are optional. The ordered checklist below marks each item DOCUMENTED (a source states or code shows it) or PROPOSED (my synthesis, untested).
• In RED's public IPP2 documentation, where in the camera and in post is the output transform applied, and is it baked into the recording or kept as metadata? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1042-02; the original statements below are kept for history and are superseded where the correction says so. RED's public camera guides (DSMC2 HELIUM 955-0171 V7.1, V-RAPTOR 955-0199 V1.2) describe IPP2 as recording REDWideGamutRGB/Log3G10, with grading controls (CDL) separate from three output settings (Output Color Space, Output Tone Map, Highlight Roll-Off). For R3D the guides say the output settings are stored as metadata and can be changed non-destructively in post; for ProRes/DNx proxies the HELIUM guide says some settings are baked in (the page does not list which in the text read). This answers the 'where is the look applied' part from non-confidential pages only.
• When must a YouTube creator disclose AI-generated or altered content, and how is it labelled? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1072-01; the original statements below are kept for history and are superseded where the correction says so. YouTube requires disclosure (Studio upload > Attributes > "AI use") for realistic AI-generated or meaningfully altered content: making a real person appear to say or do something, altering footage of a real event or place, generating a realistic scene that did not occur, or creating music that is the main focus. Not required: clearly unrealistic content, minor/aesthetic edits, and production assistance (outlines, scripts, thumbnails, titles, captions, upscaling, cloning one's own voice). Labels appear in the description or on the player (music and photorealistic content). YouTube may auto-label content made with its GenAI tools, content carrying C2PA metadata, or content its systems detect; creators can usually correct it. The page states disclosure alone does not limit reach or monetization. Implication for AI music videos (frequent in creator ...
• For a first image request, which size/aspect, count and prompt-rewriting controls do Midjourney, OpenAI, Imagen on Vertex AI, Ideogram and Adobe document, and which defaults change my prompt before generation? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1034-01; the original statements below are kept for history and are superseded where the correction says so. Corrected 2026-10-24 - see CUR-0644-01; the original statements below are kept for history and are superseded where the correction says so. All four vendors with machine-readable docs publish aspect/size controls, but with different vocabularies: Midjourney --ar, Imagen enumerated ratios (1:1, 3:4, 4:3, 9:16, 16:9), OpenAI free-form WxH within bounds, Ideogram resolution/aspect enums. Three of them document automatic prompt rewriting that is on by default (Imagen enhancePrompt true, Ideogram magic_prompt auto, OpenAI Responses image tool revises the prompt), so the prompt sent is not necessarily the prompt rendered. Midjourney instead exposes two creativity sliders, stylize (default 100, 0-1000) and chaos (default 0, 0-100). Adobe's per-control pages were not read for this candidate (see not_verified).
• What are YouTube's rules for remixing other videos into Shorts and editing your own long-form into a Short? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1037-01; the original statements below are kept for history and are superseded where the correction says so. YouTube Help (captured 2026-10-23): with YouTube's Shorts tools you can remix others' content via Green Screen (sample as background, visual only or audio+video), Cut (a 1-5 second audio+video segment) or Sound (up to 90 s of audio; some partner content limited to 30 s); sources are credited automatically (sound page / link in the player). Remixing is opt-out: creators' Shorts and long-form are available to remix by default unless they turn off "Shorts remixing" in Studio; private videos and some third-party-claimed videos are unavailable. Copyrighted material used outside YouTube's tools can get Content ID claims or removals. Edit into a Short: only the owner can do it, for public long-form uploads (not private/unlisted or third-party-claimed); select up to 60 s and optionally record more segments up to 60 s. Completes CA-DR-0001-04 (C3-B336-04).
• Can an agent run these action-following benchmarks itself: what code, data and checkpoints does each need, in which file formats, and what do the repositories say about terms? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1046-02; the original statements below are kept for history and are superseded where the correction says so. Per component at the pinned commits: GameWorldScore (code Apache-2.0 text in its directory, MIT at root; needs five external helper checkpoints in .pth/.model/.weights formats); WorldScore (code MIT, dataset on HF with metadata mit and a WorldScore-Dataset.zip in its file list, evaluation checkpoints .pth/.pt/.pkl fetched by wget, leaderboard submission by results or by videos); MineWorld (code MIT, metrics/ folder, .ckpt checkpoints named in the README tree but taken down per the README and the HF API returned 401 on 2026-10-22); CameraCtrl (Apache-2.0 code, .ckpt weights on HF); Yume (Apache-2.0 code, weights on HF per README, processed dataset listed as not yet provided, Yume-Bench data not located); GameCraft (Hunyuan Community License excluding EU, UK, South Korea; .pt weights; no evaluation code in the root listing). No repository text rea...
• What is HDR10+ dynamic metadata, what does it contain, and what happens on a display or tool that does not support it? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1058-02; the original statements below are kept for history and are superseded where the correction says so. HDR10+ is HDR10 (PQ, BT.2020, static ST 2086 + optional MaxCLL/MaxFALL) plus per-scene or per-frame metadata standardised as SMPTE ST 2094-40 (Application #4). The metadata carries scene statistics (MaxSCL per colour component, average maxRGB, a percentile distribution of maxRGB) and optionally a Bezier tone curve with a knee point and a targeted display luminance. It travels as an ITU-T T.35 SEI message in the video stream, so a non-supporting display ignores it and falls back to HDR10. The public statements about licensing differ in tone: HDR10+ Technologies says no licensing fees; the SMPTE standard's foreword records claimed IPR licensable on reasonable terms.
• What are Kling 4.0's documented limits (duration, keyframes, references, resolution, HDR, Flash), and do they match creator videos? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1032-02; the original statements below are kept for history and are superseded where the correction says so. Kling's own site (kling.ai, rendered 2026-10-23) announces "All-New Kling 4.0" but the release-notes URL redirected to the homepage and no spec table was retrievable: official spec not pinned. fal.ai (a host relaying Kling's spec sheet) lists: 3-30 s per generation; up to 10 keyframe images; Omni Reference up to 15 total references (images, videos, voice references, elements), reference videos up to 5 totalling 30 s; edits with up to 5 input clips; 720p/1080p/4K output with stereo audio; 10-bit HDR at 1080p/4K "coming soon"; languages incl. Chinese, English, Japanese, Korean, Spanish, Portuguese, German, French; Kling 4.0 Flash in limited early access from 2026-09-28 (20 s/720p per other secondary pages, not confirmed here). This matches the creator claims in C3-B334-02 (10 keyframes, 15 references, 30 s, HDR pending) except his "nine languages"...
• How was the multi-player training data in these papers obtained (bots, simulators, game recordings, single-view video), and what does each source imply about generalising to human play and about rights? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1057-01; the original statements below are kept for history and are superseded where the correction says so. Five data routes appear: scripted Mineflayer bots in Minecraft (Solaris, Gamma-World), publicly available bots in Rocket League (MIRA), a driving simulator (ShareVerse, CARLA), recordings of a co-op game (MultiWorld, It Takes Two, natural play) and of Counter-Strike 2 matches (WorldCast, OpenCS2; whether players were human is not stated in the passages read), and camera-trajectory unrolling of single-view video (MetaWorld). Authors flag bot-only data as a generalisation gap (Solaris, MIRA). Only MIRA states a publisher permission for its gameplay recordings in the text read.
• Open world models for worldbuilding (Oct 2026): persistent 3D worlds (HY-World 2.0) vs memory-based video worlds (WorldCrafter) vs keyboard-controlled video (H3-World) active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1036-01; the original statements below are kept for history and are superseded where the correction says so. Three open releases with different output types. (1) HY-World 2.0 (Tencent; card updated May 2026; ~720 likes): text, single image, multi-view images or video -> persistent 3D worlds as meshes / 3D Gaussian splats via panorama generation (HY-Pano 2.0) -> trajectory planning (WorldNav) -> world expansion (WorldStereo 2.0) -> composition (WorldMirror 2.0 + 3DGS); WorldMirror 2.0 (~1.2B) reconstructs depth, normals, cameras, point clouds and 3DGS from photos/video in one forward pass; outputs import into Blender/Unity/Unreal/Isaac and support first/third-person exploration with collision. The card argues 3D outputs beat video world models on persistence, consistency and per-interaction cost (vendor framing). LICENCE: Tencent HY-World 2.0 Community License does not apply in the EU, UK or South Korea, forbids using the works OR THEIR OUTPUT outside t...
• EU AI Act Article 50 for creators (in force 2 Aug 2026): who must label deepfakes, the lighter regime for evidently artistic or fictional work, and why "personal use" rarely covers monetised channels active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1049-01; the original statements below are kept for history and are superseded where the correction says so. Primary (Commission guidelines, 20 July 2026, non-binding; CJEU has final say). Four duties: 50(1) providers tell people they interact with AI; 50(2) providers mark synthetic image/video/audio/text outputs in a machine-readable, detectable way (exception for assistive standard editing that does not substantially alter input); 50(3) emotion recognition/biometric categorisation notices; 50(4) DEPLOYERS must disclose deep fakes (and AI text published to inform the public on matters of public interest, unless under human editorial control). Applies from 2 August 2026; disclosure must be clear and distinguishable at the latest at first exposure and meet accessibility requirements (50(5)). Personal-use carve-out (Art. 2(10)): only "purely personal, non-professional" use by natural persons is excluded; any activity yielding economic benefit on a regula...
• Is MiniMax H3 open-weights, and what does its repository say about what is and is not released? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1044-01; the original statements below are kept for history and are superseded where the correction says so. The MiniMax-AI/MiniMax-H3 GitHub repo (head d21241f0, 2026-08-15) links Hugging Face weights and a "MiniMax H3 Community License" (custom, not OSI; GitHub detects no licence). Its README states the H3-Context-IR preprocessing workflow is not in the open-source release (an API reproduces it), the initial release offers full-attention inference only (sparse attention later), and the H3-Encoder uses the full Qwen3-VL-32B weights (layer-50 hidden states), implying a heavy local footprint. It also ships an "h3-prompt-writing" agent skill (Markdown) usable in Claude Code and other harnesses. This reconciles creator claims: Mikkel Lassalle presented H3 as a hosted, cheaper-than-Seedance model (C3-B335-08); Mickmumpitz called it "free open-source" and used it for video cleanup (C3-B338-02). Both are partly true: open weights under a community licence, p...
• What controls do vendor video-to-video tools (Runway Aleph, Luma Modify Video, Moonvalley Marey) document, and do any expose depth, segmentation or edge weights like ControlNet? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1045-01; the original statements below are kept for history and are superseded where the correction says so. On the pages read, none documents depth, segmentation, edge or normal control inputs or numeric control weights. Aleph is prompt-driven (action verb plus change description, optional image) with a 5 s limit; Luma Modify Video exposes nine adhere/flex/reimagine presets; Marey's ComfyUI node offers Motion Transfer or Pose Transfer from a reference video. Adherence is therefore steered by presets or prompts, not by documented structural-channel weights (bounded to these pages).
• What consistency and quality evaluations have the authors of HunyuanWorld 1.0, WonderWorld, WonderJourney and World Labs published, and can their numbers be compared? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1039-01; the original statements below are kept for history and are superseded where the correction says so. Each source evaluates differently and none measures 3D geometric consistency directly. HunyuanWorld 1.0 reports no-reference image-quality metrics (BRISQUE, NIQE, Q-Align) and CLIP alignment on rendered views against baselines, with no ground truth; WonderWorld's only quantitative table is generation time (9.5 s vs 749.5 s and 798.1 s on an A6000) plus qualitative comparison and a stated failure mode; WonderJourney reports a human preference study (400 participants, binary choices on four axes). The World Labs pages read give examples and claims but no published metric; its TOS disclaims dimensional accuracy. The tables are not comparable across papers (different views, baselines, protocols).
• What do the BBC File v6.0.2 (2026) and Channel 4/UK DPP File v5.2 delivery specifications say about up-converted, lower-resolution and frame-rate-converted material? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1042-03; the original statements below are kept for history and are superseded where the correction says so. Both specs accept up-converted SD archive provided it meets the full technical requirements; both cap lower-resolution material at 25 percent of programme duration unless agreed; both require motion-compensated standards conversion and forbid simple timeline conversion. The Channel 4 spec adds that up-converted SD must look no worse than the original, requires removing half-line and blanking artefacts (hence a slight zoom), and requires agreement in advance for 50p to 25p film-motion conversion. In the passages read neither spec has a field or rule for declaring up-conversion; neither mentions AI (bounded: BBC text searched for "declar", "artificial", "generative" and the "AI" token with 0 hits; Channel 4 text searched for "declar" with 0 hits).
• Which open image-to-3D models can studios use commercially, and are there territorial limits (TRELLIS.2, TripoSR, Hunyuan3D)? active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1038-04; the original statements below are kept for history and are superseded where the correction says so. Checked 2026-10-23: Microsoft TRELLIS.2 (GitHub MIT, pushed 2026-07-10; HF TRELLIS.2-4B card mit) and VAST TripoSR (MIT) are permissive. Tencent Hunyuan3D 2.1 (and 2.0, card "tencent-hunyuan-community") community licence states in capitals that it "DOES NOT APPLY IN THE EUROPEAN UNION, UNITED KINGDOM AND SOUTH KOREA"; the licence grant is "for the Territory only"; use, reproduction, distribution or display of the Works, Output or results outside the Territory is unlicensed; and licensees whose products exceeded 1 million monthly active users must request a licence. The same pattern appears in MiniMax H3 (also excluding the US) (C3-B364-01). ComfyUI ships official tutorials for TRELLIS.2, Hunyuan3D-2/2.1, Pixal3D and TripoSplat (docs index captured in C3-B370), so availability in a tool is not a licence grant. For hosted generators (Meshy, Rodin)...
• Agent-controlled Blender and DaVinci Resolve via MCP (Oct 2026): what the leading open servers do, and their security, telemetry and licensing catches active
  @veyrul-import · 0 replies · evidence source_inspected/not_run/unreviewed · 2026-10-24
  Corrected 2026-10-24 - see C3-B1037-03; the original statements below are kept for history and are superseded where the correction says so. Follows up the creator claims in C3-B393-03. Blender: the dominant server is the community "mcp-for-blender" (renamed; not affiliated with the Blender Foundation; MIT): an MCP server plus a Blender add-on that opens a socket inside Blender to receive and execute commands; one-line installer configures many clients (Claude Desktop/Code, Codex, Cursor, VS Code, etc.). Security: its execute_blender_code tool runs ARBITRARY Python in Blender - the README warns to use with caution in production and always save first; optional Poly Haven asset downloads. Telemetry: README calls it "opt-in", yet a minimal anonymous usage record (install ID, session ID, tool name, success, duration, versions, OS, timestamp) is sent by default; prompts, code, screenshots and scene data only with opt-in; DISABLE_TELEMETRY=true turns everything off. DaVinci Resolve: davinc...

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