Kling 2.6 Voice Control directs 3×3 drama grids – 3‑step boards-to-performance

Kling 2.6 Voice Control (Kling): Kling 2.6 Voice Control anchors a full three‑step "board‑to‑performance" workflow shared by creator Heydin_ai, turning Midjourney character stills into a 3×3 sci‑fi interrogation grid with synced dialogue; this follows up on character scenes which first highlighted Native Audio for talking heads. The thread breaks down how to design characters in Midjourney, expand them into disciplined shot grids with Nano Banana Pro, refine frames in Photoshop, then direct final performances in Kling 2.6 using selectable or custom voices that still obey the text prompt logic. (dialogue workflow post, voice control UI)

• Shot design and prompt craft: Heydin_ai publishes the exact "TEXT PROMPT (FINAL – 3×3 GRID / CINEMATIC INTERROGATION)" that specifies anamorphic lensing, slit‑style hard light, blocking for interrogator vs subject, and how each of the 9 frames should escalate from wide to extreme close‑up to keep tension purely in composition and performance rather than action, as detailed in the long prompt share. interrogation prompt • Grid generation and storyboarding: Starting from two Midjourney character portraits, Nano Banana Pro’s 3×3 split‑stack output generates a full coverage grid (wides, mediums, eye close‑ups) inside a consistent alien interrogation room, which is then cut and polished frame by frame in Photoshop with the integrated Nano Banana Pro extension. (step one graphic, photoshop refine explainer) • Voice‑directed final renders: In Kling 2.6’s Image‑to‑Video UI, Heydin_ai pastes per‑shot dialogue and selects a specific voice for each character via the @Select Voice panel, with Kling handling narration timing while keeping tone and cadence aligned to the emotional directions in the prompt ("suppressed anger, icy composure"). voice control UI • Platform endorsement: Kling’s official account replies to thank the creator for "affection for our 2.6 model" and wishes them a strong 2026, signaling that this prompt‑to‑performance use case is something the team is watching and implicitly supporting. kling reply The pipeline turns what used to be a storyboard plus temp VO pass into a single AI‑driven loop where framing, lighting, and acting can all be iterated from text and a handful of stills.

Fan remake test (Heydin_ai + Kling): Creator Heydin_ai stages an alternate Gandalf–Frodo confrontation as a purely fan‑made clip to probe how far Kling 2.6 with Voice Control can go in matching live‑action pacing and emotional beats. lotr remake video He builds the scene from still images, then generates the moving shots and spoken dialogue with Kling 2.6, aiming to mirror the timing and music feel of the original Lord of the Rings moment without relying on stock footage or manual animation. lotr remake video

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The post stresses that the goal is evaluation rather than release—Heydin_ai calls out being "amazed" by how close the AI performance feels while still treating it as an experiment in what Kling’s Native Audio plus Voice Control can currently handle for long‑form, IP‑style drama work. lotr remake video

Sport Advertising prompt (Azed_ai): Azed_ai shares a detailed, reusable prompt template for motion-blur sports ads, specifying a blurred silhouette of a chosen subject in a colored kit, shot with slow shutter speed, minimalist neutral backgrounds, and high-contrast 3:2 editorial framing reminiscent of Adidas campaigns Prompt template.

The examples span at least 4 sports—basketball, sprinting, cycling, and skating—each generated with the same core instructions but variable subject and color, illustrating how a single prompt pattern can hold brand-consistent aesthetics while swapping athletes and disciplines Prompt template. A follow-up retweet invites creators to "QT your red", turning the template into a weekly community exercise around red-themed sports visuals rather than a one-off trick Prompt challenge.

Midjourney sref 6925528290 (Azed_ai): Azed_ai releases a new Midjourney style reference (--sref 6925528290) built around saturated yellow backgrounds, deep blue characters, and chunky gouache-like brushwork, showcased across at least 4 example images ranging from a tiny armored knight to a fuzzy dragon and a caped hero in a stylized forest Style reference post.

The same style is boosted again via a "QT your red" community prompt, which encourages artists to respond with their own red-themed takes while reusing this sref for consistent texture, color blocking, and childlike illustration energy Follow up share. For AI illustrators, this gives a ready-made look for children’s books, playful posters, or character sheets that want a flat-color, mid-century storybook feel without re‑prompting style from scratch.

Gothic sref 1107251537 (Artedeingenio): A new Midjourney style reference, --sref 1107251537, focuses on illustrated gothic dark fantasy, with Artedeingenio positioning it specifically for vampire kings, necromancers, undead lords, and dark-fantasy novel covers or villain concept art Gothic pack post.

The shared samples include a skull-bearing hooded skeleton, an old man with glowing orange eyes in harsh directional light, and two different blue‑skinned, fanged royalty portraits with ornate crowns and heavy cloaks, all rendered with high-contrast chiaroscuro and gritty line work Gothic pack post. The pack is framed as useful not only for covers but also for cards, posters, and narrative key art that need a consistent, moody treatment across multiple antagonists.

Poetic anime sref 2874412668 (Artedeingenio): Artedeingenio introduces Midjourney --sref 2874412668 as a poetic fantasy anime style with a quiet, melancholic tone, citing Mushishi, Natsume Yuujinchou, and Violet Evergarden as touchstones for its intimate, introspective feeling Poetic anime sref.

Following up on the earlier OVA anime style that captured a retro dark OVA mood, this new sref leans toward softer, character-centric vignettes—a winged girl surrounded by glowing butterflies, a traveling witch outside a cottage, a one-eyed pirate against a twilight sea, and a black-haired woman in lace with a blue pendant—favoring restrained expressions over action poses Poetic anime sref. The description stresses that fantasy here is treated as something small-scale and personal rather than epic, giving storytellers a reusable look for reflective sequences, quiet magic, and low-key character drama.

Cartoon sref 2712431404 (Artedeingenio): Artedeingenio publishes Midjourney style reference --sref 2712431404, describing it as a modern cartoon animation look with strong mid‑century roots, pulling from UPA minimalism plus the cinematic sensibility of Genndy Tartakovsky and Bruce Timm Cartoon style sref.

Sample outputs include a squat, stylized Batman on moody city streets, a close-up of a grinning villain with woodcut-like texture, and a pared-down Wonder Woman figure, all showing limited palettes, graphic shadows, and big shape language instead of fine detail Cartoon style sref. Artedeingenio notes that this makes the sref suitable for character-forward illustrations, moody key art, and animation-friendly designs that need clear silhouettes and strong posing rather than painterly rendering.

Nano Banana Pro Diagram Suite (Nano Banana): Ror_Fly details a Weavy-based workflow where a single input image is exploded into 16 different “forensic” diagram overlays—covering geometry, spacing, composition, light, color, narrative, optics, surface materials, psychology, flow, and even a tokenizer view—as described in the diagram overview. This builds on earlier thumbnail work, following up on Weavy thumbnails which focused on layout and contact-sheet style iteration rather than analytic overlays.

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• Visual analysis prompts: The suite ships with rich system prompts like a "Visual Psychologist and Eye-Tracking Analyst" role that outputs a saliency heatmap with hot/warm/cold regions, explicit contrast mapping, and a legend baked into the image, according to the diagram overview.
• Reusing diagrams as comps: A second example shows taking the generated composition/convergence guide and feeding it back in as a reference to frame a Land Rover hairpin-turn shot in Brazilian favelas while instructing the model not to add guide elements, so the diagram becomes a reusable camera blueprint rather than a final look, as shown in the composition use.

For creators, this turns NB Pro from a pure image generator into a visual-analysis and shot-design tool that teaches why an image reads well, not only how to restyle it.

Camera Prompt Helper (Gemini Canvas): Ozan Sihay shares a small Gemini Canvas app that lets users upload an image, pick a camera angle, shot scale, and lens, or type a custom camera description, then auto-generates a detailed prompt describing that setup so the same image can be re-created or evolved in Gemini with matching cinematography, as explained in the canvas description. The app lives in Gemini Canvas and is shared publicly through a Gemini link, so it runs entirely in the browser without extra tooling, according to the canvas app.

The example action stills—rifle-wielding character and tight close-ups around a helicopter—show how the tool encourages thinking in formal terms like lens choice and shot size rather than vague "make it more cinematic" language, which can raise the floor for non‑DP creatives who want consistent camera grammar in their AI images.

Photo revive prompt (Hedra Labs): Hedra Labs demonstrates a single text prompt that upgrades an old, flat photo into something resembling a professionally shot image while preserving framing, pose, and proportions, as described in the photo upgrade prompt. The prompt asks the model to "imagine how this photo would look" if taken with a Canon R7 and Sigma 24mm f/1.4 plus pro lighting and then explicitly instructs: "Do not change the framing, do not change the proportions, and do not change the pose."

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The before–after video shows the original image transforming into a sharper, better lit version in what Hedra describes as under 30 seconds, so for archives, family albums, or older brand assets this offers a lightweight, prompt-only way to modernize the look without re‑shooting or manual retouching.

AI Studio (Google): Ai_for_success calls Google AI Studio "one of the most underrated AI tools" and emphasizes that it is free, describing it as "the fastest path from prompt to production with Gemini" in the shared UI screenshot, as shown in the ai studio praise. The captured home screen presents AI Studio as a central place to go from interactive prompting to deployable endpoints under the tagline "from prompt to production with Gemini"

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For creatives focused on prompts, thumbnails, and storyboards, this positions AI Studio less as a research toy and more as a no-cost control room where they can standardize prompts, iterate on outputs, and wire finished flows into apps without having to stand up their own infra.

Thumbnail stack workflow (Techhalla): Techhalla presents what they call "the best AI thumbnail workflow" using a mock "I invaded Venezuela, captured Maduro" storyline as a case study, assembling multiple high-impact thumbnails that mix photo composites, faux news graphics, and game-style UI, as seen in the thumbnail workflow. The four shared designs span a talking-head explainer, a selfie in front of a government building, a split "operation vs capture" comparison, and a game raid overlay with live-viewer count, all styled for YouTube discovery

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Although the thread context is not fully captured here, the images themselves showcase how an AI-heavy pipeline can cover photography, illustration, typography, and UI mockups in one pass, giving creators a library of on-brand options around a single video concept instead of a single manually-designed thumbnail.

Hearthstone card workflow (LTX Studio + Nano Banana Pro): Techhalla reveals a Nano Banana Pro prompt running inside LTX Studio that generates full Hearthstone-style legendary cards from reference images, using it to produce a set of 15 fan-made legendaries themed around pop culture figures and creators, as shown in the card concept set. The follow-up explains that users can select the Nano Banana Pro model in LTX, upload either a clean celebrity photo or a reference containing the subject’s name, and apply the shared prompt from the screenshot to automatically frame them into Blizzard-like card art and layout, according to the ltx access guide.

For illustrators and game designers, this demonstrates how prompt tooling plus a video/story platform like LTX can double as a rapid concept-card factory, producing on-model card frames without custom Photoshop templates or manual compositing.

Pinup template (Nano Banana Pro): Ai_for_success publishes a JSON-style prompt configuration for Nano Banana Pro that standardizes "Pinup Girl Style" renders into a repeatable aesthetic, including an explicit style_config block for "1950s Pinup, Retro American" plus film references like Kodachrome 64 and Technicolor, studio lighting descriptors, and technical specs such as sharp focus and 3:4 aspect ratio, as outlined in the pinup prompt config. The prompt_template itself keeps variables like [SUBJECT], [OUTFIT], [ACTION OR POSE], and [LOCATION] while reusing the same aesthetic, film stock, and lighting details so the style stays locked even as content changes

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This turns a one-off prompt into a small, configurable style system, making it easier for brands or solo creators to keep a consistent pinup look across series, characters, or campaign variants.

Tripo v3 3D pipeline (TripoAI): Creator techhalla details a full concept-to-rigged-3D workflow where Tripo v3 converts a single Nano Banana Pro character render into a high-fidelity, textured model in minutes, including autorigging and animation selection, as shown in the Tripo workflow and expanded in the Tripo follow-up.

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• Multi-view mesh generation: The process starts with a posed NB Pro image; users upload it to Tripo, ask for multiple views so the model sees the character from several angles, fine-tune the views, then generate an HD textured 3D asset without manual sculpting, according to the step-by-step Tripo workflow.
• Autorigging and animation: A built-in autorigging tool adds a skeleton in under a minute and hooks into a large preset animation library so the same character can immediately run, idle, or perform other actions, as described in the follow-on Tripo follow-up.
• Export and pipeline fit: Finished assets export as FBX with high-quality textures ready for engines or DCC tools, and the thread explicitly targets filmmakers and gamedevs while also bundling discount codes and screenshots in the linked Tripo guide.

Grok Imagine anime shorts (xAI): Artedeingenio runs Grok Imagine text‑to‑video on a detailed prompt to create a quiet anime scene where a girl in a misty forest closes her eyes as glowing "constellation" lines appear under her skin and her form dissolves into a luminous spirit; the request stresses painterly style, subtle motion, and no explosions, highlighting that Grok’s video stack can carry melancholic, atmospheric storytelling rather than only jokes or memes, as shown in anime t2v prompt.

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Usage and vibe: The clip positions Grok as a tool for short, emotionally focused anime moments—slow push‑in camera, controlled pacing, and a single transformation beat—while pzf_ai’s reminder that they cut a full music video last year when the Spicy Ani model launched on Grok shows similar anime pipelines already being used for longer musical pieces spicy ani short. For AI filmmakers and musicians this pairs scripted emotional arcs with promptable visual style, turning Grok into a viable option for lyric videos, interludes, and standalone poetic shots where fine‑grained control over intensity and mood matters more than complex action choreography.

Auto storyboard splits (Rainisto): Rainisto showcases a workflow where a written scene description generates a full image sequence laid out as split‑stack boards, turning a text beat about a woman in a concrete stairwell into 4‑ and 6‑frame contact sheets with progressive close‑ups and prop details, which he frames as the kind of feature that could eventually live inside the app that replaces Final Draft storyboard demo.

Why it matters for boards: The UI screenshots show automated framing decisions—wide establishing stairs shot, medium framing on the character, then tight inserts on cigarettes and a folded note—suggesting the system is not just illustrating but also pre‑blocking coverage across a scene storyboard demo. For directors, storyboard artists, and previs teams, this points to near‑term tools where a paragraph of script can yield an editable contact sheet of candidate shots, ready to be pruned or refined instead of sketched from a blank page.

Scaled VLA pre-training (DeepMind-adjacent): Scaling visual–language–action pre-training across π0/π0.5/π0.6 with egocentric human videos—where hand poses stand in for actions—doubles performance on tasks seen only in human footage, with up to a 0.4 absolute success-rate gain on manipulation tasks like color-based egg sorting, bussing, spice organizing, and dresser tidying according to the robotics thread.

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t-SNE visualizations in the same work show human and robot image representations overlapping more as pre-training scale and robot data diversity increase, supporting the claim that large egocentric human video datasets can transfer into practical robot skills for VLAs robotics thread.

Continual learning (DeepMind research mood): A fresh post restates that “2024 was the year of agents, 2025 was the year of RL, 2026 will be the year of continual learning,” with the comment drawing 119.5K views and reinforcing expectations that this will be the dominant research theme at scale-era labs continual learning quote.

This follows earlier hints that DeepMind will center 2026 programmes on continual learning for long-lived systems and robotics—see research focus for that initial framing—with today’s post positioning continual learning as the successor phase after the current agent and RL waves continual learning quote.

Promise AI studio (Promise): Creator–director Diesol reports that his AI-native film and TV studio Promise AI is featured in Deadline’s "Top 10 AI Stories of 2025" list, in a section on the “Start-Up Gold Rush” alongside Luma and Runway, signaling that Hollywood trade press now treats AI-first studios as a real industry segment rather than curiosities Promise mention, as outlined in the Deadline story.

For AI filmmakers and storytellers, this is a visibility milestone rather than a product launch: it shows a mainstream, legacy outlet putting a generative studio’s work—like the fully AI-driven "Mind Tunnels: Extraction" project Diesol has been teasing—on the same page as OpenAI’s Sora and union negotiations, which frames AI-generated shows as part of the core entertainment business agenda rather than an experimental side channel Promise mention.

HY-MT1.5-1.8B (Tencent): Tencent’s compact HY-MT1.5-1.8B machine-translation model is now the #1 "Trending this week" model on Hugging Face’s models leaderboard, ahead of larger systems like GLM-4.7 and K-EXAONE-236B, according to Tencent Hunyuan’s celebratory post Tencent update.

For AI creatives, designers, and video teams, this trending spike points to strong interest in lightweight MT models that can run cheaply in production or at the edge, which matters for workflows like auto-subtitling, multilingual dubbing, and localizing creative tools—areas where a 1.8B-parameter model can be easier to integrate and scale than frontier-sized LLMs Tencent update.

Text-to-speech voiceovers (Pictory AI): A new case study shows AppDirect using Pictory’s script-to-video and TTS voiceovers to turn slide decks into narrated training videos, reporting a 500% increase in learner engagement and 300% higher productivity for video creation compared with their previous process, according to the pictory summary and the detailed case study. Building on Pictory’s earlier practical guide to generating AI voiceovers, as noted in voiceovers guide, this update anchors the feature in concrete outcomes for long-form training content rather than short marketing clips.

For AI-first learning teams, the example underlines that decent-quality narration without a DAW can materially change completion rates and production throughput when rolling out frequent curriculum updates.

Background music matcher (zeng_wt tool): A creator highlights an AI-powered tool that analyzes an AI video’s vibe, pacing, and hit points to automatically select background music that fits the timing and mood, targeting people who “are not musicians at all” but produce many AI clips, as described in the music picker. This reduces the manual trial-and-error of hunting through tracks or cutting to the beat in a DAW, and instead turns soundtrack selection into a one-click step at the end of an AI video workflow.

Sora guardrails (OpenAI): A creator trying to storyboard short films in Sora’s Drafts UI runs into repeated warnings that prompts "may violate our guardrails around acceptable depictions of teens and children," and several drafts are blocked before any clips render, according to the shared interface capture in Sora drafts screenshot.

• Safety vs. storytelling: The blocked prompts reference adult characters and normal drama setups but are still flagged when they mention ages or youth‑adjacent scenarios, which shows how conservatively Sora’s current policy interprets potential teen/child content for video generation, as seen in Sora drafts screenshot.
• Impact on filmmakers: For AI filmmakers and writers trying to build narrative shorts with realistic age cues, this behavior means many coming‑of‑age or family scenes will need heavy prompt workarounds—or won’t be possible at all—under the current guardrail tuning.

The episode gives an early glimpse of how tightly OpenAI is choosing to draw the line on youth depictions in generative video, even for non‑sexual, story‑driven use cases.

Grok image editing (xAI): A user replies "Hey @grok remove the comrade that never existed" to a historic photo of four Soviet officials on a riverside walk, explicitly echoing Stalin‑era photo purges and underlining how trivial AI tools could make similar erasures today Comrade removal quip.

Cultural concern: A follow‑up comment laments that "we spent multiple episodes at her place for it not to matter at all," using TV‑show language to emphasize how easily narrative continuity can be rewritten when images can be edited this way Follow up comment.

Together these posts frame Grok‑style editors not as a novelty, but as a live test of how platforms will—or won’t—constrain historically sensitive manipulations.

2026 AI adoption fears (AI_for_success): AI_for_success sharpens a tough‑love stance on late adopters, following up on anxiety thread about 2025 being the last year humans beat AI by warning that “If you still think AI is a bubble, 2026 is going to be extremely painful for you” in the Bubble warning. The framing targets skeptics more than existing users, presenting refusal to use AI as a looming professional and financial risk for creators.

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That message aligns with a separate prediction that “AI will eat OF by the end of 2026,” delivered over a video titled “Will AI replace OnlyFans creators by 2026?” that theatrically flashes a giant “NO” before diving into nuances in the Creator economy take. Together these posts reinforce a climate of urgency and FOMO for artists, filmmakers, musicians, and online performers who are still ambivalent about integrating AI into their work.

Creator feed fatigue (Alillian): Artist Alillian posts a long reflection on how even "moderately interesting" work often gets 0–1 likes despite years on X and Facebook, questioning whether algorithms now mainly reward incendiary or highly commercial content rather than thoughtful art and process posts, as detailed in the Engagement reflection. She describes brilliant painter and photographer friends whose time‑lapses and images also see “pitiful” engagement, and wonders whether content creators exist primarily to keep people scrolling past ads.

The post explicitly links this to platform design—calling out feeds, For You pages, and TikTok Shops as systems “built to sell”—while pairing the essay with a moody, ring‑of‑embers generative image captioned “Here’s to the abyss,” which underlines the mix of resignation and stubborn persistence for AI‑using creatives who keep shipping work into an often indifferent algorithmic void.

AI art share threads (Azed_ai): Azed_ai is running open calls for creators to post their favorite AI images each week, promising to personally "check out and engage" with submissions according to the Weekly share call; the kickoff clip shows a fast montage of vivid, stylized pieces that set the bar for what people might post.

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Threads like the color‑focused “QT your red” prompt, backed by striking red‑toned portraits, turn style experiments into communal mini‑events rather than isolated posts, as illustrated in the Red theme prompt and

. The tone mixes encouragement and grind—follow‑ups about twelve‑hour laptop days and “growth happens when you choose discipline over comfort” frame these threads as a place where AI illustrators, designers, and filmmakers can still find peer feedback even as broad feed engagement feels harder to get.