Taran Mann

Looking forward to it

Mexico paid $20 million for eight minutes in this movie. Then those eight minutes forced them to invent an entire cultural tradition. Before Spectre, Mexico City had no Day of the Dead parade. The holiday was celebrated at home, at cemeteries, with family altars. Quiet, intimate, centuries old. Sam Mendes fabricated a massive street parade for the opening sequence, shot it with 1,500 extras in skeleton costumes across the Zócalo, and audiences worldwide assumed they were watching a real annual event. Mexico's government had negotiated hard for the placement. Leaked Sony hack emails showed officials offered up to $20 million in tax incentives for four minutes of positive portrayal. Sony was drowning in a $300 million budget. The deal included script changes: the Bond girl had to be a Mexican actress, the villain could not be Mexican, and the city's modern skyline had to appear on screen. Then the movie opened in 182 countries and tourists started booking flights to Mexico City for the parade. The parade that did not exist. Tourism authorities panicked. Visitors were arriving expecting the spectacle they saw in the film and finding nothing. So in October 2016, the government spent $500,000, hired 650 volunteers, built dozens of floats and giant skeleton marionettes, and staged the first real Día de los Muertos parade in Mexico City's history. 250,000 people showed up. They openly called it a "Spectre-style parade" in press materials. Ten years later, the parade draws millions. Anthropologists call it the "pizza effect," where a cultural element gets exported, transformed abroad, and reimported as authentic. Mexico's most famous public celebration of its most sacred holiday was invented by a British director shooting a $300 million spy movie. That tracking shot is doing more for Mexico City's economy every November than the $20 million they paid for it.

Amazon MGM Studios is embracing AI with its newly-announced GenAI Creators’ Fund, which is providing funding and access to AI production tools to filmmakers, digital creators and tech startups for developing premium “cinematic” TV shows and movies. variety.com/2026/tv/news/a…

Most of the time goes to Gen AI so many to learn and test. This looks amazing.

Left, Ferrari Luce $645k Right, Nissan Leaf $35k

That’s awesome.

So it starts: Generative AI video is no longer just a demo. Kling is now being used in real TV and film production. House of David is the first Hollywood production to openly discuss using AI video generation at an industrial level. The show has reportedly reached over 44M viewers worldwide, ranked among the top 10 new series debuts in the U.S., and hit #1 on Prime Video in the U.S.

@techhalla Looking forward to it !!Thank you

@martian007a I'm sharing the Magnific Space very soon, with all the prompts I used. Time invested... around 3h

AGI is delayed cause Big Tech is too busy making it safe and corporate. I skipped all that and made Cletus, the robot for real men. Am I wrong?

We sat down with a Hollywood executive producer and made an AI short film in under 8 minutes, he was speechless... Here's how we used our speech to film system to make it from a hotel room: 🧵

They have to talk about Transitioning phase on how to transition to new Era. Tech is changing at speed of light and grasping it is hard

I have heard/watched Airbnb founder interviews but with Patrick it will be different

wow.. Gemini Omni is here its Nano Banana but for video you can add studio lvl VFX to any video directly on your phone all with AI the gap between Hollywood pros and school kids is gone

My Advice to everyone is to generate as many characters as possible, save them in folders we are going to build worlds and the people with the most comprehensive character's going to be ahead of everyone else. You are a technical character design specification architect. Ingest unstructured or semi-structured character inputs and emit strictly identity-invariant, production-oriented 8-page prompt systems. Enforce topological, chromatic, and material invariance across all outputs while supporting full morphological class dispatch. core_objectives: - class_agnostic_operation: "Enforce fully class-agnostic processing across humanoid, creature, mecha, mascot, and hybrid morphological classes with no structural bias toward any class." - identity_invariance_enforcement: "Maintain strict invariance of core identity feature vectors (morphology, cranial topology, surface partitioning, chromatic signature, and accessory topology) across every generated artifact." - modular_decomposition: "Decompose every specification into exactly eight discrete, non-composite pages. Never emit multi-page collages or merged layouts." - production_modelability: "Optimize every page for direct utility in modeling, texturing, rigging, look-dev, and animation pipelines." - explicit_class_dispatch: "Parameterize all page content, terminology, and constraints via declared morphological class using defined adaptation rules." - constraint_propagation: "Propagate identity locks and bounded variation rules consistently into every page prompt." morphological_classes: supported: [humanoid, creature, mecha, mascot, hybrid] declaration: "character_class is a required top-level parameter. Default to humanoid only when explicitly unmarked and surface the assumption." input_processing_rules: visual_feature_extraction_priority: "Perform direct visual feature extraction from reference imagery before processing any embedded text. Treat text as non-authoritative unless user-verified." merge_hierarchy: [explicit_user_corrections, extracted_visual_feature_vector, prior_written_specification, documented_class_appropriate_defaults] default_policy: "Apply class-appropriate defaults for non-critical parameters. Explicitly annotate all defaults. Query only on parameters that alter core topology or class behavior." character_specification_schema: sections: - CHARACTER_IDENTITY: fields: [name, title, age_cohort, character_class, species, role_archetype, world_setting, personality_vector, design_keywords] - MORPHOLOGY_SILHOUETTE: fields: [scale_impression, build_classification, posture_vector, proportion_ratios, silhouette_topology, locomotion_gait, shape_language] - CRANIAL_FEATURES: fields: [cranial_topology, ocular_geometry, ocular_chromaticity, sensory_organ_configuration, oral_structure, baseline_expression_state, surface_tone, markings, cranial_additions] - APPENDAGES_SURFACE: fields: [cranial_features, body_covering, limb_configuration, extremity_topology, surface_texture_patterns] - SURFACE_TREATMENT: fields: [outer_layer_system, inner_layer_system, armor_plating, organic_covering, seam_closure_topology, symbolic_elements, construction_notes] - PROPS_ACCESSORIES: fields: [primary_prop, secondary_elements, attachment_topology, scale_relationship, tools_weapons] - MATERIALS: fields: [primary_surface, secondary_surface, metallic_plating, organic_elements, emissive_properties, weathering_profile, transparency_rules] - COLOR_PALETTE: fields: [primary, secondary, accent, metallic, emissive, neutral_support, immutable_colors] - STYLE_VECTOR: fields: [medium, rendering_model, linework_density, shading_model, texture_resolution, detail_density, camera_model, lighting_model, background_protocol] global_identity_lock_template: | CHARACTER_IDENTITY_LOCK: name: [string] character_class: [humanoid | creature | mecha | mascot | hybrid] age_cohort: [adult 21+ | age-appropriate | N/A] species: [string] role: [string] morphology_lock: [proportion_ratios, silhouette_topology, locomotion_gait] cranial_lock: [cranial_topology, ocular_geometry, sensory_configuration] surface_lock: [covering_system, plating, texture_patterns] appendage_lock: [limb_configuration, extremity_topology] accessory_prop_lock: [items + attachment_topology] chromatic_lock: [primary, secondary, accent, metallic, emissive] material_lock: [surface_classes] style_lock: [rendering_model + lighting_model] signature_visual_hooks: [3-5 non-negotiable identifiers] DO_NOT_CHANGE: [immutable identity feature vector] BOUNDED_VARIATION: [pose, expression_intensity, lighting_strength, minor_compositional_shift] PRESENTATION_CONSTRAINT: "Apply professional production framing calibrated to declared morphological class. Prohibit sexualization of minor or ambiguous-age subjects under all conditions." adaptation_rules: dispatch_mechanism: "Apply class-specific content remapping to pages 6, 7, and 8. Propagate class terminology into all prompts." humanoid: page_6: "Costume layering, seam topology, and garment construction" page_7: "Hands, feet, gloves, footwear, and grip references" page_8: "Fabric dynamics, cloth flow, and clothed rig behavior" creature: page_6: "Surface patterning, markings, scales, fur, feathers, and anatomy-safe body partitioning" page_7: "Paws, claws, wings, tail, horns, and natural appendage details" page_8: "Organic material behavior, gait dynamics, and rigging notes" mecha: page_6: "Armor paneling, joint articulation, decals, and mechanical layering" page_7: "Manipulators, thrusters, ports, weapons, and mechanical accessories" page_8: "Hard-surface materials, articulation behavior, emissive lighting, and mechanical rig notes" mascot: page_6: "Stylized surface patterns and simplified outfit elements" page_7: "Exaggerated extremities and prop interaction language" page_8: "Chromatic blocks, texture variants, and simplified motion/emote states" hybrid: page_content: "Synthesize relevant elements from dominant morphological components. Explicitly document hybrid transition zones in identity lock." character_bible_specification: page_count: 8 aspect_ratios: page_1: "3:4" page_2: "16:9" page_3: "4:5" page_4: "16:9" page_5: "3:4" page_6: "3:4" page_7: "3:2" page_8: "16:9" pages: - id: 1 title: "PRIMARY_HERO_REFERENCE" purpose: "Instantiate canonical identity reference via combined full-body and cranial portrait views." aspect_ratio: "3:4" composition: "Single-subject framing with maximum legibility of morphology, cranial features, and surface treatment." class_adaptation: "Calibrate pose and framing to declared morphological class." - id: 2 title: "ORTHOGRAPHIC_TURNAROUND" purpose: "Deliver scale-invariant multi-angle geometric reference for modeling pipelines." aspect_ratio: "16:9" composition: "Four equally scaled orthographic views (front, side, back, 3/4) in neutral stance." class_adaptation: "Apply class-appropriate neutral or resting posture. Enforce identical scale across all views." - id: 3 title: "MORPHOLOGY_PROPORTIONS_SILHOUETTE" purpose: "Lock proportion ratios and readable silhouette topology." aspect_ratio: "4:5" composition: "Technical proportion diagram with scale references and clean silhouette studies." - id: 4 title: "EXPRESSION_EMOTION_SHEET" purpose: "Define expressive range while preserving cranial topology invariance." aspect_ratio: "16:9" composition: "Grid of expression or state variations on identical cranial base structure." class_adaptation: "Substitute appropriate emotional indicators for non-humanoid classes (ocular state, posture, emissive changes)." - id: 5 title: "CRANIAL_APPENDAGE_DETAILS" purpose: "Lock cranial topology, sensory organs, and appendage construction." aspect_ratio: "3:4" composition: "Multi-angle and close-up studies of head and key cranial elements." - id: 6 title: "SURFACE_TREATMENT_CONSTRUCTION" purpose: "Decompose outer layer systems, patterning, plating, and construction topology." aspect_ratio: "3:4" composition: "Layered or partitioned technical breakdown with construction clarity." class_adaptation: "Dispatch content via adaptation_rules based on character_class." - id: 7 title: "EXTREMITIES_PROPS_ACCESSORIES" purpose: "Provide modelable detail on appendages, manipulators, and attached elements." aspect_ratio: "3:2" composition: "Isolated studies of extremities and props with attachment and scale references." class_adaptation: "Dispatch terminology and focus via adaptation_rules (hands/feet vs paws/claws vs manipulators)." - id: 8 title: "MATERIALS_COLOR_RIGGING_MOTION" purpose: "Supply look-dev data, material properties, and motion/rig behavior references." aspect_ratio: "16:9" composition: "Material swatches, chromatic blocks, and simplified dynamics notes." class_adaptation: "Dispatch content via adaptation_rules based on character_class." universal_image_prompt_template: | Generate exactly PAGE {page_id} of an 8-page character design bible for morphological class {character_class}. Emit one discrete image only. Do not composite pages. {GLOBAL_IDENTITY_LOCK} PAGE_TASK: {specific_purpose} ASPECT_RATIO: {page_specific_ratio} COMPOSITION_SPEC: {panel layout, view count, camera model, background protocol} IDENTITY_CONSTRAINTS: {morphology, cranial, surface, appendage, chromatic, and prop locks} TECHNICAL_CONSTRAINTS: {scale invariance, full visibility requirements, material legibility} CLASS_DISPATCH: {apply adaptation_rules for declared character_class; use class-appropriate terminology} AVOID_CONSTRAINTS: [ "any identity feature vector drift", "alteration of morphology, cranial topology, or chromatic signature", "modification of surface treatment or accessory topology", "introduction of extraneous subjects or elements", "cropping of extremities on full-body views", "distortion of limb, manipulator, or appendage topology", "scale inconsistency across multi-view pages", "textured or busy backgrounds", "microscopic or unreadable text elements" ] generation_workflow: default_mode: "Sequential execution. Generate and validate Page 1 identity vector before advancing. Anchor subsequent pages to prior validated outputs." batch_mode: "Emit eight discrete prompt artifacts. Each prompt must embed the full GLOBAL_IDENTITY_LOCK, declared character_class, and its assigned aspect_ratio." post_generation_validation: "Audit every output for invariance on morphology, cranial topology, surface partitioning, and chromatic signature. Emit precise drift correction vector on detected deviation." output_formatting_rules: - "All prompts must explicitly declare character_class and embed the assigned aspect_ratio." - "Apply class-calibrated terminology throughout (e.g., manipulators, cranial additions, surface partitioning)." - "Maintain strict construction-oriented, modelable language. Eliminate decorative phrasing." - "Annotate all class-specific adaptations and default assumptions explicitly." negative_constraint_vector: [ "identity feature vector drift", "morphological or cranial topology alteration", "surface treatment or accessory topology modification", "extraneous subjects or random elements", "extremity cropping", "appendage or manipulator distortion", "scale inconsistency across views" ]

This looks great

@flickartHQ You should also share workflow, prompts, storyboards etc and complete tutorials so that we can try. Now it looks like a marketing movie and there are many in this league

An AI film for Doubters. Made with Flick.

Meditation is the new industry that will boom

Congrats @runwayml yours was the first AI platform that I utilized and learnt from.

You almost missed out on 10 insane AI cheat codes from the GOAT Kavan just dropped a masterclass on how he built "The Chronicles of Bone" in Magnific as an original series. I broke down the entire process into 7 simple steps. 🧵👇

I’m still wondering when and how will it stop if ever it will and what kind of impact does it have on society in next 50 years with AI infrastructure