Text-to-video model

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Short description: Machine learning model

File:OpenAI - This is Sora 2.webm A text-to-video model is a form of generative artificial intelligence that uses a natural language description as input to produce a video relevant to the input text.[1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models.[2]

Models

There are different models, including open source models. Chinese-language input[3] CogVideo is the earliest text-to-video model "of 9.4 billion parameters" to be developed, with its demo version of open source codes first presented on GitHub in 2022.[4] That year, Meta Platforms released a partial text-to-video model called "Make-A-Video",[5][6][7] and Google's Brain (later Google DeepMind) introduced Imagen Video, a text-to-video model with 3D U-Net.[8][6][9][10][11]

In February 2023, Runway released Gen-1 and Gen-2, among the first commercially available text-to-video and video-to-video models accessible to the public through a web interface. Gen-1, initially released as a video-to-video model, allowed users to transform existing video footage using text or image prompts.[12] Gen-2, introduced in March 2023 and made publicly available in June 2023, added text-to-video capabilities, enabling users to generate videos from text prompts alone.[13]

In March 2023, a research paper titled "VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation" was published, presenting a novel approach to video generation.[14] The VideoFusion model decomposes the diffusion process into two components: base noise and residual noise, which are shared across frames to ensure temporal coherence. By utilizing a pre-trained image diffusion model as a base generator, the model efficiently generated high-quality and coherent videos. Fine-tuning the pre-trained model on video data addressed the domain gap between image and video data, enhancing the model's ability to produce realistic and consistent video sequences.[15] In the same month, Adobe introduced Firefly AI as part of its features.[16]

In January 2024, Google announced development of a text-to-video model named Lumiere which is anticipated to integrate advanced video editing capabilities.[17] Matthias Niessner and Lourdes Agapito at AI company Synthesia work on developing 3D neural rendering techniques that can synthesise realistic video by using 2D and 3D neural representations of shape, appearances, and motion for controllable video synthesis of avatars.[18] In June 2024, Luma Labs launched its Dream Machine video tool.[19][20] That same month,[21] Kuaishou extended its Kling AI text-to-video model to international users. In July 2024, TikTok owner ByteDance released Jimeng AI in China, through its subsidiary, Faceu Technology.[22] By September 2024, the Chinese AI company MiniMax debuted its video-01 model, joining other established AI model companies like Zhipu AI, Baichuan, and Moonshot AI, which contribute to China's involvement in AI technology.[23] In December 2024 Lightricks launched LTX Video as an open source model.[24]

Alternative approaches to text-to-video models include[25] Google's Phenaki, Hour One, Colossyan,[3] Runway's Gen-3 Alpha,[26][27] and OpenAI's Sora,[28][29] Several additional text-to-video models, such as Plug-and-Play, Text2LIVE, and TuneAVideo, have emerged.[30] FLUX.1 developer Black Forest Labs has announced its text-to-video model SOTA.[31] Google was preparing to launch a video generation tool named Veo for YouTube Shorts in 2025.[32] In May 2025, Google launched the Veo 3 iteration of the model. It was noted for its impressive audio generation capabilities, which were a previous limitation for text-to-video models.[33] In July 2025 Lightricks released an update to LTX Video capable of generating clips reaching 60 seconds,[34][35] and in October 2025 it released LTX-2, with audio capabilities built in.[36]

Architecture and training

There are several architectures that have been used to create text-to-video models. Similar to text-to-image models, these models can be trained using Recurrent Neural Networks (RNNs) such as long short-term memory (LSTM) networks, which has been used for Pixel Transformation Models and Stochastic Video Generation Models, which aid in consistency and realism respectively.[37] An alternative for these include transformer models. Generative adversarial networks (GANs), Variational autoencoders (VAEs), — which can aid in the prediction of human motion[38] — and diffusion models have also been used to develop the image generation aspects of the model.[39]

Text-video datasets used to train models include, but are not limited to, WebVid-10M, HDVILA-100M, CCV, ActivityNet, and Panda-70M.[40][41] These datasets contain millions of original videos of interest, generated videos, captioned-videos, and textual information that help train models for accuracy. Text-video datasets used to train models include, but are not limited to PromptSource, DiffusionDB, and VidProM.[40][41] These datasets provide the range of text inputs needed to teach models how to interpret a variety of textual prompts.

The video generation process involves synchronizing the text inputs with video frames, ensuring alignment and consistency throughout the sequence. This predictive process is subject to decline in quality as the length of the video increases due to resource limitations.[41] The Will Smith Eating Spaghetti test is a benchmark for models.[42]

Limitations

Despite the rapid evolution of text-to-video models in their performance, a primary limitation is that they are very computationally heavy which limits its capacity to provide high quality and lengthy outputs.[43][44] Additionally, these models require a large amount of specific training data to be able to generate high quality and coherent outputs, which brings about the issue of accessibility.[44][43]

Moreover, models may misinterpret textual prompts, resulting in video outputs that deviate from the intended meaning. This can occur due to limitations in capturing semantic context embedded in text, which affects the model's ability to align generated video with the user's intended message.[44][41] Various models, including Make-A-Video, Imagen Video, Phenaki, CogVideo, GODIVA, and NUWA, are currently being tested and refined to enhance their alignment capabilities and overall performance in text-to-video generation.[44]

Another issue with the outputs is that text or fine details in AI-generated videos often appear garbled, a problem that stable diffusion models also struggle with. Examples include distorted hands and unreadable text.

Ethics

The deployment of text-to-video models raises ethical considerations related to content generation. These models have the potential to create inappropriate or unauthorized content, including explicit material, graphic violence, misinformation, and likenesses of real individuals without consent.[40] Ensuring that AI-generated content complies with established standards for safe and ethical usage is essential, as content generated by these models may not always be easily identified as harmful or misleading. The ability of AI to recognize and filter out NSFW or copyrighted content remains an ongoing challenge, with implications for both creators and audiences.[40]

Impacts and applications

Text-to-video models offer a broad range of applications that may benefit various fields, from educational and promotional to creative industries. These models can streamline content creation for training videos, movie previews, gaming assets, and visualizations, making it easier to generate content.[45]

During the Russo-Ukrainian war, fake videos made with Artificial Intelligence were created as part of a propaganda war against Ukraine and shared in social media. These included depictions of children in the Ukrainian Armed Forces, fake ads targeting children encouraging them to denounce critics of the Ukrainian government, or fictitious statements by Ukrainian President Volodymyr Zelenskyy about the country's surrender, among others.[46][47][48][49][50][51]

Movies

Kaur vs Kore is the first Indian feature film made using generative AI which features dual role for the AI character of Sunny Leone, set to release in 2026.[52][53][54]

Chiranjeevi Hanuman – The Eternal is an Indian movie made entirely using Generative AI created by Vijay Subramaniam which is set for theatrical release in 2026. The movie was widely criticised by the Film makers in the Bollywood industry for entirely relying on AI and use of AI was seen as an existential threat to their career.[55][56][57]

Series

Mahabharat: Ek Dharmayudh is an Indian mythological OTT series released on October 2025 and streamed on JioHotstar. It is recognized as the first series created entirely using artificial intelligence to generate visuals and character animations and consists of 100 episodes.[58][59][60]

Comparison of models

Model/Product Company Year released Status Key features Capabilities Pricing Video length Supported languages
Synthesia Synthesia 2019 Released AI avatars, multilingual support for 60+ languages, customization options[61] Specialized in realistic AI avatars for corporate training and marketing[61] Subscription-based, starting around $30/month Varies based on subscription 60+
Vexub Vexub 2023 Released Text-to-video from prompt, focus on TikTok and YouTube storytelling formats for social media[62] Generates AI videos (1–15 mins) from text prompts; includes editing and voice features[62] Subscription-based, with various plans Up to ~15 minutes 70+
InVideo AI InVideo 2021 Released AI-powered video creation, large stock library, AI talking avatars[61] Tailored for social media content with platform-specific templates[61] Free plan available, Paid plans starting at $16/month Varies depending on content type Multiple (not specified)
Fliki Fliki AI 2022 Released Text-to-video with AI avatars and voices, extensive language and voice support[61] Supports 65+ AI avatars and 2,000+ voices in 70 languages[61] Free plan available, Paid plans starting at $30/month Varies based on subscription 70+
Runway Gen-2 Runway AI 2023 Released Multimodal video generation from text, images, or videos[63] High-quality visuals, various modes like stylization and storyboard[63] Free trial, Paid plans (details not specified) Up to 16 seconds Multiple (not specified)
Pika Labs Pika Labs 2024 Beta Dynamic video generation, camera and motion customization[64] User-friendly, focused on natural dynamic generation[64] Currently free during beta Flexible, supports longer videos with frame continuation Multiple (not specified)
Runway Gen-3 Alpha Runway AI 2024 Alpha Enhanced visual fidelity, photorealistic humans, fine-grained temporal control[65] Ultra-realistic video generation with precise key-framing and industry-level customization[65] Free trial available, custom pricing for enterprises Up to 10 seconds per clip, extendable Multiple (not specified)
Google Veo Google 2024 Released Google Gemini prompting, voice acting, sound effects, background music. Cinema style realistic videos.[66] Can generate very realistic and detailed character models/scenes/clips, with accommodating and matching voice acting, ambient sounds, and background music. Ability to extend clips with continuity.[67] Varies ($250 Google Pro/Ultra AI subscription, and additional AI credit Top-Ups) Eight seconds for individual clips (however clips can be continued/extended as separate clips) 50+
OpenAI Sora OpenAI 2024 Alpha Deep language understanding, high-quality cinematic visuals, multi-shot videos[68] Capable of creating detailed, dynamic, and emotionally expressive videos; still under development with safety measures[68] Pricing not yet disclosed Expected to generate longer videos; duration specifics TBD Multiple (not specified)
Runway Gen-4 Runway 2025 Released Consistent characters across scenes,[69] world consistency,[70] camera control, physics simulation Generates 5-10 second clips with consistent characters, objects, and environments across multiple shots[71] Credit-based subscription, part of paid plans 5-10 seconds Multiple (not specified)

See also

References

  1. ↑ Artificial Intelligence Index Report 2023 (Report). Stanford Institute for Human-Centered Artificial Intelligence. p. 98. https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_AI-Index-Report_2023.pdf. "Multiple high quality text-to-video models, AI systems that can generate video clips from prompted text, were released in 2022." 
  2. ↑ Melnik, Andrew; Ljubljanac, Michal; Lu, Cong; Yan, Qi; Ren, Weiming; Ritter, Helge (2024-05-06). "Video Diffusion Models: A Survey". arXiv:2405.03150 [cs.CV].
  3. ↑ 3.0 3.1 Wodecki, Ben (2023-08-11). "Text-to-Video Generative AI Models: The Definitive List". Informa. https://aibusiness.com/nlp/ai-video-generation-the-supreme-list. 
  4. ↑ CogVideo, THUDM, 2022-10-12, https://github.com/THUDM/CogVideo, retrieved 2022-10-12 
  5. ↑ Davies, Teli (2022-09-29). "Make-A-Video: Meta AI's New Model For Text-To-Video Generation" (in en). https://wandb.ai/telidavies/ml-news/reports/Make-A-Video-Meta-AI-s-New-Model-For-Text-To-Video-Generation--VmlldzoyNzE4Nzcx. 
  6. ↑ 6.0 6.1 Monge, Jim Clyde (2022-08-03). "This AI Can Create Video From Text Prompt" (in en). https://betterprogramming.pub/this-ai-can-create-video-from-text-prompt-6904439d7aba. 
  7. ↑ "Meta's Make-A-Video AI creates videos from text". https://www.fonearena.com/blog/375627/meta-make-a-video-ai-create-videos-from-text.html. 
  8. ↑ "google: Google takes on Meta, introduces own video-generating AI". 6 October 2022. https://m.economictimes.com/tech/technology/google-takes-on-meta-introduces-own-video-generating-ai/articleshow/94681128.cms. 
  9. ↑ "Nuh-uh, Meta, we can do text-to-video AI, too, says Google". https://www.theregister.com/AMP/2022/10/06/google_ai_imagen_video/. 
  10. ↑ "Papers with Code - See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction" (in en). https://paperswithcode.com/paper/see-plan-predict-language-guided-cognitive. 
  11. ↑ "Papers with Code - Text-driven Video Prediction" (in en). https://paperswithcode.com/paper/text-driven-video-prediction. 
  12. ↑ page, Will Douglas Heavenarchive. "The original startup behind Stable Diffusion has launched a generative AI for video" (in en). https://www.technologyreview.com/2023/02/06/1067897/runway-stable-diffusion-gen-1-generative-ai-for-video/. 
  13. ↑ Wiggers, Kyle (2023-06-09). "Runway's Gen-2 shows the limitations of today's text-to-video tech" (in en-US). https://techcrunch.com/2023/06/09/runways-gen-2-shows-the-limitations-of-todays-text-to-video-tech/. 
  14. ↑ Luo, Zhengxiong; Chen, Dayou; Zhang, Yingya; Huang, Yan; Wang, Liang; Shen, Yujun; Zhao, Deli; Zhou, Jingren; Tan, Tieniu (2023). "VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation". arXiv:2303.08320 [cs.CV].
  15. ↑ Luo, Zhengxiong; Chen, Dayou; Zhang, Yingya; Huang, Yan; Wang, Liang; Shen, Yujun; Zhao, Deli; Zhou, Jingren; Tan, Tieniu (2023). "VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation". arXiv:2303.08320 [cs.CV].
  16. ↑ "Adobe launches Firefly Video model and enhances image, vector and design models. Adobe Newsroom". Adobe Inc.. 2024-10-10. https://news.adobe.com/news/2024/10/101424-adobe-launches-firefly-video-model. 
  17. ↑ Yirka, Bob (2024-01-26). "Google announces the development of Lumiere, an AI-based next-generation text-to-video generator.". https://techxplore.com/news/2024-01-google-lumiere-ai-based-generation.html. 
  18. ↑ "Text to Speech for Videos". https://www.synthesia.io/text-to-speech. 
  19. ↑ Nuñez, Michael (2024-06-12). "Luma AI debuts 'Dream Machine' for realistic video generation, heating up AI media race" (in en-US). https://venturebeat.com/ai/luma-ai-debuts-dream-machine-for-realistic-video-generation-heating-up-ai-media-race/. 
  20. ↑ Fink, Charlie. "Apple Debuts Intelligence, Mistral Raises $600 Million, New AI Text-To-Video" (in en). https://www.forbes.com/sites/charliefink/2024/06/13/apple-debuts-intelligence-mistral-raises-600-million-new-ai-text-to-video/. 
  21. ↑ Franzen, Carl (2024-06-12). "What you need to know about Kling, the AI video generator rival to Sora that's wowing creators" (in en-US). https://venturebeat.com/ai/what-you-need-to-know-about-kling-the-ai-video-generator-rival-to-sora-thats-wowing-creators/. 
  22. ↑ "ByteDance joins OpenAI's Sora rivals with AI video app launch". Reuters. 2024-08-06. https://www.reuters.com/technology/artificial-intelligence/bytedance-joins-openais-sora-rivals-with-ai-video-app-launch-2024-08-06/. 
  23. ↑ "Chinese ai "tiger" minimax launches text-to-video-generating model to rival OpenAI's sora". 2024-09-02. https://finance.yahoo.com/news/chinese-ai-tiger-minimax-launches-093000322.html. 
  24. ↑ Requiroso, Kelvene (2024-12-15). "Lightricks' LTXV Model Breaks Speed Records, Generating 5-Second AI Video Clips in 4 Seconds" (in en-US). https://www.eweek.com/news/lightricks-open-source-ai-video-generator/. 
  25. ↑ Text2Video-Zero, Picsart AI Research (PAIR), 2023-08-12, https://github.com/Picsart-AI-Research/Text2Video-Zero, retrieved 2023-08-12 
  26. ↑ Kemper, Jonathan (2024-07-01). "Runway's Sora competitor Gen-3 Alpha now available" (in en-US). https://the-decoder.com/runways-sora-competitor-gen-3-alpha-now-available/. 
  27. ↑ "Generative AI's Next Frontier Is Video" (in en). Bloomberg.com. 2023-03-20. https://www.bloomberg.com/news/articles/2023-03-20/generative-ai-s-next-frontier-is-video. 
  28. ↑ "OpenAI teases 'Sora,' its new text-to-video AI model" (in en). 2024-02-15. https://www.nbcnews.com/tech/tech-news/openai-sora-video-artificial-intelligence-unveiled-rcna139065. 
  29. ↑ Kelly, Chris (2024-06-25). "Toys R Us creates first brand film to use OpenAI's text-to-video tool" (in en-US). Informa. https://www.marketingdive.com/news/toys-r-us-openai-sora-gen-ai-first-text-video/719797/. 
  30. ↑ Jin, Jiayao; Wu, Jianhang; Xu, Zhoucheng; Zhang, Hang; Wang, Yaxin; Yang, Jielong (2023-08-04). "Text to Video: Enhancing Video Generation Using Diffusion Models and Reconstruction Network". 2023 2nd International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT). IEEE. pp. 108–114. doi:10.1109/CCPQT60491.2023.00024. ISBN 979-8-3503-4269-7. 
  31. ↑ "Announcing Black Forest Labs" (in en-US). 2024-08-01. https://blackforestlabs.ai/announcing-black-forest-labs/. 
  32. ↑ Forlini, Emily Dreibelbis (2024-09-18). "Google's veo text-to-video AI generator is coming to YouTube shorts". https://www.pcmag.com/news/googles-veo-text-to-video-ai-generator-is-coming-to-youtube-shorts. 
  33. ↑ Subin, Jennifer Elias,Samantha (2025-05-20). "Google launches Veo 3, an AI video generator that incorporates audio" (in en). https://www.cnbc.com/2025/05/20/google-ai-video-generator-audio-veo-3.html. 
  34. ↑ Fink, Charlie. "LTX Video Breaks The 60-Second Barrier, Redefining AI Video As A Longform Medium" (in en). https://www.forbes.com/sites/charliefink/2025/07/16/ltx-video-breaks-the-60-second-barrier-redefining-ai-video-as-a-longform-medium/. 
  35. ↑ "Lightricks' latest release lets creators direct long-form AI-generated videos in real time" (in en-US). 2025-07-16. https://siliconangle.com/2025/07/16/lightricks-latest-release-allows-creators-direct-longform-ai-generated-videos-real-time/. 
  36. ↑ Shahaf, Tal (2025-10-23). "Lightricks unveils powerful AI video model challenging OpenAI and Google" (in en). Ynetglobal. https://www.ynetnews.com/tech-and-digital/article/hklbzavrgx. 
  37. ↑ Bhagwatkar, Rishika; Bachu, Saketh; Fitter, Khurshed; Kulkarni, Akshay; Chiddarwar, Shital (2020-12-17). "A Review of Video Generation Approaches". 2020 International Conference on Power, Instrumentation, Control and Computing (PICC). IEEE. pp. 1–5. doi:10.1109/PICC51425.2020.9362485. ISBN 978-1-7281-7590-4. 
  38. ↑ Kim, Taehoon; Kang, ChanHee; Park, JaeHyuk; Jeong, Daun; Yang, ChangHee; Kang, Suk-Ju; Kong, Kyeongbo (2024-01-03). "Human Motion Aware Text-to-Video Generation with Explicit Camera Control". 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE. pp. 5069–5078. doi:10.1109/WACV57701.2024.00500. ISBN 979-8-3503-1892-0. 
  39. ↑ Singh, Aditi (2023-05-09). "A Survey of AI Text-to-Image and AI Text-to-Video Generators". 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC). IEEE. pp. 32–36. doi:10.1109/AIRC57904.2023.10303174. ISBN 979-8-3503-4824-8. 
  40. ↑ 40.0 40.1 40.2 40.3 Miao, Yibo; Zhu, Yifan; Dong, Yinpeng; Yu, Lijia; Zhu, Jun; Gao, Xiao-Shan (2024-09-08). "T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models". arXiv:2407.05965 [cs.CV].
  41. ↑ 41.0 41.1 41.2 41.3 Zhang, Ji; Mei, Kuizhi; Wang, Xiao; Zheng, Yu; Fan, Jianping (August 2018). "From Text to Video: Exploiting Mid-Level Semantics for Large-Scale Video Classification". 2018 24th International Conference on Pattern Recognition (ICPR). IEEE. pp. 1695–1700. doi:10.1109/ICPR.2018.8545513. ISBN 978-1-5386-3788-3. 
  42. ↑ Placido, Dani Di. "Google's AI Passed The 'Will Smith Eating Spaghetti' Test" (in en). https://www.forbes.com/sites/danidiplacido/2025/05/22/google-passed-the-will-smith-eating-spaghetti-test/. 
  43. ↑ 43.0 43.1 Bhagwatkar, Rishika; Bachu, Saketh; Fitter, Khurshed; Kulkarni, Akshay; Chiddarwar, Shital (2020-12-17). "A Review of Video Generation Approaches". 2020 International Conference on Power, Instrumentation, Control and Computing (PICC). IEEE. pp. 1–5. doi:10.1109/PICC51425.2020.9362485. ISBN 978-1-7281-7590-4. 
  44. ↑ 44.0 44.1 44.2 44.3 Singh, Aditi (2023-05-09). "A Survey of AI Text-to-Image and AI Text-to-Video Generators". 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC). IEEE. pp. 32–36. doi:10.1109/AIRC57904.2023.10303174. ISBN 979-8-3503-4824-8. 
  45. ↑ Singh, Aditi (2023-05-09). "A Survey of AI Text-to-Image and AI Text-to-Video Generators". 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC). IEEE. pp. 32–36. doi:10.1109/AIRC57904.2023.10303174. ISBN 979-8-3503-4824-8. 
  46. ↑ ქურასბედიანი, ალექსი (2025-06-09). "AI-Generated Photo Of Ukrainian Children In Military Uniforms Circulated Online | Mythdetector.com" (in en-US). https://mythdetector.com/en/ai-generated-photo-of-ukrainian-children/. 
  47. ↑ "Fake Ukraine ad urges kids to report relatives enjoying Russian music" (in en). 2025-03-28. https://www.euronews.com/my-europe/2025/03/28/fake-ukrainian-tv-advert-urges-children-to-report-relatives-listening-to-russian-music. 
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  50. ↑ "Deepfake video of Zelenskyy could be 'tip of the iceberg' in info war, experts warn" (in en). NPR. 2022-03-16. https://www.npr.org/2022/03/16/1087062648/deepfake-video-zelenskyy-experts-war-manipulation-ukraine-russia. 
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  52. ↑ "'Kaur vs KORE': Sunny Leone is all set to play double role in an AI-driven feature film - Report". The Times of India. 2025-09-24. ISSN 0971-8257. https://timesofindia.indiatimes.com/entertainment/hindi/bollywood/news/kaur-vs-kore-sunny-leone-is-all-set-to-play-double-role-in-an-ai-driven-feature-film-report/articleshow/124094700.cms. 
  53. ↑ Farzeen, Sana (2025-09-24). "Exclusive: Sunny Leone sets trend with AI-driven feature film 'Kaur vs KORE'" (in en). https://www.indiatoday.in/movies/bollywood/story/sunny-leone-ai-film-kaur-vs-kore-first-indian-ai-powered-feature-film-2792597-2025-09-24. 
  54. ↑ "Sunny Leone takes on dual role as human and AI avatar in 'Kaur vs KORE'" (in en). 2025-09-24. https://english.mathrubhumi.com/movies-music/news/kaur-vs-kore-sunny-leone-ai-film-t4782zmm. 
  55. ↑ Sharma, Manoj (2025-10-26). "From Mahabharat to Hanuman: Collective Artists Network's Vijay Subramaniam on how AI is shaping India's entertainment future" (in en). https://www.fortuneindia.com/business-news/from-mahabharat-to-hanuman-collective-artists-networks-vijay-subramaniam-on-how-ai-is-shaping-indias-entertainment-future/127699. 
  56. ↑ PTI (2025-08-20). "Anurag Kashyap slams producer Vijay Subramaniam over AI generated film ‘Chiranjeevi Hanuman’" (in en-IN). The Hindu. ISSN 0971-751X. https://www.thehindu.com/entertainment/movies/anurag-kashyap-vijay-subramaniam-ai-generated-chiranjeevi-hanuman-vikramaditya-motwane/article69955791.ece. 
  57. ↑ "AI-generated film Chiranjeevi Hanuman announced, Vikramaditya Motwane not pleased about it: ‘So it begins’" (in en). 2025-08-19. https://www.hindustantimes.com/entertainment/bollywood/aigenerated-film-chiranjeevi-hanuman-announced-vikramaditya-motwane-not-pleased-about-it-so-it-begins-101755586946675.html. 
  58. ↑ "Mahabharat: Ek Dharmayudh OTT release: When and where to watch India's first AI-powered mythological series". The Economic Times. 2025-10-23. ISSN 0013-0389. https://economictimes.indiatimes.com/magazines/panache/mahabharat-ek-dharmayudh-ott-release-when-and-where-to-watch-indias-first-ai-powered-mythological-series/articleshow/124751142.cms?from=mdr. 
  59. ↑ "'With AI Mahabharat, viewers will get to experience the same story in a new way'". The Times of India. 2025-10-18. ISSN 0971-8257. https://timesofindia.indiatimes.com/life-style/spotlight/with-ai-mahabharat-viewers-will-get-to-experience-the-same-story-in-a-new-way/articleshow/124663174.cms. 
  60. ↑ Ramachandran, Naman (2025-10-10). "AI-Powered ‘Mahabharat’ Trailer Bows Ahead of India Debut (EXCLUSIVE)" (in en-US). https://variety.com/2025/tv/news/ai-mahabharat-trailer-1236545384/. 
  61. ↑ 61.0 61.1 61.2 61.3 61.4 61.5 "Top AI Video Generation Models of 2024" (in en). https://deepgram.com/learn/top-ai-video-generation-models-of-2024. 
  62. ↑ 62.0 62.1 "Vexub – Text-to-video AI generator". https://vexub.com. 
  63. ↑ 63.0 63.1 "Runway Research | Gen-2: Generate novel videos with text, images or video clips" (in en). https://runwayml.com/research/gen-2. 
  64. ↑ 64.0 64.1 Sharma, Shubham (2023-12-26). "Pika Labs' text-to-video AI platform opens to all: Here's how to use it" (in en-US). https://venturebeat.com/ai/pika-labs-text-to-video-ai-platform-opens-to-all-heres-how-to-use-it/. 
  65. ↑ 65.0 65.1 "Runway Research | Introducing Gen-3 Alpha: A New Frontier for Video Generation" (in en). https://runwayml.com/research/introducing-gen-3-alpha. 
  66. ↑ "Meet Flow, AI-powered filmmaking with Veo 3". 20 May 2025. https://blog.google/technology/ai/google-flow-veo-ai-filmmaking-tool/. 
  67. ↑ "Google Veo DeepMind". https://deepmind.google/models/veo/. 
  68. ↑ 68.0 68.1 "Sora | OpenAI". https://openai.com/index/sora/. 
  69. ↑ Nuñez, Michael (2025-03-31). "Runway Gen-4 solves AI video’s biggest problem: character consistency across scenes" (in en-US). VentureBeat. https://venturebeat.com/ai/runways-gen-4-ai-solves-the-character-consistency-challenge-making-ai-filmmaking-actually-useful/. 
  70. ↑ "Runway’s New Gen-4 AI System Promises the Most Predictable Media Creation Yet | No Film School" (in en). https://nofilmschool.com/runway-gen-4-ai. 
  71. ↑ Wiggers, Kyle (2025-03-31). "Runway releases an impressive new video-generating AI model" (in en-US). https://techcrunch.com/2025/03/31/runway-releases-an-impressive-new-video-generating-ai-model/. 

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