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B2B Tools You Need To Have in Your Arsenal in 2024

What's Next for AI: Interpreting Anthropic CEO's Vision

Què hi ha a continuació per a la IA: interpretar la visió del CEO antròpic

Co bude dál pro AI: Interpretace vize generálního ředitele společnosti Anthropic

Τι ακολουθεί για την AI: Ερμηνεύοντας το όραμα του CEO της Anthropic

¿Qué viene después en el mundo de la IA?: interpretación de la visión del director ejecutivo de Anthropic

AIの今後: Anthropic CEOのビジョンを解釈する

Nini ekoya sima pona AI: Ko interpréter Vision ya CEO Anthropic

AI-ийн дараагийн зүйл: Anthropic CEO-ийн алсын харааг тайлбарлах нь

Seo se Latelago bakeng sa AI: Go Hlatholla Pono ya CEO ya Anthropic

Leswi landzelaka eka AI: Ku hlamusela Xivono xa CEO wa Anthropic

Що далі для ШІ: інтерпретація бачення генерального директора Anthropic

AI uchun navbatdagi narsa: Antropik bosh direktorning qarashlarini talqin qilish

人工智能的下一步：解读 Anthropic 首席执行官的愿景

Authors:
(1) Yuwei Guo, The Chinese University of Hong Kong;
(2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author;
(3) Anyi Rao, Stanford University;
(4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory;
(5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory;
(6) Yu Qiao, Shanghai Artificial Intelligence Laboratory;
(7) Maneesh Agrawala, Stanford University;
(8) Dahua Lin, Shanghai Artificial Intelligence Laboratory;
(9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Table of Links Abstract and 1 Introduction 2 Work Related 3 Preliminary AnimateDiff 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.2 Learn Motion Priors with Motion Module 4.3 Adapt to New Motion Patterns with MotionLora 4.4 AnimateDiff in Practice 5 Experiments and 5.1 Qualitative Results 5.2 Qualitative Comparison 5.3 Ablative Study 5.4 Controllable Generation 6 Conclusion 7 Ethics Statement 8 Reproducibility Statement, Acknowledgement and References 5.4 CONTROLLABLE GENERATION. The separated learning of visual content and motion priors in AnimateDiff enables the direct application of existing content control approaches for controllable generation. To demonstrate this capability, we combined AnimateDiff with ControlNet (Zhang et al., 2023) to control the generation with extracted depth map sequence. In contrast to recent video editing techniques (Ceylan et al., 2023; Wang et al., 2023a) that employ DDIM (Song et al., 2020) inversion to obtain smoothed latent sequences, we generate animations from randomly sampled noise. As illustrated in Figure 8, our results exhibit meticulous motion details (such as hair and facial expressions) and high visual quality. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Yuwei Guo, The Chinese University of Hong Kong; (2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author; (3) Anyi Rao, Stanford University; (4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory; (5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory; (6) Yu Qiao, Shanghai Artificial Intelligence Laboratory; (7) Maneesh Agrawala, Stanford University; (8) Dahua Lin, Shanghai Artificial Intelligence Laboratory; (9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Authors: Authors: (1) Yuwei Guo, The Chinese University of Hong Kong; (2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author; (3) Anyi Rao, Stanford University; (4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory; (5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory; (6) Yu Qiao, Shanghai Artificial Intelligence Laboratory; (7) Maneesh Agrawala, Stanford University; (8) Dahua Lin, Shanghai Artificial Intelligence Laboratory; (9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Work Related 2 Work Related 3 Preliminary 3 Preliminary AnimateDiff AnimateDiff 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.2 Learn Motion Priors with Motion Module 4.2 Learn Motion Priors with Motion Module 4.3 Adapt to New Motion Patterns with MotionLora 4.3 Adapt to New Motion Patterns with MotionLora 4.4 AnimateDiff in Practice 4.4 AnimateDiff in Practice 5 Experiments and 5.1 Qualitative Results 5 Experiments and 5.1 Qualitative Results 5.2 Qualitative Comparison 5.2 Qualitative Comparison 5.3 Ablative Study 5.3 Ablative Study 5.4 Controllable Generation 5.4 Controllable Generation 6 Conclusion 6 Conclusion 7 Ethics Statement 7 Ethics Statement 8 Reproducibility Statement, Acknowledgement and References 8 Reproducibility Statement, Acknowledgement and References 5.4 CONTROLLABLE GENERATION. The separated learning of visual content and motion priors in AnimateDiff enables the direct application of existing content control approaches for controllable generation. To demonstrate this capability, we combined AnimateDiff with ControlNet (Zhang et al., 2023) to control the generation with extracted depth map sequence. In contrast to recent video editing techniques (Ceylan et al., 2023; Wang et al., 2023a) that employ DDIM (Song et al., 2020) inversion to obtain smoothed latent sequences, we generate animations from randomly sampled noise. As illustrated in Figure 8, our results exhibit meticulous motion details (such as hair and facial expressions) and high visual quality. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

AnimateDiff Combines with ControlNet for Precise Motion Control and High-Quality Video Generation

Authors:
(1) Yuwei Guo, The Chinese University of Hong Kong;
(2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author;
(3) Anyi Rao, Stanford University;
(4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory;
(5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory;
(6) Yu Qiao, Shanghai Artificial Intelligence Laboratory;
(7) Maneesh Agrawala, Stanford University;
(8) Dahua Lin, Shanghai Artificial Intelligence Laboratory;
(9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Table of Links Abstract and 1 Introduction 2 Work Related 3 Preliminary AnimateDiff 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.2 Learn Motion Priors with Motion Module 4.3 Adapt to New Motion Patterns with MotionLora 4.4 AnimateDiff in Practice 5 Experiments and 5.1 Qualitative Results 5.2 Qualitative Comparison 5.3 Ablative Study 5.4 Controllable Generation 6 Conclusion 7 Ethics Statement 8 Reproducibility Statement, Acknowledgement and References 5.2 QUANTITATIVE COMPARISON We conduct the quantitative comparison through user study and CLIP metrics. The comparison focuses on three key aspects: text alignment, domain similarity, and motion smoothness. The results are shown in Table 1. Detailed implementations can be found in supplementary materials. User study. In the user study, we generate animations using all three methods based on the same personalized T2I models. Participants are then asked to individually rank the results based on the above three aspects. We use the Average User Ranking (AUR) as a preference metric where a higher score indicates superior performance. Note that the corresponding prompts and images are provided for reference for text alignment and domain similarity evaluation. CLIP metric. We also employed the CLIP (Radford et al., 2021) metric, following the approach taken by previous studies (Wu et al., 2023; Khachatryan et al., 2023). When evaluating domain similarity, it is important to note that the CLIP score was computed between the animation frames and the reference images generated using the personalized T2Is. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Yuwei Guo, The Chinese University of Hong Kong; (2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author; (3) Anyi Rao, Stanford University; (4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory; (5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory; (6) Yu Qiao, Shanghai Artificial Intelligence Laboratory; (7) Maneesh Agrawala, Stanford University; (8) Dahua Lin, Shanghai Artificial Intelligence Laboratory; (9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Authors: Authors: (1) Yuwei Guo, The Chinese University of Hong Kong; (2) Ceyuan Yang, Shanghai Artificial Intelligence Laboratory with Corresponding Author; (3) Anyi Rao, Stanford University; (4) Zhengyang Liang, Shanghai Artificial Intelligence Laboratory; (5) Yaohui Wang, Shanghai Artificial Intelligence Laboratory; (6) Yu Qiao, Shanghai Artificial Intelligence Laboratory; (7) Maneesh Agrawala, Stanford University; (8) Dahua Lin, Shanghai Artificial Intelligence Laboratory; (9) Bo Dai, The Chinese University of Hong Kong and The Chinese University of Hong Kong. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Work Related 2 Work Related 3 Preliminary 3 Preliminary AnimateDiff AnimateDiff 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.1 Alleviate Negative Effects from Training Data with Domain Adapter 4.2 Learn Motion Priors with Motion Module 4.2 Learn Motion Priors with Motion Module 4.3 Adapt to New Motion Patterns with MotionLora 4.3 Adapt to New Motion Patterns with MotionLora 4.4 AnimateDiff in Practice 4.4 AnimateDiff in Practice 5 Experiments and 5.1 Qualitative Results 5 Experiments and 5.1 Qualitative Results 5.2 Qualitative Comparison 5.2 Qualitative Comparison 5.3 Ablative Study 5.3 Ablative Study 5.4 Controllable Generation 5.4 Controllable Generation 6 Conclusion 6 Conclusion 7 Ethics Statement 7 Ethics Statement 8 Reproducibility Statement, Acknowledgement and References 8 Reproducibility Statement, Acknowledgement and References 5.2 QUANTITATIVE COMPARISON We conduct the quantitative comparison through user study and CLIP metrics. The comparison focuses on three key aspects: text alignment, domain similarity, and motion smoothness. The results are shown in Table 1. Detailed implementations can be found in supplementary materials. User study. In the user study, we generate animations using all three methods based on the same personalized T2I models. Participants are then asked to individually rank the results based on the above three aspects. We use the Average User Ranking (AUR) as a preference metric where a higher score indicates superior performance. Note that the corresponding prompts and images are provided for reference for text alignment and domain similarity evaluation. User study. CLIP metric . We also employed the CLIP (Radford et al., 2021) metric, following the approach taken by previous studies (Wu et al., 2023; Khachatryan et al., 2023). When evaluating domain similarity, it is important to note that the CLIP score was computed between the animation frames and the reference images generated using the personalized T2Is. CLIP metric This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

User Preferences and CLIP Metrics: Results of AnimateDiff’s Performance in Video Generation

Shoukathali Jambagi on Strategic Vision and Business Process Transformation

شوكاثالي جامباجي يتحدث عن الرؤية الاستراتيجية وتحويل العمليات التجارية

Shoukathali Jambagi o strategické vizi a transformaci obchodních procesů

Shoukathali Jambagi über strategische Vision und Geschäftsprozesstransformation

Shoukathali Jambagi sobre la visión estratégica y la transformación de los procesos de negocio

Shoukathali Jambagi o strateškoj viziji i transformaciji poslovnih procesa

戦略的ビジョンとビジネスプロセス変革について語るShoukathali Jambagi

შუკათალი ჯამბაგი სტრატეგიული ხედვისა და ბიზნეს პროცესის ტრანსფორმაციის შესახებ

Shoukathali Jambagi mengenai Visi Strategik dan Transformasi Proses Perniagaan

Shoukathali Jambagi om strategisk vision och affärsprocesstransformation

Шоукаталӣ Ҷамбагӣ дар бораи дидгоҳи стратегӣ ва табдили равандҳои тиҷорат

Shoukathali Jambagi เกี่ยวกับวิสัยทัศน์เชิงกลยุทธ์และการเปลี่ยนแปลงกระบวนการทางธุรกิจ

Шукаталі Джамбагі про стратегічне бачення та трансформацію бізнес-процесів

Uni-OVSeg: A Step Towards Efficient and Bias-Resilient Vision Systems

In today’s digital age, the demand for high-quality video content is skyrocketing across various sectors, from education to entertainment. AI video generators have emerged as essential tools to meet this growing need, offering innovative solutions that simplify and accelerate the video creation process. Enter Pollo AI, a revolutionary AI-driven video generator that promises to transform how we create and share videos with its smart, user-friendly technology. In this review, we will delve into Pollo AI's features, exploring how it stands out in the crowded field of video generation tools. What Is Pollo AI? Pollo AI is a state-of-the-art AI video generator that can take any text prompt you provide and convert it into a high-quality, professional video clip. For example, by entering a prompt like “A chess match between AI and an alien,” Pollo AI can generate a visual clip that vividly brings your text to life. Its text-to-video functionality makes creating engaging content easier than ever. Pollo AI’s innovative image-to-video feature allows users to transform static images into dynamic, high-class visual outcomes effortlessly. Simply upload an image, and Pollo AI will generate a captivating video that brings the image back to reality with motion and effects. This feature is perfect for creating engaging visual content for social media or educational purposes. How Does Pollo AI Work? Pollo AI is an intuitive tool designed for both first-timers and professionals who need to generate creative and engaging AI videos easily. Here is a comprehensive breakdown of the simple steps to get this platform started: Step 1: Input Text Prompt or Photos To create a video with Pollo AI, simply type your text prompt, like “a bomb exploded in a desert” or “a cat is walking toward a flower, sniffing and licking it,” and Pollo AI will visualize it for you. Additionally, you can upload an image, such as a family photo, and Pollo AI will create a video or animation based on that image. Step 2: Customize Your Input With Pollo AI, you can customize your video using Standard or Professional modes, choose an aspect ratio like 16:9 or 9:16, and control the length of your video. You can also adjust the prompt adherence slider for creative flexibility and select camera movements such as Horizontal Pan or Vertical Pan to tailor your video’s specifics. Step 3: Click Create to Start the Process After inputting all your preferred video settings, the final step is to hit the Create button and let Pollo AI start crafting your video. The processing time may vary based on factors like the use of Professional Mode and the video’s length and complexity, so be patient while Pollo AI works its magic. Step 4: Check Out the Ultimate Creation When the visual content is complete, you can view it directly in your browser. You have the option to watch it multiple times, save it, download it, share it, or use it however you like. If you are not satisfied, you can always return to the drawing board and start the process again. Why Choose Pollo AI? While there are other AI video generators available on the market, Pollo AI stands out as the superior option for creating high-class visual content. Let’s dive into its main features in detail. Text-To-Video Transformation: With a simple text prompt, Pollo AI can bring your ideas to life by identifying crucial elements and visualizing them in a compelling video. This tool creatively interprets your instructions, delivering the perfect video style and content for your specific needs. Refresh the Story of Your Image: Give your static images a dynamic makeover. Along with your text inputs, Pollo AI can breathe life into your visuals by creating videos that narrate their stories while preserving the original content. This smart tool transforms simple images into engaging, story-driven animations. Versatile AI Video Creation: Pollo AI can turn your ideas in mind into videos of any style you desire. Whether you envision lifelike cinematic sequences or creative, stylized animations, Pollo AI offers limitless possibilities to bring your concepts to vibrant life. Rapid Video Production: Its state-of-the-art video generation algorithms are engineered for speed, enabling Pollo AI to produce high-quality videos in mere minutes. Whether you need a quick turnaround for a project or want to see your ideas come to life swiftly, Pollo AI ensures you won’t have to wait long. Exceptional Video Quality: Pollo AI leverages cutting-edge technology to transform your creative ideas into stunning, high-definition videos that meet professional standards. The result is a perfect fusion of innovation and excellence, offering you visually captivating outputs that stand out. Effortless Video Creation: Users do not need any technical video-editing skills to utilize Pollo AI. This AI video generator is designed to be user-friendly and intuitive, simplifying the video creation process. With Pollo AI, anyone can easily create professional-grade videos without prior experience or technical knowledge. Summary Pollo AI sets a new benchmark in the world of video generation with its advanced, user-centric technology. By streamlining the video creation process, it allows users to produce high-quality content quickly and effortlessly, making it an invaluable tool for content creators. In a market crowded with video generation tools, Pollo AI stands out not only for its intelligent features but also for its commitment to delivering exceptional results. Whether you are a novice or a professional, Pollo AI provides the perfect blend of innovation and ease of use, ensuring your visual outcomes are both stunning and impactful. This story was distributed by Margrowth under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author In today’s digital age, the demand for high-quality video content is skyrocketing across various sectors, from education to entertainment. AI video generators have emerged as essential tools to meet this growing need, offering innovative solutions that simplify and accelerate the video creation process. Enter Pollo AI , a revolutionary AI-driven video generator that promises to transform how we create and share videos with its smart, user-friendly technology. In this review, we will delve into Pollo AI's features, exploring how it stands out in the crowded field of video generation tools. Pollo AI Pollo AI What Is Pollo AI? Pollo AI is a state-of-the-art AI video generator that can take any text prompt you provide and convert it into a high-quality, professional video clip. For example, by entering a prompt like “A chess match between AI and an alien,” Pollo AI can generate a visual clip that vividly brings your text to life. Its text-to-video functionality makes creating engaging content easier than ever. text-to-video text-to-video Pollo AI’s innovative image-to-video feature allows users to transform static images into dynamic, high-class visual outcomes effortlessly. Simply upload an image, and Pollo AI will generate a captivating video that brings the image back to reality with motion and effects. This feature is perfect for creating engaging visual content for social media or educational purposes. image-to-video image-to-video How Does Pollo AI Work? Pollo AI is an intuitive tool designed for both first-timers and professionals who need to generate creative and engaging AI videos easily. Here is a comprehensive breakdown of the simple steps to get this platform started: Step 1: Input Text Prompt or Photos To create a video with Pollo AI, simply type your text prompt, like “a bomb exploded in a desert” or “a cat is walking toward a flower, sniffing and licking it,” and Pollo AI will visualize it for you. Additionally, you can upload an image, such as a family photo, and Pollo AI will create a video or animation based on that image. Step 2: Customize Your Input With Pollo AI, you can customize your video using Standard or Professional modes, choose an aspect ratio like 16:9 or 9:16, and control the length of your video. You can also adjust the prompt adherence slider for creative flexibility and select camera movements such as Horizontal Pan or Vertical Pan to tailor your video’s specifics. Step 3: Click Create to Start the Process After inputting all your preferred video settings, the final step is to hit the Create button and let Pollo AI start crafting your video. The processing time may vary based on factors like the use of Professional Mode and the video’s length and complexity, so be patient while Pollo AI works its magic. Step 4: Check Out the Ultimate Creation When the visual content is complete, you can view it directly in your browser. You have the option to watch it multiple times, save it, download it, share it, or use it however you like. If you are not satisfied, you can always return to the drawing board and start the process again. Why Choose Pollo AI? While there are other AI video generators available on the market, Pollo AI stands out as the superior option for creating high-class visual content. Let’s dive into its main features in detail. Text-To-Video Transformation: With a simple text prompt, Pollo AI can bring your ideas to life by identifying crucial elements and visualizing them in a compelling video. This tool creatively interprets your instructions, delivering the perfect video style and content for your specific needs. Text-To-Video Transformation: With a simple text prompt, Pollo AI can bring your ideas to life by identifying crucial elements and visualizing them in a compelling video. This tool creatively interprets your instructions, delivering the perfect video style and content for your specific needs. Refresh the Story of Your Image: Give your static images a dynamic makeover. Along with your text inputs, Pollo AI can breathe life into your visuals by creating videos that narrate their stories while preserving the original content. This smart tool transforms simple images into engaging, story-driven animations. Refresh the Story of Your Image: Give your static images a dynamic makeover. Along with your text inputs, Pollo AI can breathe life into your visuals by creating videos that narrate their stories while preserving the original content. This smart tool transforms simple images into engaging, story-driven animations. Versatile AI Video Creation: Pollo AI can turn your ideas in mind into videos of any style you desire. Whether you envision lifelike cinematic sequences or creative, stylized animations, Pollo AI offers limitless possibilities to bring your concepts to vibrant life. Versatile AI Video Creation: Pollo AI can turn your ideas in mind into videos of any style you desire. Whether you envision lifelike cinematic sequences or creative, stylized animations, Pollo AI offers limitless possibilities to bring your concepts to vibrant life. Rapid Video Production: Its state-of-the-art video generation algorithms are engineered for speed, enabling Pollo AI to produce high-quality videos in mere minutes. Whether you need a quick turnaround for a project or want to see your ideas come to life swiftly, Pollo AI ensures you won’t have to wait long. Rapid Video Production: Its state-of-the-art video generation algorithms are engineered for speed, enabling Pollo AI to produce high-quality videos in mere minutes. Whether you need a quick turnaround for a project or want to see your ideas come to life swiftly, Pollo AI ensures you won’t have to wait long. Exceptional Video Quality: Pollo AI leverages cutting-edge technology to transform your creative ideas into stunning, high-definition videos that meet professional standards. The result is a perfect fusion of innovation and excellence, offering you visually captivating outputs that stand out. Exceptional Video Quality: Pollo AI leverages cutting-edge technology to transform your creative ideas into stunning, high-definition videos that meet professional standards. The result is a perfect fusion of innovation and excellence, offering you visually captivating outputs that stand out. Effortless Video Creation: Users do not need any technical video-editing skills to utilize Pollo AI. This AI video generator is designed to be user-friendly and intuitive, simplifying the video creation process. With Pollo AI, anyone can easily create professional-grade videos without prior experience or technical knowledge. Effortless Video Creation: Users do not need any technical video-editing skills to utilize Pollo AI. This AI video generator is designed to be user-friendly and intuitive, simplifying the video creation process. With Pollo AI, anyone can easily create professional-grade videos without prior experience or technical knowledge. Summary Pollo AI sets a new benchmark in the world of video generation with its advanced, user-centric technology. By streamlining the video creation process, it allows users to produce high-quality content quickly and effortlessly, making it an invaluable tool for content creators. Pollo AI Pollo AI In a market crowded with video generation tools, Pollo AI stands out not only for its intelligent features but also for its commitment to delivering exceptional results. Whether you are a novice or a professional, Pollo AI provides the perfect blend of innovation and ease of use, ensuring your visual outcomes are both stunning and impactful. This story was distributed by Margrowth under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Margrowth under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Margrowth under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author https://business.hackernoon.com/brand-as-author

Pollo AI Review: Intelligent AI-Based Video Generator

Pollo AI Review: Intelligenter KI-basierter Videogenerator

Reseña de Pollo AI: generador de videos inteligente basado en inteligencia artificial

סקירת Pollo AI: מחולל וידאו חכם מבוסס בינה מלאכותית

Pollo AI Revizyon: Entelijan AI ki baze sou dèlko videyo

Ulasan Pollo AI: Generator Video Cerdas Berbasis AI

Pollo AI Recensione: generatore video intelligente basato sull'intelligenza artificiale

Pollo AI レビュー: インテリジェントな AI ベースのビデオ ジェネレーター

Pollo AI მიმოხილვა: ინტელექტუალური AI-ზე დაფუძნებული ვიდეო გენერატორი

Pollo AI Review: ម៉ាស៊ីនបង្កើតវីដេអូដែលមានមូលដ្ឋានលើ AI ឆ្លាតវៃ

Pollo AI Review: Intelligente AI-gebaseerde videogenerator

Recenzia Pollo AI: Inteligentný videogenerátor založený na AI

Pollo AI İncelemesi: Akıllı AI Tabanlı Video Oluşturucu

LOS ANGELES, United States, October 30th, 2024/Chainwire/--Xsolla,a global video game commerce company, announces plans to launch Xsolla ZK and introduce a digital backpack of virtual items on the blockchain. Xsolla ZK is powered by ZKsync technology and will drive the continuous growth and expansion of Web3 technologies to further develop solutions on the blockchain for the video game industry. Xsolla ZK will become part of the Elastic Chain ecosystem- an expanding constellation of interconnected chains powered by Zksync, an Ethereum Layer 2 zero-knowledge roll-up technology. Xsolla ZK will also introduce its ‘digital backpack’ for game developers, item creators, and gaming infrastructure providers to store and manage in-game items. Xsolla has seen success in the gaming industry, with two decades of experience, over 2,500 games monetized with its products, and over 1,000 developers and publishers utilizing its technology for their games. Lee Jacobson, Senior Vice President of Business Development Web3 at Xsolla, expressed his enthusiasm for the project: "Xsolla ZK leverages Ethereum Layer 2 zk Rollup technology to create a digital backpack for game developers. By deploying our expertise on the ZKsync Elastic Chain, we provide game developers with a scalable and pioneering solution aligning with the economic models with which they are familiar. Xsolla ZK is not just about innovation; it's about creating real value for the gaming community."Xsolla will combine its expertise in in-game commerce with ZKsync’s cutting-edge blockchain technology. Rich Kim, Head of Gaming at Matter Labs, said, "We are thrilled to see companies like Xsolla launch pioneering projects for Web3 gaming. For gaming ecosystems to thrive, it’s critical to close the gap for both users and builders; builders need proven, plug-and-play infrastructure to launch rich features while handling the performance required by mass usage games. Additionally, users need easy-to-use and convenient in-game features and payment options that can be leveraged across a broad ecosystem of games. Xsolla ZK is carving a path for gaming to transition and thrive in Web3." About Xsolla Xsolla is a global video game commerce company with a robust and powerful set of tools and services designed specifically for the industry. Since its founding in 2005, Xsolla has helped thousands of game developers and publishers of all sizes fund, market, launch, and monetize their games globally and across multiple platforms. As an innovative leader in game commerce, Xsolla’s mission is to solve the inherent complexities of global distribution, marketing, and monetization to help their partners reach more geographies, generate more revenue, and create relationships with gamers worldwide. Headquartered and incorporated in Los Angeles, California, with offices in Montreal, London, Berlin, Beijing, Guangzhou, Seoul, Tokyo, Kuala Lumpur, Raleigh, and other cities around the world, Xsolla supports major gaming titles like Valve, Take-Two, KRAFTON, Nexters, NetEase, Playstudios, Playrix, miHoYo, and more. About the Elastic Chain The Elastic Chain is an ever-expanding cluster of ZK rollups, secured by cryptography and designed for native interoperability with a unified, seamless user experience. The Elastic Chain delivers the functionality of a multi-chain ecosystem with the simplicity of a single blockchain, enabling scalable, secure, and efficient transactions. These core components ensure that this cluster of ZK Chains can interact and transact with each other efficiently, inheriting the security of Ethereum and forming a network that can scale horizontally without compromising on the core properties that make blockchains so powerful. For more information about Xsolla ZK and how to get early access, users can visit: xsolla.pro/zk For additional information and to learn more, users can visit xsolla.com. For additional information and to learn more, users can visit matter-labs.io. Contact Global Director of Public Relations Derrick Stembridge Xsolla d.stembridge@xsolla.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here LOS ANGELES, United States, October 30th, 2024/Chainwire/--Xsolla,a global video game commerce company, announces plans to launch Xsolla ZK and introduce a digital backpack of virtual items on the blockchain. Xsolla ZK is powered by ZKsync technology and will drive the continuous growth and expansion of Web3 technologies to further develop solutions on the blockchain for the video game industry. Xsolla ZK will become part of the Elastic Chain ecosystem- an expanding constellation of interconnected chains powered by Zksync, an Ethereum Layer 2 zero-knowledge roll-up technology. Elastic Chain Elastic Chain Xsolla ZK will also introduce its ‘digital backpack’ for game developers, item creators, and gaming infrastructure providers to store and manage in-game items. Xsolla has seen success in the gaming industry, with two decades of experience, over 2,500 games monetized with its products, and over 1,000 developers and publishers utilizing its technology for their games. Lee Jacobson, Senior Vice President of Business Development Web3 at Xsolla, expressed his enthusiasm for the project: "Xsolla ZK leverages Ethereum Layer 2 zk Rollup technology to create a digital backpack for game developers. By deploying our expertise on the ZKsync Elastic Chain, we provide game developers with a scalable and pioneering solution aligning with the economic models with which they are familiar. Xsolla ZK is not just about innovation; it's about creating real value for the gaming community."Xsolla will combine its expertise in in-game commerce with ZKsync’s cutting-edge blockchain technology. Rich Kim, Head of Gaming at Matter Labs, said, "We are thrilled to see companies like Xsolla launch pioneering projects for Web3 gaming. For gaming ecosystems to thrive, it’s critical to close the gap for both users and builders; builders need proven, plug-and-play infrastructure to launch rich features while handling the performance required by mass usage games. Additionally, users need easy-to-use and convenient in-game features and payment options that can be leveraged across a broad ecosystem of games. Xsolla ZK is carving a path for gaming to transition and thrive in Web3." Rich Kim, Head of Gaming at Matter Labs, said, "We are thrilled to see companies like Xsolla launch pioneering projects for Web3 gaming. For gaming ecosystems to thrive, it’s critical to close the gap for both users and builders; builders need proven, plug-and-play infrastructure to launch rich features while handling the performance required by mass usage games. Additionally, users need easy-to-use and convenient in-game features and payment options that can be leveraged across a broad ecosystem of games. Xsolla ZK is carving a path for gaming to transition and thrive in Web3." About Xsolla Xsolla is a global video game commerce company with a robust and powerful set of tools and services designed specifically for the industry. Xsolla Xsolla Since its founding in 2005, Xsolla has helped thousands of game developers and publishers of all sizes fund, market, launch, and monetize their games globally and across multiple platforms. As an innovative leader in game commerce, Xsolla’s mission is to solve the inherent complexities of global distribution, marketing, and monetization to help their partners reach more geographies, generate more revenue, and create relationships with gamers worldwide. Headquartered and incorporated in Los Angeles, California, with offices in Montreal, London, Berlin, Beijing, Guangzhou, Seoul, Tokyo, Kuala Lumpur, Raleigh, and other cities around the world, Xsolla supports major gaming titles like Valve, Take-Two, KRAFTON, Nexters, NetEase, Playstudios, Playrix, miHoYo, and more. About the Elastic Chain The Elastic Chain is an ever-expanding cluster of ZK rollups, secured by cryptography and designed for native interoperability with a unified, seamless user experience. Elastic Chain Elastic Chain The Elastic Chain delivers the functionality of a multi-chain ecosystem with the simplicity of a single blockchain, enabling scalable, secure, and efficient transactions. These core components ensure that this cluster of ZK Chains can interact and transact with each other efficiently, inheriting the security of Ethereum and forming a network that can scale horizontally without compromising on the core properties that make blockchains so powerful. For more information about Xsolla ZK and how to get early access, users can visit: xsolla.pro/zk xsolla.pro/zk xsolla.pro/zk For additional information and to learn more, users can visit xsolla.com . xsolla.com xsolla.com For additional information and to learn more, users can visit matter-labs.io . matter-labs.io matter-labs.io Contact Global Director of Public Relations Derrick Stembridge Xsolla d.stembridge@xsolla.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here

Xsolla To Launch Xsolla ZK, Advancing Web3 Adoption For Video Games

Xsolla, Xsolla ZK-ni işə salır, Video Oyunlar üçün Web3 qəbulunu inkişaf etdirir

Xsolla ke spuštění Xsolla ZK, postupující přijetí Web3 pro videohry

Xsolla lanzará Xsolla ZK, impulsando la adopción de Web3 para videojuegos

Xsolla lanzará Xsolla ZK, avanzando na adopción de Web3 para videoxogos

Xsolla が Xsolla ZK をリリース、ビデオゲームへの Web3 導入を推進

Xsolla Ko Lancer Xsolla ZK, Ko Avancé Adoption Web3 Pona Ba Jeux Vidéo

Xsolla lanceert Xsolla ZK, wat de acceptatie van Web3 voor videogames bevordert

Xsolla lançará Xsolla ZK, promovendo a adoção do Web3 para videogames

Xsolla va lansa Xsolla ZK, promovând adoptarea Web3 pentru jocurile video

Xsolla Kuzindua Xsolla ZK, Kuendeleza Uasili wa Web3 kwa Michezo ya Video

Xsolla запускає Xsolla ZK, просуваючи впровадження Web3 для відеоігор

I-Xsolla iyakuQalisa i-Xsolla ZK, iPhuhlisa iWeb3 yoMthombo kwiMidlalo yeVidiyo

Hey Hackers!Connectech ID has been nominated inHackerNoon's Startups of The Year 2024 awards in Jakarta, Indonesia under the Media category. Please vote for us here: https://hackernoon.com/startups/asia/asia-jakarta-indonesia?stup=66f320316ea4677e23de94b3&embedable=true Read more about us below to understand why we deserve your vote. Tell us what your Startup is all about Founded in 2023, Connectech ID is a Jakarta-based digital marketing agency focused on community building, social media management, and content creation for tech companies and startups. Our mission is to connect global tech companies with the dynamic Indonesian market, through customized digital strategies and collaborative community activations. We've had the privilege of working with clients like BenQ and ID Cloud Host, organizing events that have significantly boosted their outreach and engagement. What inspired you to launch your startup in the Media industry, and what unique value does your company bring to this space? The idea for Connectech ID came from my own experiences in digital marketing and community building. After being laid off, I noticed that many tech startups were struggling to engage their audiences and build communities, both of which are critical for long-term growth. That’s when I saw the opportunity to help fill that gap. I launched Connectech ID to provide strategic media solutions that help businesses not only thrive but also grow with their communities. Since I’ve been involved in Indonesia tech community for over 5 years, we’re able to craft tailored content and campaigns that truly resonate with niche audiences. We’re not just a marketing agency; we build communities that grow alongside the businesses we support. I’m also passionate about supporting fellow tech professionals who have been laid off, as I’ve experienced the same challenges of navigating a difficult job market. What have been the biggest challenges in disrupting the traditional media and entertainment landscape, and how has your startup overcome them? One of the biggest challenges has been helping tech companies shift from traditional marketing approaches to community-driven strategies. Many are focused on short-term gains and hesitate to invest in the longer-term process of community building. To address this, I focus on educating clients about the benefits of community-driven marketing. Building strong relationships with audiences leads to better retention and organic growth in the long run. We also tailor our strategies to fit each client’s unique needs, which allows us to align their goals with the broader benefits of community engagement. How do you stay ahead of the rapidly changing trends and technologies in the Media industry to ensure your startup remains relevant and competitive? At Connectech ID, staying ahead means constantly learning and experimenting. We use AI tools to enhance content creation, keep a close eye on emerging trends and algorithms, and stay connected with tech communities by attending their events and hosting our own. But most importantly, we prioritize creating authentic content that provides real value to our members. We want to genuinely contribute to our communities, not just take advantage of opportunities. This approach keeps us relevant and allows our clients to stay ahead of the curve. What are your long-term vision and goals for your company, and how do you plan to continue innovating and growing in the future? My long-term vision for Connectech ID is to become a global leader in tech community-building and content creation. While we currently focus on Indonesia, we aim to expand our reach internationally, helping businesses across different markets. We’ll continue innovating by integrating new digital marketing trends, and expanding our services to offer more comprehensive solutions. Our goal is to help companies grow sustainably, emphasizing long-term community engagement and thoughtful digital strategies. Final Thoughts The journey with Connectech ID has been full of both challenges and rewards. It’s a constant learning experience, and I’m grateful for the opportunity to grow alongside the businesses and communities we work with. I’m thankful to the team, our community, and everyone who has believed in Connectech’s vision. Together, we’re building lasting connections and creating real impact—not just in Indonesia, but globally. Vote for us today! Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here.
Want to nominate a startup? Follow the steps here.Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Hey Hackers! Connectech ID has been nominated in HackerNoon's Startups of The Year 2024 awards in Jakarta, Indonesia under the Media category. HackerNoon's Startups of The Year 2024 Media Please vote for us here: Please vote for us here: https://hackernoon.com/startups/asia/asia-jakarta-indonesia?stup=66f320316ea4677e23de94b3&embedable=true https://hackernoon.com/startups/asia/asia-jakarta-indonesia?stup=66f320316ea4677e23de94b3&embedable=true Read more about us below to understand why we deserve your vote. Tell us what your Startup is all about Founded in 2023, Connectech ID is a Jakarta-based digital marketing agency focused on community building, social media management, and content creation for tech companies and startups. Our mission is to connect global tech companies with the dynamic Indonesian market, through customized digital strategies and collaborative community activations. We've had the privilege of working with clients like BenQ and ID Cloud Host, organizing events that have significantly boosted their outreach and engagement. What inspired you to launch your startup in the Media industry, and what unique value does your company bring to this space? The idea for Connectech ID came from my own experiences in digital marketing and community building. After being laid off, I noticed that many tech startups were struggling to engage their audiences and build communities, both of which are critical for long-term growth. That’s when I saw the opportunity to help fill that gap. I launched Connectech ID to provide strategic media solutions that help businesses not only thrive but also grow with their communities. Since I’ve been involved in Indonesia tech community for over 5 years, we’re able to craft tailored content and campaigns that truly resonate with niche audiences. We’re not just a marketing agency; we build communities that grow alongside the businesses we support. I’m also passionate about supporting fellow tech professionals who have been laid off, as I’ve experienced the same challenges of navigating a difficult job market. What have been the biggest challenges in disrupting the traditional media and entertainment landscape, and how has your startup overcome them? One of the biggest challenges has been helping tech companies shift from traditional marketing approaches to community-driven strategies. Many are focused on short-term gains and hesitate to invest in the longer-term process of community building. To address this, I focus on educating clients about the benefits of community-driven marketing. Building strong relationships with audiences leads to better retention and organic growth in the long run. We also tailor our strategies to fit each client’s unique needs, which allows us to align their goals with the broader benefits of community engagement. How do you stay ahead of the rapidly changing trends and technologies in the Media industry to ensure your startup remains relevant and competitive? At Connectech ID, staying ahead means constantly learning and experimenting. We use AI tools to enhance content creation, keep a close eye on emerging trends and algorithms, and stay connected with tech communities by attending their events and hosting our own. But most importantly, we prioritize creating authentic content that provides real value to our members. We want to genuinely contribute to our communities, not just take advantage of opportunities. This approach keeps us relevant and allows our clients to stay ahead of the curve. What are your long-term vision and goals for your company, and how do you plan to continue innovating and growing in the future? My long-term vision for Connectech ID is to become a global leader in tech community-building and content creation. While we currently focus on Indonesia, we aim to expand our reach internationally, helping businesses across different markets. We’ll continue innovating by integrating new digital marketing trends, and expanding our services to offer more comprehensive solutions. Our goal is to help companies grow sustainably, emphasizing long-term community engagement and thoughtful digital strategies. Final Thoughts The journey with Connectech ID has been full of both challenges and rewards. It’s a constant learning experience, and I’m grateful for the opportunity to grow alongside the businesses and communities we work with. I’m thankful to the team, our community, and everyone who has believed in Connectech’s vision. Together, we’re building lasting connections and creating real impact—not just in Indonesia, but globally. Vote for us today! Vote for us today ! Vote for us today Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here. Want to nominate a startup? Follow the steps here. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here . Startups of The Year 2024 create a brand profile create a brand profile create a brand profile here here Want to nominate a startup? Follow the steps here . here here Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here , here , and here . last year’s Startups of The Year interview questions last year’s Startups of The Year interview questions here here here here here here

From Layoff to Launch: Connectech ID's Vision for Indonesia's Tech Community

Are you looking to create engaging faceless short videos for platforms like YouTube or TikTok but want to avoid the hassle of complex video editing? This article will walk you through how to automate the entire process using OpenAI, ElevenLabs, and MoviePy. By the end of this tutorial, you'll know how to automatically generate visuals and voiceovers for short videos based on any script. Whether you’re creating educational content, storytelling, or meme videos, this workflow will save you tons of time. Prerequisites Before getting started, you’ll need: API keys for both OpenAI (for generating visuals) and ElevenLabs (for voiceovers).
Basic Python knowledge.
MoviePy and other required Python libraries installed (moviepy, openai, elevenlabs, etc.). Step 1: Setting Up API Keys import openai
from elevenlabs import ElevenLabs

# Set up your OpenAI and ElevenLabs API keys
openai.api_key = "your_openai_api_key"
elevenlabs_client = ElevenLabs(api_key="your_elevenlabs_api_key") Start by getting API keys from OpenAI and ElevenLabs. Replace the placeholders in the code with your actual API keys. Step 2: Preparing the Script Your video starts with a story or script. You can replace the story_script variable with the text you want to turn into a video. Here’s an example script about Dogecoin: story_script = """
Dogecoin began as a joke in 2013, inspired by the popular 'Doge' meme featuring a Shiba Inu dog. It unexpectedly gained a massive following thanks to its community's charitable initiatives, eventually evolving into a legitimate cryptocurrency with support from Elon Musk.
""" The script will be split into sentences to match each visual and audio segment. Step 3: Generating Images with OpenAI’s DALL-E For each sentence, we generate a corresponding image using OpenAI’s DALL-E model. def generate_image_from_text(sentence, context, idx):
    prompt = f"Generate an image without any text that describes: {sentence}. Context: {context}"
    response = openai.images.generate(
        model="dall-e-3",
        prompt=prompt,
        size="1024x1792",
        response_format="b64_json"
    )

    image_filename = f"images/image_{idx}.jpg"
    with open(image_filename, "wb") as f:
        f.write(base64.b64decode(response.data[0].b64_json))
    return image_filename This function sends each sentence to DALL-E and saves the generated image. We ensure the generated visuals match the video's theme. Step 4: Generating Voiceovers with ElevenLabs Once we have the visuals, we need voiceovers. ElevenLabs converts each sentence into speech. def generate_audio_from_text(sentence, idx):
    audio = elevenlabs_client.text_to_speech.convert(
        voice_id="pqHfZKP75CvOlQylNhV4",
        model_id="eleven_multilingual_v2",
        text=sentence,
        voice_settings=VoiceSettings(stability=0.2, similarity_boost=0.8)
    )
    audio_filename = f"audio/audio_{idx}.mp3"
    with open(audio_filename, "wb") as f:
        for chunk in audio:
            f.write(chunk)
    return audio_filename This function generates an audio file for each sentence. You can select different voice settings to customize the narration style. Step 5: Combining Audio and Video Next, we pair each image with its corresponding voiceover using MoviePy: from moviepy.editor import ImageClip, AudioFileClip

image_clip = ImageClip(image_path, duration=audio_clip.duration)
image_clip = image_clip.set_audio(audio_clip)
video_clips.append(image_clip.set_fps(30)) Each image is displayed for the duration of its audio clip, ensuring synchronization. Step 6: Applying Video Effects To make the video more dynamic, we apply zoom and fade effects to each image. For example, the apply_zoom_in_center effect slowly zooms into the center of the image: def apply_zoom_in_center(image_clip, duration):
    return image_clip.resize(lambda t: 1 + 0.04 * t) Other effects include zooming in from the upper part or zooming out. These effects are applied randomly to each clip to keep the video visually engaging. Step 7: Final Video Assembly We combine all video clips into one seamless video and add background music: final_video = concatenate_videoclips(video_clips, method="compose")
final_video.write_videofile(output_video_path, codec="libx264", audio_codec="aac", fps=30) Step 8: Adding Captions Captions improve video accessibility and engagement. We use Captacity to automatically add captions based on the audio. captacity.add_captions(
    video_file=output_video_path,
    output_file="captioned_video.mp4",
    font_size=130,
    font_color="yellow",
    stroke_width=3
) Step 9: Adding Background Music To finish the video, background music is added. The volume is reduced so that it doesn't overpower the narration. background_music = AudioFileClip(music_filename).subclip(0, final_video.duration).volumex(0.2)
narration_audio = final_video.audio.volumex(1.5)
combined_audio = CompositeAudioClip([narration_audio, background_music])
final_video.set_audio(combined_audio) Conclusion The GitHub repository for this project is available here. By using OpenAI and ElevenLabs, we’ve automated the creation of faceless videos from text. You can now quickly generate YouTube Shorts or TikToks without needing a camera or microphone. This automated process has allowed us to create a Faceless Shorts Video service on our Robopost software, offering content creators a seamless way to produce high-quality videos. Whether you are creating educational videos, short stories, or even meme-style content, this service handles everything from visuals to voiceovers with minimal effort. Now, you can focus on creativity and storytelling while Robopost handles the heavy lifting of video production. Happy creating! Are you looking to create engaging faceless short videos for platforms like YouTube or TikTok but want to avoid the hassle of complex video editing? This article will walk you through how to automate the entire process using OpenAI , ElevenLabs , and MoviePy . OpenAI ElevenLabs MoviePy By the end of this tutorial, you'll know how to automatically generate visuals and voiceovers for short videos based on any script. Whether you’re creating educational content, storytelling, or meme videos, this workflow will save you tons of time. Prerequisites Before getting started, you’ll need: API keys for both OpenAI (for generating visuals) and ElevenLabs (for voiceovers). Basic Python knowledge. MoviePy and other required Python libraries installed (moviepy, openai, elevenlabs, etc.). API keys for both OpenAI (for generating visuals) and ElevenLabs (for voiceovers). API keys Basic Python knowledge. MoviePy and other required Python libraries installed ( moviepy , openai , elevenlabs , etc.). moviepy openai elevenlabs Step 1: Setting Up API Keys import openai
from elevenlabs import ElevenLabs

# Set up your OpenAI and ElevenLabs API keys
openai.api_key = "your_openai_api_key"
elevenlabs_client = ElevenLabs(api_key="your_elevenlabs_api_key") import openai
from elevenlabs import ElevenLabs

# Set up your OpenAI and ElevenLabs API keys
openai.api_key = "your_openai_api_key"
elevenlabs_client = ElevenLabs(api_key="your_elevenlabs_api_key") Start by getting API keys from OpenAI and ElevenLabs . Replace the placeholders in the code with your actual API keys. OpenAI ElevenLabs Step 2: Preparing the Script Your video starts with a story or script. You can replace the story_script variable with the text you want to turn into a video. Here’s an example script about Dogecoin : story_script Dogecoin story_script = """
Dogecoin began as a joke in 2013, inspired by the popular 'Doge' meme featuring a Shiba Inu dog. It unexpectedly gained a massive following thanks to its community's charitable initiatives, eventually evolving into a legitimate cryptocurrency with support from Elon Musk.
""" story_script = """
Dogecoin began as a joke in 2013, inspired by the popular 'Doge' meme featuring a Shiba Inu dog. It unexpectedly gained a massive following thanks to its community's charitable initiatives, eventually evolving into a legitimate cryptocurrency with support from Elon Musk.
""" The script will be split into sentences to match each visual and audio segment. Step 3: Generating Images with OpenAI’s DALL-E For each sentence, we generate a corresponding image using OpenAI’s DALL-E model. def generate_image_from_text(sentence, context, idx):
    prompt = f"Generate an image without any text that describes: {sentence}. Context: {context}"
    response = openai.images.generate(
        model="dall-e-3",
        prompt=prompt,
        size="1024x1792",
        response_format="b64_json"
    )

    image_filename = f"images/image_{idx}.jpg"
    with open(image_filename, "wb") as f:
        f.write(base64.b64decode(response.data[0].b64_json))
    return image_filename def generate_image_from_text(sentence, context, idx):
    prompt = f"Generate an image without any text that describes: {sentence}. Context: {context}"
    response = openai.images.generate(
        model="dall-e-3",
        prompt=prompt,
        size="1024x1792",
        response_format="b64_json"
    )

    image_filename = f"images/image_{idx}.jpg"
    with open(image_filename, "wb") as f:
        f.write(base64.b64decode(response.data[0].b64_json))
    return image_filename This function sends each sentence to DALL-E and saves the generated image. We ensure the generated visuals match the video's theme. Step 4: Generating Voiceovers with ElevenLabs Once we have the visuals, we need voiceovers. ElevenLabs converts each sentence into speech. def generate_audio_from_text(sentence, idx):
    audio = elevenlabs_client.text_to_speech.convert(
        voice_id="pqHfZKP75CvOlQylNhV4",
        model_id="eleven_multilingual_v2",
        text=sentence,
        voice_settings=VoiceSettings(stability=0.2, similarity_boost=0.8)
    )
    audio_filename = f"audio/audio_{idx}.mp3"
    with open(audio_filename, "wb") as f:
        for chunk in audio:
            f.write(chunk)
    return audio_filename def generate_audio_from_text(sentence, idx):
    audio = elevenlabs_client.text_to_speech.convert(
        voice_id="pqHfZKP75CvOlQylNhV4",
        model_id="eleven_multilingual_v2",
        text=sentence,
        voice_settings=VoiceSettings(stability=0.2, similarity_boost=0.8)
    )
    audio_filename = f"audio/audio_{idx}.mp3"
    with open(audio_filename, "wb") as f:
        for chunk in audio:
            f.write(chunk)
    return audio_filename This function generates an audio file for each sentence. You can select different voice settings to customize the narration style. Step 5: Combining Audio and Video Next, we pair each image with its corresponding voiceover using MoviePy : MoviePy from moviepy.editor import ImageClip, AudioFileClip

image_clip = ImageClip(image_path, duration=audio_clip.duration)
image_clip = image_clip.set_audio(audio_clip)
video_clips.append(image_clip.set_fps(30)) from moviepy.editor import ImageClip, AudioFileClip

image_clip = ImageClip(image_path, duration=audio_clip.duration)
image_clip = image_clip.set_audio(audio_clip)
video_clips.append(image_clip.set_fps(30)) Each image is displayed for the duration of its audio clip, ensuring synchronization. Step 6: Applying Video Effects To make the video more dynamic, we apply zoom and fade effects to each image. For example, the apply_zoom_in_center effect slowly zooms into the center of the image: apply_zoom_in_center def apply_zoom_in_center(image_clip, duration):
    return image_clip.resize(lambda t: 1 + 0.04 * t) def apply_zoom_in_center(image_clip, duration):
    return image_clip.resize(lambda t: 1 + 0.04 * t) Other effects include zooming in from the upper part or zooming out. These effects are applied randomly to each clip to keep the video visually engaging. Step 7: Final Video Assembly We combine all video clips into one seamless video and add background music: final_video = concatenate_videoclips(video_clips, method="compose")
final_video.write_videofile(output_video_path, codec="libx264", audio_codec="aac", fps=30) final_video = concatenate_videoclips(video_clips, method="compose")
final_video.write_videofile(output_video_path, codec="libx264", audio_codec="aac", fps=30) Step 8: Adding Captions Captions improve video accessibility and engagement. We use Captacity to automatically add captions based on the audio. Captacity captacity.add_captions(
    video_file=output_video_path,
    output_file="captioned_video.mp4",
    font_size=130,
    font_color="yellow",
    stroke_width=3
) captacity.add_captions(
    video_file=output_video_path,
    output_file="captioned_video.mp4",
    font_size=130,
    font_color="yellow",
    stroke_width=3
) Step 9: Adding Background Music To finish the video, background music is added. The volume is reduced so that it doesn't overpower the narration. background_music = AudioFileClip(music_filename).subclip(0, final_video.duration).volumex(0.2)
narration_audio = final_video.audio.volumex(1.5)
combined_audio = CompositeAudioClip([narration_audio, background_music])
final_video.set_audio(combined_audio) background_music = AudioFileClip(music_filename).subclip(0, final_video.duration).volumex(0.2)
narration_audio = final_video.audio.volumex(1.5)
combined_audio = CompositeAudioClip([narration_audio, background_music])
final_video.set_audio(combined_audio) Conclusion The GitHub repository for this project is available here. The GitHub repository for this project is available here. By using OpenAI and ElevenLabs, we’ve automated the creation of faceless videos from text. You can now quickly generate YouTube Shorts or TikToks without needing a camera or microphone. This automated process has allowed us to create a Faceless Shorts Video service on our Robopost software , offering content creators a seamless way to produce high-quality videos. Whether you are creating educational videos, short stories, or even meme-style content, this service handles everything from visuals to voiceovers with minimal effort. Faceless Shorts Video service Faceless Shorts Video service on our Robopost software Robopost software Now, you can focus on creativity and storytelling while Robopost handles the heavy lifting of video production. Happy creating!

How to Use ElevenLabs and OpenAI to Automate Faceless Shorts Video for YouTube and TikTok

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