PT

Aqui está a tradução do artigo frase a frase para português: **How To Use Google VEO 3 JSON Prompting To Create $100k AI Ads** **Como Usar o Prompt JSON do Google VEO 3 Para Criar Anúncios de IA de $100 mil**

#Ganhar dinheiro
2025-08-06 19:5131 min de leitura

Introdução ao Conteúdo

Este vídeo explica como criar anúncios virais usando um novo formato de prompting chamado prompting JSON. Ele mostra exemplos como os anúncios da VO3 Tree AI e demonstra como criar vídeos de unboxing visualmente impressionantes e anúncios profissionais com diferentes marcas e personagens. O vídeo fornece os prompts necessários e explica o uso de plataformas como Open Art e Google Flow para gerar esses vídeos. Ele também oferece um link para um chatbot personalizado para criar prompts JSON FO3, incentiva a experimentação criativa e sugere uma exploração mais aprofundada em histórias animadas por IA.

Informações-chave

  • A criação de prompts em JSON é uma forma de estruturar prompts de vídeo, o que pode levar a resultados impressionantes.
  • Você pode criar vários tipos de vídeos com ele, incluindo vídeos de unboxing, anúncios e conteúdo baseado em personagens.
  • O vídeo fornece acesso a um bot personalizado que gera prompts JSON e mostra exemplos de vídeos gerados por IA, como comerciais da Starbucks e anúncios de perfumes, para demonstrar o poder do prompting JSON.
  • Também sugere o uso do Open Art ou Google Flow para criar os vídeos. Links e uma descrição para uma newsletter estão disponíveis para ajudar as pessoas a terem acesso a prompts e conteúdo.

Análise da Linha do Tempo

Palavras-chave do Conteúdo

Okay, here's the translated version of "VO3 Tree AI ads & JSON Prompting" sentence by sentence into Portuguese:* **VO3 Tree AI ads** - Anúncios de VO3 Tree AI.* **& JSON Prompting** - & Prompting JSON.

Anúncios virais de VO3 Tree AI são criados usando prompting JSON, um novo formato que permite a criação de conteúdo impressionante. O vídeo mostrará como usar esse formato e fornecerá prompts para começar.

Okay, I'm ready. Please provide the article "IKEA Unboxing Videos" sentence by sentence, and I will translate each one into Portuguese.

Inspirado por vídeos de unboxing da IKEA, este método não se limita à IKEA e pode ser aplicado a diferentes marcas, estilos e até personagens. O vídeo irá guiá-lo na criação destes você mesmo, fornecendo prompts e exemplos criativos.

Aqui está a tradução do título "JSON Prompting Explained" para português, frase por frase:* **JSON Prompting Explained** - *JSON Prompting Explicado*

Aqui está a tradução do artigo, frase por frase:* JSON prompting is a way to structure your video and gives the AI a specific format. **O JSON prompting é uma maneira de estruturar seu vídeo e fornece um formato específico para a IA.*** The videos show examples of how to create a Starbucks ad, perfume ad, Apple ad, Ferrari ad using JSON prompting. **Os vídeos mostram exemplos de como criar um anúncio da Starbucks, um anúncio de perfume, um anúncio da Apple, um anúncio da Ferrari usando JSON prompting.*** A custom "Chip Bolt" tool is mentioned for generating JSON prompts, available via a link in the description. **Uma ferramenta personalizada "Chip Bolt" é mencionada para gerar JSON prompts, disponível através de um link na descrição.**

Okay, here's the translation of "Open Art Platform & Text to Video Generation" into Portuguese, sentence by sentence. Since it's a title, there isn't much to translate by sentence, but I'll provide a direct translation and some alternatives:**Direct Translation:*** Open Art Platform & Text to Video Generation -> Plataforma de Arte Aberta & Geração de Texto para Vídeo.**Alternative Translations (for better flow depending on context):*** Plataforma de Arte Aberta e Geração de Vídeo a partir de Texto. (This emphasizes that the video is generated *from* text.)* Plataforma Aberta de Arte e Geração de Vídeo com Texto. (This uses "com texto," implying the text is used *in* the video creation.)* Plataforma de Arte Livre & Geração de Vídeo via Texto. ("Livre" is another option for "Open," and "via Texto" is a more concise way to say "using Text.") Ultimately, the best translation will depend on the specific context in which the title is being used. The "Plataforma de Arte Aberta & Geração de Texto para Vídeo" is the most literal, but the alternatives might sound more natural in certain situations.

A plataforma Open Art é usada para acessar o Google V3 para gerar vídeos com prompts de texto, usando o modelo VO3 Tree com resolução de 1080p no modo rápido. Ela oferece acesso a múltiplos geradores de vídeo por IA, tornando-o mais fácil do que gerenciar múltiplas assinaturas. Prompts para transformações de quartos labuba são usados como exemplo, notando prompts personalizados para gerar um prompt JSON FO3 de uma transformação de quarto com abertura de caixa no estilo Tom e Jerry.

Ok, I'm ready. Please provide the article you would like me to translate into Portuguese, sentence by sentence. I will do my best to provide accurate and natural-sounding translations. Just paste the text here and I'll get started.

Um bot personalizado está disponível através de um link na descrição do vídeo para gerar prompts JSON. Usuários podem pedir ao bot para criar prompts, como uma transformação de sala de abertura de caixa no estilo Tom e Jerry, que o bot irá gerar no formato correto. Usuários podem ajustar o prompt ao seu gosto depois de gerado pelo bot.

Okay, here's the translation of "Creative AI Examples" sentence by sentence:* **Original:** Creative AI Examples* **Translation:** Exemplos de IA Criativa.

Aqui está a tradução do artigo frase por frase:* **Examples include a Pikachu-themed Pokeball bedroom and a Louis Vuitton luxury brand theme.** Exemplos incluem um quarto com tema de Pokebola do Pikachu e um tema da marca de luxo Louis Vuitton.* **It suggests using the format for professional advertisements and demonstrates generating prompts for Samsung or Apple product launches.** Sugere-se usar o formato para anúncios profissionais e demonstra a geração de prompts para lançamentos de produtos da Samsung ou Apple.* **A Ferrari advertisement is shown as another example.** Um anúncio da Ferrari é mostrado como outro exemplo.

Okay, I'm ready. Please provide the Starbucks commercial text and I will translate it into Portuguese, sentence by sentence.

Uma propaganda da Starbucks gerada por IA é apresentada como exemplo, sugerindo que poderia substituir uma propaganda de \$100.000. Um anúncio de perfume é exibido, incentivando os espectadores a tentarem criar anúncios similares com os prompts fornecidos. Prompts e inscrição para uma newsletter estão disponíveis na descrição.

Perguntas e respostas relacionadas

I don't have enough information to answer that question. I can generate human-like text in response to a wide range of prompts and questions, but my knowledge about VO3 Tree AI ads is limited.

Os anúncios de IA da Árvore VO3 são anúncios criados usando um novo formato de prompting chamado prompting JSON e estão se tornando virais.

JSON prompting is a technique used in interacting with large language models (LLMs) to encourage them to respond in a specific, structured JSON (JavaScript Object Notation) format. Essentially, you're guiding the LLM to produce its output in a predictable machine-readable format.Here's a breakdown of why it's useful and how it works:* **Purpose:** The main goal of JSON prompting is to get the LLM to return information in a structured way that is easily parsed and used by other programs or systems. Instead of free-form text, you get data that your code can directly process.* **How it works:** You craft your prompts to explicitly request the LLM to format its response as JSON. This may involve: * **Providing examples:** Showing the LLM examples of the desired JSON structure, including the key-value pairs and data types you want. (This is often called "few-shot learning"). * **Clear instructions:** Clearly stating in your prompt: "Return the result as a JSON object," or "Give me the output in JSON format with the following keys..." * **Schema Definition:** Sometimes including a schema (like JSON Schema) that describes the expected structure and data types. This is the most precise approach.* **Benefits:** * **Machine-readability:** JSON is easily parsed by programming languages, making it simple to extract the specific information you need. * **Data consistency:** By enforcing a structure, you get more consistent and reliable data from the LLM. This reduces the need for error handling and data cleaning. * **Automation:** Enables automation of tasks that rely on LLM output, such as data extraction, knowledge base creation, and generating structured reports.* **Example:** **Without JSON Prompting (Unstructured):** User prompt: "Tell me about the capital of France and its population." LLM response: "The capital of France is Paris, and its population is approximately 2.1 million people within the city limits." **With JSON Prompting (Structured):** User prompt: "Tell me about the capital of France and its population. Return the answer as a JSON object with keys 'capital' and 'population'. Example: `{'capital': 'London', 'population': 9000000}`" LLM response: `{"capital": "Paris", "population": 2100000}`* **Challenges:** * **LLM compliance:** LLMs aren't perfect, and they might occasionally generate invalid JSON or deviate from the requested structure, especially with complex schemas or unclear prompts. * **Prompt engineering:** Crafting effective JSON prompts requires careful experimenting and understanding of the LLM's capabilities and limitations. * **Cost:** Complex prompts can sometimes require more computation and therefore increase costs.In summary, JSON prompting is a valuable technique for harnessing the power of LLMs to generate structured data, making it easier to integrate LLM output into your applications and workflows. It involves designing prompts that explicitly instruct the LLM to provide results in JSON format, often including examples or schema definitions to ensure data consistency and machine-readability.

A solicitação JSON é um método para estruturar seus prompts de vídeo para que o Google V3 possa interpretá-los corretamente.

There isn't one single, universally recommended platform for using JSON prompting for AI video generation. The "best" platform depends heavily on your specific needs, technical skills, budget, and desired level of control. However, I can break down the options and highlight platforms that are commonly used and well-regarded within the AI video generation community:**Understanding the Landscape**First, it's important to understand that JSON prompting primarily serves as a method for structured input to *control* the video generation process of a specific AI model or service. It's usually not a feature of the platform *itself*, but rather a way to interact with it. You'll need a platform that *allows* for and effectively interprets JSON instructions.Here's a breakdown:* **AI Video Generation Models/APIs with JSON Support:** These form the core engine for generating the video. They accept JSON as a structured way to specify scene descriptions, character actions, camera movements, style choices, music cues, and more.* **Platforms/Frameworks for Interacting with those APIs:** These are the front-ends, development environments, or workflow services you use to *send* the JSON to the AI video generation model and manage the output.**Key Platforms and Approaches**Here's a breakdown of the likely recommendations and considerations you should make when choosing.1. **RunwayML Gen-2 and other Research Models (Advanced Users/Developers):** * **JSON Capability:** While not always directly advertised, if you're integrating into the models deeply you should be able to do it. * **Considerations:** RunwayML, in particular, is used by a lot of AI developers. Access to the core models often requires more technical expertise and may be accessed through APIs or command-line tools. Not as user-friendly for direct video creation. If you have an experienced developer, you can create elaborate and customized outputs.2. **Model Labs/Development Environments (More technical and customizable):**Many cloud platforms and services provide access to powerful AI models capable of video generation and are designed specifically for developers. Here's what to consider about them:* **Google Cloud AI Platform (Vertex AI):** Offers access to various AI models (including potentially video generation models as they become available) and provides robust tools for building and deploying AI applications. You could write code to format your prompts as JSON and send them to a Google Cloud model.* **Amazon SageMaker:** Similar to Google Cloud AI Platform, SageMaker provides a comprehensive environment for building, training, and deploying machine learning models.* **Microsoft Azure AI:** Azure offers a suite of AI services, including tools for video analysis and generation. You can leverage these services with JSON prompting to control the video creation process * **JSON Capability**: They support API-based calls with JSON payloads. * **Considerations**: Requires significant programming experience in Python or other languages. Offers the highest level of customization and control, but has a steeper learning curve. Best for complex projects and integrations. You would likely have to find and integrate third-party models yourself.3. **Custom Development (Highest Flexibility):** * **JSON Capability**: You define it. * **Considerations**: If you're building your own AI video generation model or significantly modifying an existing one, you'll have full control over how it interprets JSON prompts. This requires a very deep understanding of AI/ML and video processing.**Criteria for Choosing a Platform**When selecting a platform, consider these factors:* **Ease of Use:** How comfortable are you with coding and using APIs? Some platforms offer more user-friendly interfaces than others.* **Price:** AI video generation can be computationally expensive. Compare the pricing models of different platforms. Some charge per minute of video generated, while others offer subscription plans.* **Features:** Does the platform offer the specific features you need, such as style transfer, character animation, or music integration?* **Community and Support:** Is there a strong community of users and developers who can provide help and guidance?* **Speed and Quality:** How quickly can the platform generate videos, and what is the quality of the output?* **Customization:** How much control do you have over the video generation process? Can you fine-tune the AI model to achieve your desired results?* **JSON Support**: **Specifically**: How well does the platform document and handle JSON input for controlling parameters like scene description, camera movement, character actions, and style? Look for examples and clear explanations.**In Summary**To reiterate, there isn't one single *correct* answer. Start by identifying the *models* that generate video in ways that you like, then look at how to best interact with those models.

Open Art e Google Flow são as plataformas recomendadas para usar o uso de prompts JSON e a geração de vídeos por IA. Open Art oferece acesso fácil aos geradores de vídeo por IA com várias assinaturas diferentes.

To recommend the best type of video generation, I need more information! Tell me about:* **What is the purpose of the video?** (e.g., marketing, education, entertainment, internal training, social media)* **What is the subject matter?** (e.g., product demo, explainer video, animation, live-action, abstract artwork)* **Who is the target audience?** (e.g., age, interests, technical level)* **What is your budget?** (e.g., free, low-cost, professional)* **What is your timeline?** (e.g., quick turnaround, longer production time)* **What resources do you have available?** (e.g., actors, equipment, footage, technical skills)* **Any references of videos that match your preferences?** (If so, please provide the links to these videos.)Once I have this information, I can give you a more tailored recommendation.In the meantime, here are some *general* types of video generation:* **Live-Action:** Filming real people and environments. This is good for authenticity and showing realistic scenarios but can be expensive and time-consuming.* **Animation:** Creating videos using animated characters and environments. This is good for explaining complex concepts, creating fantastical worlds, and having tight control over the visuals. There are many subtypes, including: * **2D Animation:** Classic cartoon style, often simpler to produce. * **3D Animation:** More realistic and immersive but requires more advanced software and skills. * **Motion Graphics:** Using animated text and shapes to convey information. Great for explainer videos and marketing materials.* **Screen Recording:** Recording your computer screen to show software demonstrations or tutorials.* **Whiteboard Animation:** Drawing animations on a whiteboard to explain concepts.* **AI-Generated Video:** Videos created using AI tools, often from text prompts or existing images/videos. This can be quick and cost-effective, but the quality can vary.* **Stop-Motion Animation:** Manipulating physical objects in small increments and photographing them to create the illusion of movement.The more details you give me, the more helpful my recommendation will be!

Okay, I'm ready. Please provide the article "Text to Video and Google V3" sentence by sentence, and I will translate each one into Portuguese.

You can find premade JSON prompts in various places, depending on your use case and needs. Here's a breakdown of common resources and strategies:**1. Online Prompt Repositories & Communities:*** **PromptBase (promptbase.com):** A marketplace for buying and selling prompts, including JSON-based prompts for various AI models, particularly around data extraction, content generation, and task automation. You often have to pay, but it's a good place to see examples.* **Prompt Engineering Guide (promptengineering.org):** While not a repository, this site offers lots of structured information on how to design & build prompts, including using structured formats like JSON. It's primarily educational, but the examples are useful to adapt.* **Hugging Face Hub (HF Hub):** Search the Hugging Face Hub for datasets that contain prompts formatted using JSON. Look for datasets specifically mentioning "prompt" or "instructions" and check if the data is structured in JSON. Example datasets to look for: * Instruction datasets (e.g., "*instruction-tuning*") * Question answering datasets (where the question and answer could be contained in a JSON structure).* **GitHub (github.com):** Search on GitHub for repositories containing JSON prompt examples. Use keywords like "JSON prompt," "LLM JSON schema," "JSON API prompt," etc. Pay attention to the license of any repository you find. Example searches: * `"JSON prompt" LLM` * `"OpenAI" JSON prompts` * `JSON schema api extraction`* **Reddit (reddit.com):** Subreddits like r/LocalLLaMA, r/ChatGPT, r/LangChain, r/PromptEngineering often have users sharing prompts and discussing best practices, including using JSON. Search within those subreddits.**2. AI Development Platforms & Tools:*** **LangChain:** LangChain is a framework designed to build applications powered by language models. It supports structured outputs through Pydantic models and JSON Schema, which you can use to define the desired output format in your prompts. The LangChain documentation and examples are excellent resources.* **Semantic Kernel:** Semantic Kernel, from Microsoft, also provides tools and techniques to use JSON Schemas. Look for their examples and sample code.* **Guidance:** (GitHub: microsoft/guidance) Guidance enables you to control language models more effectively than standard prompting. It incorporates structure, conditionals, and tools into prompts in a user-friendly Pythonic way, and often involves defining JSON schemas within the Guidance language.**3. Task-Specific Resources:*** **Data Extraction Prompt Libraries:** If your goal is data extraction, look for libraries or tools that are *specifically designed* for that task. They may have pre-built JSON prompt templates or allow you to easily define the desired JSON output schema.* **API Interaction Tools:** If you're using JSON prompts to interact with APIs, check the API documentation for examples of request and response structures that can be adapted into prompts. Some APIs might even provide example prompts directly.**4. Creating Your Own:**The best prompts are often tailored to your specific needs. These structured generation workflows typically follow this layout:1. **Define your JSON Schema:** This is *crucial*. Use JSON Schema to explicitly declare the expected structure and data types of the JSON you want the LLM to output. There are online JSON Schema editors and validators to help you build this. Good Schema is the foundation for successful generation with LLMs.2. **Craft the Prompt:** Provide the LLM with clear instructions on what information to extract, summarize, or generate and *emphasize that the output MUST conform to the specified JSON Schema*. Give examples in your prompt.3. **Include examples in your prompt:** Especially including valid JSON output greatly increases the chance of your model conforming to the right structure.**Example (Conceptual - adapt to your use case):****JSON Schema (simplified):**```json{ "type": "object", "properties": { "title": { "type": "string", "description": "Title of the article" }, "author": { "type": "string", "description": "Author of the article" }, "summary": { "type": "string", "description": "A short summary of the article" } }, "required": ["title", "author", "summary"]}```**Prompt:**```Extract the title, author, and a short summary from the following article and format the output as a JSON object conforming to this schema:```json{ "type": "object", "properties": { "title": { "type": "string", "description": "Title of the article" }, "author": { "type": "string", "description": "Author of the article" }, "summary": { "type": "string", "description": "A short summary of the article" } }, "required": ["title", "author", "summary"]}```Here's an example of the output format:```json{ "title": "The Art of Prompt Engineering", "author": "Jane Doe", "summary": "This article discusses the key principles of prompt engineering."}```Here is the article:[Insert article text here]Return *ONLY* the JSON object as indicated in the examples provided.```**Key Considerations:*** **Specific Use Case:** The best place to find prompts depends heavily on what you're trying to accomplish. Focus your search on resources related to your task (e.g., data extraction, API interaction, content generation).* **LLM Model:** Prompts that work well for one LLM (e.g., GPT-4) may not work as effectively for another (e.g., Llama 2, Mixtral). Adapt prompts to the specific capabilities of the model you're using.* **Iterative Refinement:** Prompt engineering is an iterative process. Start with a basic prompt and refine it based on the results you get. Experiment with different phrasing, examples, and schema definitions.* **JSON Schema Validation:** After getting the output from the LLM, validate it against the JSON schema to ensure that it conforms to the expected format. This helps identify errors and improve your prompts.* **Context is Key**: The more context you provide the LLM through examples of JSON format, the more useful information it is able to pull out.By using these resources and techniques, you can find or create JSON prompts that effectively leverage the power of language models for your specific applications. Remember to iterate, experiment, and validate to achieve the best results.

O link para o bot personalizado/JSON Prompts está na descrição.

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