Google Vertex AI Tutorial & Overview (Better Than ChatGPT?!)

James NoCode
9 Jun 202329:25

TLDRDiscover Google's Vertex AI, a powerful large language model rivaling ChatGPT. Explore its capabilities in model building, deployment, and scaling with managed ML tools. Dive into Model Gardens for standard and fine-tunable models, and the innovative Generative AI Studio for customizing AI responses. Learn how to integrate these models into applications via APIs, and join Patreon for exclusive access to apps and in-depth content.

Takeaways

  • 🌐 Google Vertex AI is a platform for building, deploying, and scaling machine learning models with fully managed ML tools for various use cases.
  • 🔍 The Model Garden within Vertex AI offers a variety of standard models for different applications, including text, image, audio, and video processing.
  • 🎨 Generative AI Studio allows users to test, customize, and deploy generative AI models, leveraging their capabilities in applications with a focus on language and speech models.
  • 📝 Users can design and test their own prompts for AI models, refining the model's responses based on specific instructions and examples.
  • 🔄 Model tuning is possible by uploading data in JSONL format, which helps the model learn desired behaviors and responses.
  • 📊 The platform provides examples and contexts for various use cases, such as chat summarization, classification, entity extraction, writing, and ideation.
  • 🔗 API integration is available for the models, enabling easy connection and communication with the models from external applications.
  • 🚀 No-code tools like Flutter Flow can be used to build applications that integrate with Vertex AI's models through API calls.
  • 🌟 Patreon community members get exclusive access to apps built on the channel and can clone and experiment with generative AI apps using Vertex AI.
  • 🎥 The video provides a detailed tutorial and overview of Google's Vertex AI, positioning it as a strong alternative to other popular language models like ChatGPT.

Q & A

  • What is Google Vertex AI?

    -Google Vertex AI is a platform that enables users to build, deploy, and scale machine learning models faster with fully managed ML tools for any use case.

  • How can one access Google Vertex AI?

    -To access Google Vertex AI, one needs to search for 'Google Vertex AI', go to the console, and if they have Firebase or Google projects, they can directly use it. Otherwise, they need to create a new project.

  • What types of models are available in Vertex AI's Model Garden?

    -Model Garden offers a variety of models including foundation models like Palm 2 for text and chat, fine-tunable image classification models like Vision Transformer, and models for detecting people, vehicles, and more in videos or images.

  • What is the Generative AI Studio in Vertex AI?

    -The Generative AI Studio is a tool within Vertex AI that allows users to quickly test and customize generative AI models to leverage their capabilities in applications.

  • How can users experiment with prompts in the Generative AI Studio?

    -Users can design, test, and refine their own prompts by providing instructions and examples to the models. They can adjust the model's responses to fit their desired format and content.

  • What parameters can users adjust in the Generative AI Studio?

    -Users can adjust parameters like temperature, which controls the creativity of the model, and token limits, which determine the maximum amount of text output from one prompt.

  • How can users save and revisit their prompt designs?

    -Users can save their prompts by clicking on 'My Prompts' and revisit them later for further adjustments or testing.

  • What is model tuning in the context of Vertex AI?

    -Model tuning in Vertex AI involves uploading a JSON file containing input-text and output-text pairs to train the model according to specific user requirements.

  • How can the AI models in Vertex AI be integrated into applications?

    -The Generative AI Studio provides an API that allows users to connect the AI models to their applications. Users can use the API through various programming languages or tools like Flutter Flow.

  • What is the benefit of using Vertex AI for generative AI applications?

    -Using Vertex AI for generative AI applications allows for faster and potentially more customized responses, as users can fine-tune models and adjust them to their specific needs. It also provides a range of models suitable for various applications.

Outlines

00:00

🌐 Introducing Google's Large Language Model (LLM) and Vertex AI

The paragraph introduces the viewer to Google's large language model (LLM) and Vertex AI, highlighting that there are numerous LLMs beyond GPT and ChatGPT. The speaker mentions an app called LM Studio that allows for testing and interaction with various LLMs. The focus then shifts to explaining how to access and utilize Vertex AI by searching for it and navigating through the platform's features, such as Model Garden and Generative AI Studio. The speaker emphasizes the ability to build, deploy, and scale machine learning models efficiently using Vertex AI's fully managed tools.

05:02

🛠️ Exploring Generative AI Studio and Prompt Design

This paragraph delves into the functionalities of the Generative AI Studio within Vertex AI, where users can test, customize, and leverage generative AI models for their applications. The speaker discusses the ability to experiment with different prompts, which are instructions given to the LLM to shape the output. The paragraph also covers the process of fine-tuning a model by providing it with examples to guide its responses. The speaker demonstrates how to use the Generative AI Studio to get desired answers from the model, adjusting parameters such as temperature and token limits to control the creativity and length of the output.

10:02

📝 Customizing Responses and Model Tuning

The speaker continues to explore the customization of AI responses through the use of examples and the model tuning process. The paragraph explains how users can shape the AI's answers by providing specific questions and corresponding desired answers. It also introduces the concept of 'tuning' an existing model by uploading a JSON file containing input-output pairs to alter the model's behavior according to user preferences. The speaker provides an example of how to format and use this file for model tuning, emphasizing the flexibility and adaptability of the AI to meet specific user needs.

15:02

🔗 Integrating AI Models with Applications via APIs

This paragraph discusses the integration of AI models with applications through APIs. The speaker explains the process of connecting to an AI model using an API, starting with executing a command in a cloud shell to obtain an access token. The paragraph details the steps to configure an API call within a no-code tool like Flutter Flow, including setting up the request with the necessary headers and body. The speaker demonstrates how to test the API call and extract the relevant information from the response to be used within an app. The focus is on the practical application of the AI model in a real-world scenario, showcasing the ease of integration and the potential for creating AI-powered applications.

20:03

🎉 Demonstrating AI Integration in a No-Code App

The speaker concludes the video by demonstrating the successful integration of the AI model into a simple no-code app built in Flutter Flow. The app allows users to input questions and receive answers from the AI model via API calls. The paragraph highlights the speed and accuracy of the AI's responses, which are tailored to the user's specifications through the examples and tuning process explained earlier. The speaker emphasizes the potential of Vertex AI for building generative AI applications and invites viewers to explore the platform further, while also promoting the Patreon community for exclusive access to the apps and content created by the speaker.

Mindmap

Keywords

💡Google Vertex AI

Google Vertex AI is a suite of tools and services provided by Google Cloud that enables users to build, deploy, and scale machine learning models more efficiently. It offers fully managed ML tools for various use cases, making it easier for developers and businesses to integrate AI into their applications. In the video, the presenter introduces Google Vertex AI as an alternative to other large language models like GPT, highlighting its capabilities and features such as Model Garden and Generative AI Studio.

💡Large Language Models (LLMs)

Large Language Models, or LLMs, are AI models that process and generate human-like text based on the input they receive. They are trained on vast amounts of data to understand and produce text in a way that can be useful for various applications, such as content generation, chatbots, and summarization. The video discusses LLMs like GPT and ChatGPT, and introduces Google's contribution to this field through Vertex AI, emphasizing the versatility and potential for customization of these models.

💡Model Garden

Model Garden is a feature within Google Vertex AI that provides a collection of pre-built machine learning models for users to interact with and utilize. These models cover a range of applications, from text and image processing to speech recognition and generation. In the video, the presenter mentions Model Garden as a resource where users can find and use different standard models for their projects without having to build them from scratch.

💡Generative AI Studio

Generative AI Studio is a component of Google Vertex AI that allows users to test, customize, and deploy generative AI models quickly. It offers a user-friendly interface where users can experiment with different prompts and model behaviors, fine-tuning the AI to produce specific types of responses or outputs. The video highlights the Generative AI Studio as a powerful tool for developers to leverage the capabilities of AI in their applications, with the ability to adjust parameters and save prompt designs for future use.

💡Prompts

In the context of the video, prompts are the inputs or instructions given to the AI models to guide their output. They are essential for shaping the response of the AI, telling it what kind of information is needed and in what format. The presenter demonstrates how to use prompts effectively in the Generative AI Studio to get precise answers, and how they can be customized and saved for reuse in different scenarios.

💡Fine-tuning

Fine-tuning is the process of adjusting a pre-trained AI model to better suit specific use cases or meet particular performance criteria. It involves feeding the model additional data and examples to teach it how to behave in the desired manner. In the video, the presenter explains how users can fine-tune models in Google Vertex AI by uploading JSON formatted data that includes example inputs and desired outputs, allowing for a more personalized AI behavior.

💡API Integration

API (Application Programming Interface) Integration refers to the process of connecting an external service or tool to an application, allowing them to communicate and exchange data. In the video, the presenter shows how to integrate Google Vertex AI's generative models with other applications using APIs, demonstrating the potential for developers to incorporate AI capabilities into their own projects, such as a no-code app built in Flutter Flow.

💡Flutter Flow

Flutter Flow is a no-code app development platform that enables users to build applications without writing code. It offers a visual interface for designing and configuring app elements, such as API calls and user interactions. The video features the creation of a simple app in Flutter Flow that interacts with Google Vertex AI's models, showcasing how easy it is to integrate AI capabilities into no-code applications.

💡No-Code

No-Code refers to the development approach where applications are built without traditional programming languages. Instead, users rely on visual interfaces and pre-built components to create functional apps. The video demonstrates the use of no-code tools like Flutter Flow to integrate with complex technologies like Google Vertex AI, making AI accessible to a wider range of users without the need for extensive coding skills.

💡Patreon Community

The Patreon Community mentioned in the video is a platform where creators offer exclusive content and resources to their supporters, who become patrons by contributing financially. In this context, the presenter is a member of such a community and provides apps and other resources related to AI and technology to the patrons. The Patreon Community allows members to access, clone, and experiment with the apps built by the presenter, as well as participate in live streams and masterclass series.

Highlights

Google's Vertex AI offers a powerful large language model (LLM) for various applications.

Vertex AI enables faster building, deploying, and scaling of machine learning models with fully managed ML tools.

Model Garden provides access to standard models like Foundation models and fine-tunable models for specific use cases.

Generative AI Studio allows users to test, customize, and leverage generative AI models for applications.

Language models in Vertex AI can be used for chat generation, content generation, chat summarization, and more.

The platform offers a variety of models for text, audio, image, and video applications.

Users can design and test their own prompts to get desired responses from the AI models.

Prompt tuning allows users to upload data to train and customize models according to their preferences.

API integration enables developers to connect Vertex AI models with their own applications for seamless functionality.

The tutorial demonstrates connecting Vertex AI with a no-code platform like Flutter Flow for easy app development.

The generative AI models can be fine-tuned with examples and specific formatting for precise outputs.

Vertex AI's generative models are noted for their speed and ability to respond in a format specified by the user.

The platform supports a wide range of languages for speech models, including text-to-speech and speech-to-text.

Exclusive apps and tools used in the video are available to members of the Patreon community.

The video provides a comprehensive overview of Vertex AI's capabilities and practical applications.