Omni Prompting with gpt-4o-mini | A Staple In The Future of AI Software?

All About AI
22 Jul 202413:17

TLDRThis video discusses the concept of 'omn' prompting, utilizing the capabilities of the GPT-40 Mini model for multimodal AI interactions, including text, vision, and voice. The presenter highlights the benefits of using visual prompts alongside text, demonstrates a screen-sharing app that integrates with GPT-40 Mini for real-time analysis and questions, and emphasizes the potential of low-cost, high-output AI models for creating personalized assistants and innovative applications.

Takeaways

  • 🌟 The concept of 'omn' prompting is introduced, which combines text, vision, and voice inputs for AI models like gpt-4o-mini.
  • 🚀 The release of gpt-4o-mini is significant, offering multi-modal capabilities and a lower cost that makes it viable for various applications.
  • 💡 The speaker emphasizes the importance of context and the potential of using visual prompts alongside text in AI interactions.
  • 🛠️ API calls can be made with multiple modalities using gpt-4o-mini, including text and image inputs, and potentially voice in the future.
  • 💰 The price of using gpt-4o-mini is highlighted as being very low, making it accessible for integration into various projects and applications.
  • 🖼️ The speaker demonstrates a screen share app called 'cognicast' that uses gpt-4o-mini to analyze images and provide descriptions.
  • 🔍 The app 'cognicast' can be used to monitor and analyze any selected window or the full screen, offering a personalized assistant experience.
  • 📈 The potential of gpt-4o-mini is discussed in terms of creating a hyper-personal assistant that could integrate voice, text, and images.
  • 🔗 The integration of gpt-4o-mini into websites is suggested as a way to provide users with immediate analysis and insights from images and text.
  • 🎨 The speaker shares a website where users can test out 'omn' prompting with gpt-4o-mini, offering a hands-on experience of the technology.
  • 🔍 The future possibilities of integrating voice with text and images in AI models are discussed, indicating an exciting direction for AI development.

Q & A

  • What is the concept of 'Omni Prompting' discussed in the video?

    -Omni Prompting is a concept that leverages multimodal inputs such as text, vision, and voice to interact with AI models like GPT-4 Mini, allowing for a more comprehensive and contextual interaction with the AI.

  • Why did the presenter choose to discuss GPT-4 Mini in the video?

    -The presenter chose to discuss GPT-4 Mini because of its capabilities to handle multimodal inputs and its significantly lower cost, which makes it viable for a wide range of applications.

  • How can GPT-4 Mini take advantage of both text and visual inputs?

    -GPT-4 Mini can take advantage of both text and visual inputs by making an API call that includes text type and an image URL, allowing for a more integrated response based on both types of input.

  • What is the significance of the low cost of GPT-4 Mini for its applications?

    -The low cost of GPT-4 Mini makes it feasible to use for a variety of applications, including screen share apps and image analysis, without worrying about the financial implications of extensive API calls.

  • What is the 'Cognic Cast' app mentioned in the video?

    -Cognic Cast is a screen share app created by the presenter that uses GPT-4 Mini to analyze and respond to what is happening on the computer screen, enhancing the user's interactive experience with AI.

  • How does the presenter plan to integrate voice input into the Omni Prompting concept?

    -The presenter plans to integrate voice input by expecting future updates to the GPT-4 Mini model that will allow voice to be included in the same API call as text and image inputs, creating a more seamless interaction.

  • What is the price structure for using GPT-4 Mini as mentioned in the video?

    -The price for using GPT-4 Mini is 15 cents per million input tokens and 60 cents per 1 million output tokens, with a provision for low-resolution image inputs costing 0.42 USD each.

  • What is the role of the 'detail love' setting in the presenter's code?

    -The 'detail love' setting in the presenter's code is used to select low resolution for the images being sent to GPT-4 Mini, which helps in reducing the cost of each image input.

  • How does the presenter's screen share app work with GPT-4 Mini?

    -The screen share app works by capturing screenshots of the selected window or screen, sending it along with a text prompt to GPT-4 Mini, and then receiving a response that analyzes or describes the content of the image.

  • What is the potential impact of the low cost of GPT-4 Mini on future AI applications?

    -The low cost of GPT-4 Mini could lead to a surge in the development of AI applications that utilize multimodal inputs, making AI more accessible and integrated into various aspects of daily life and work.

  • What are the presenter's thoughts on the future of open-source models in relation to GPT-4 Mini?

    -The presenter is excited about the potential of open-source models, such as those from Anthropic, to offer similar capabilities to GPT-4 Mini but at a lower cost, despite the potential hassle of hosting them.

Outlines

00:00

🤖 Introduction to Omni-Prompting with GPT 4.0 Mini

The speaker introduces the concept of 'omni-prompting,' which integrates text, vision, and voice inputs for AI models. They express excitement about the GPT 4.0 Mini's capabilities, especially its ability to handle multiple modalities in a single API call. The speaker also mentions the model's affordability, suggesting it makes advanced AI features more accessible. They demonstrate an application called 'Cognic Cast,' which uses GPT 4.0 Mini to analyze screenshots and provide responses to user queries.

05:03

🖼️ Utilizing Visual and Textual Inputs for Enhanced AI Interaction

This paragraph delves into the practical application of using both visual and textual prompts with AI, as exemplified by the speaker's experience with CLA 3.5. They discuss creating a React component and using images to expedite the development process, highlighting the efficiency gains from the integration of visual inputs. The speaker also anticipates the future integration of voice, which could further streamline interactions with AI models.

10:05

💡 Exploring the Potential of Low-Cost AI Models for Innovative Applications

The speaker explores the implications of the reduced cost of running AI models like GPT 4.0 Mini, suggesting it opens up new possibilities for app development. They showcase a screen-sharing app that can analyze and describe content on the user's screen, emphasizing the ease of customization and the potential for integrating voice commands. The speaker also mentions plans to share the app on GitHub and encourages viewers to join their community for access.

🌐 Sharing Resources for Omni-Prompting and Anticipating Future Developments

In the final paragraph, the speaker shares resources for those interested in trying out omni-prompting, directing viewers to their website for a demo. They also discuss the potential for integrating security measures and the flexibility of using low-cost AI models for various applications. The speaker expresses excitement about the future of AI, including the upcoming release of CLA 3.5 and open-source models, and thanks the audience for their support.

Mindmap

Keywords

💡Omni Prompting

Omni Prompting refers to the integration of multiple input types, such as text, vision, and voice, into a single AI model to generate responses. This concept is central to the video's theme, illustrating the potential for a more comprehensive and interactive AI experience. The script discusses the use of GPT-4.0 Mini to handle multimodal inputs, indicating the evolution of AI from text-based to more dynamic and inclusive of various sensory inputs.

💡GPT-4.0 Mini

GPT-4.0 Mini is a model mentioned in the script that is capable of processing text, image, and potentially voice inputs. It represents a shift towards more versatile AI applications, as it can understand and respond to a broader range of human communication methods. The script highlights its significance due to its ability to perform Omni Prompting at a low cost, making advanced AI capabilities more accessible.

💡API Call

An API (Application Programming Interface) call is a request made to an application's backend to perform a specific function. In the context of the video, the script describes how the GPT-4.0 Mini model can receive multimodal inputs through a single API call, streamlining the process of integrating AI into applications. This is showcased through the screen share app, which uses the API to analyze images and text.

💡Multimodality

Multimodality in AI refers to the ability of a system to process and understand multiple types of input data, such as text, images, and voice. The script emphasizes the importance of multimodality in enhancing AI's capabilities, as it allows for a more natural and human-like interaction with technology. The video discusses how GPT-4.0 Mini can handle text and image inputs, with the anticipation of voice integration.

💡Screen Share App

The screen share app is an application created by the video's author to demonstrate the capabilities of GPT-4.0 Mini. It allows users to capture and analyze screenshots of their computer screens using the AI model. This app exemplifies the practical application of Omni Prompting, as it leverages the AI's ability to process visual and text inputs to provide descriptions and summaries of on-screen content.

💡Cognicast

Cognicast is the name given to the screen share app in the script. It represents an innovative use of AI, where the app can analyze and provide insights into the content of a user's screen. The script describes how this app can be used to interact with the GPT-4.0 Mini model, showcasing the practical implementation of AI in everyday tasks.

💡Price of GPT-4.0 Mini

The price of GPT-4.0 Mini is a key point in the script, as it discusses the affordability of using this AI model for Omni Prompting. The author highlights the low cost per million tokens for both input and output, making it feasible for developers to integrate AI into their applications without incurring high expenses. This price point is crucial for the widespread adoption of AI technologies.

💡Output Token Window

The output token window refers to the maximum number of tokens that an AI model can generate in a single response. The script mentions that GPT-4.0 Mini has a larger output token window, which is beneficial for generating more detailed and comprehensive responses. This feature is important for applications that require extensive output, such as summarizing long documents or providing in-depth analysis.

💡Hyper Personal Assistant

A hyper personal assistant, as discussed in the script, is an AI system that is highly personalized and capable of understanding and responding to a user's needs in a very specific and tailored manner. The video suggests that the combination of text, image, and voice inputs in GPT-4.0 Mini could lead to the development of such assistants, providing a more intuitive and interactive user experience.

💡Open Model Versions

Open model versions refer to AI models that are publicly available and can be used by anyone, as opposed to proprietary models that are exclusive to a particular company or service. The script mentions that while there are open model versions of the AI technology discussed, they may not yet be as advanced as the GPT-4.0 Mini. However, the potential for these models to improve and become more accessible is highlighted.

💡Anthropic

Anthropic is a company or entity mentioned in the script that is expected to add voice capabilities to their AI models in the future. The anticipation of voice integration is part of the broader theme of enhancing AI's multimodal capabilities, which would allow for even more natural and human-like interactions with AI systems.

Highlights

Introduction of the concept of Omni Prompting with gpt-4o-mini, a new approach to AI software.

The release of gpt-4o-mini and its potential to revolutionize AI with its multimodal capabilities.

The importance of context in smaller AI models and the benefits of combining text, vision, and voice inputs.

Demonstration of creating an API call with text and image inputs using gpt-4o-mini.

The anticipation of voice integration into the model for a fully multimodal AI experience.

The economic feasibility of using gpt-4o-mini due to its low cost.

Introduction of the cognic cast app, a screen share application that integrates with gpt-4o-mini.

How the app can analyze screenshots and provide descriptions based on the image content.

The pricing structure of gpt-4o-mini and its affordability for developers.

The potential of gpt-4o-mini to serve as a hyper-personal assistant with screen share capabilities.

The integration of gpt-4o-mini with other open-source models for broader AI applications.

The creator's plan to share the screen share app on GitHub for community use.

The demonstration of the app's ability to monitor and analyze any selected window or full screen.

The future enhancement of the app with voice integration for hands-free operation.

The website AIS sv. Tech where users can test Omni prompting without access to gpt-4o-mini.

The ease of integrating Omni prompting into websites and the potential for custom security measures.

The lowering cost of large language model APIs and the opportunities it presents for innovation.

The anticipation of the release of CLA 3.5 and its potential impact on AI development.

The creator's excitement for the future of AI and the possibilities opened by the decreasing costs and advancements in technology.

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