Unveiling the Power of GPT 4 Turbo: What's New?

Table of Contents

1. Introduction
2. Open AI Dev Day Announcements
3. GPT-4 Turbo
4. Pricing Changes for GPT-4 Turbo
5. Improved Function Calling and Reproducible Outputs
6. GPT-3.5 Turbo
7. Assistant API
8. Examples of GPT Applications
9. How to Build a GPT
10. Conclusion

Introduction

Welcome to the SI Podcast! In today's episode, we will be discussing the highlights of Open AI Dev Day. This event focuses on the latest advancements in AI and its implications for business. Join us as we dive into the key announcements and updates presented during this event. Whether You're an AI enthusiast, developer, or simply curious about the future of technology, this episode is one you won't want to miss. So, sit back, relax, and let's explore the exciting world of Open AI.

Open AI Dev Day Announcements

Open AI Dev Day was an event filled with groundbreaking announcements. In this section, we'll cover some of the most significant updates shared during the event.

GPT-4 Turbo

One of the highlights of Open AI Dev Day was the introduction of GPT-4 Turbo, Open AI's most advanced model to date. This model offers an impressive 128k Context window and knowledge of world events up to April 2023. With a context window larger than ever before, GPT-4 Turbo provides developers and users with unparalleled capabilities. The ability to process such vast amounts of information opens up new opportunities for natural language processing and understanding.

Pricing Changes for GPT-4 Turbo

Open AI also announced considerable pricing changes for GPT-4 Turbo. Input tokens are now priced at just 1 cent per thousand, while output tokens cost only 3 cents per thousand. This reduction in pricing makes GPT-4 Turbo significantly more affordable, making its advanced features and reasoning abilities accessible to a wider range of applications and industries. The continuous decrease in pricing showcases Open AI's commitment to driving innovation and making AI more accessible to businesses and individuals alike.

Improved Function Calling and Reproducible Outputs

Open AI has made significant improvements to function calling with the introduction of the ability to call multiple functions in a single message. This enhancement streamlines the interaction between the model and developers, allowing for more efficient and effective communication. Additionally, the accuracy of returning the right function parameters has been improved, ensuring more precise results.

The new reproducible outputs beta feature offers greater control over the deterministic nature of model outputs. While chat completions are non-deterministic by default, Open AI provides developers with tools to achieve deterministic outputs by utilizing the seed parameter and system fingerprint field. These features enable developers to receive consistent outputs across API calls, maintaining control over the quality and reliability of the model's responses.

GPT-3.5 Turbo

Adding to the advancements, Open AI introduced GPT-3.5 Turbo during Dev Day. This new model supports a 16k context by default, offering four times more context than previous versions. This increase in context capabilities comes at a lower price, with input tokens priced at 0.1 cents per thousand and output tokens at 0.06 cents per thousand. The significantly reduced input token prices make fine-tuning of the 16k model much more accessible and cost-effective.

GPT-3.5 Turbo also benefits from improved function calling and reproducible outputs, aligning its capabilities with those of GPT-4 Turbo. Open AI's commitment to enhancing the developer experience is evident, as they consistently work to refine and improve their models and functionalities.

Assistant API

Another exciting announcement during Open AI Dev Day was the beta release of the Assistant API. Designed to help developers build agent-like experiences in applications, this API opens up a world of possibilities for creating purpose-built AI assistants. The Assistant API enables these assistants to follow specific instructions, leverage additional knowledge, and Interact with various models and tools to perform a wide range of tasks.

Through persistent Threads and context management, developers can HAND off thread state management to Open AI, allowing for seamless continuation of conversational experiences. Furthermore, new tools like code interpreter retrieval and function calling enhance the capabilities of these AI assistants, fostering versatility and flexibility in their functionality.

Examples of GPT Applications

Open AI provided several examples of real-world applications utilizing GPT models. These examples highlight the potential of AI assistants and how they can enhance various tasks and industries.

For instance, Code.org leverages GPT to enhance its computer science curriculum used by millions of students worldwide. By using GPT, Code.org created a lesson planner that helps teachers provide engaging experiences for middle school students. Through interactive Q&A Sessions using video game characters, GPT makes learning coding concepts more accessible and enjoyable.

Canva, a leading graphic design platform, has built a GPT that allows users to start designing by describing their desired outcome in natural language. This integration enables users to effortlessly generate design options Based on their descriptions, providing a more intuitive and efficient design experience.

Zapier, a popular integration platform, utilizes GPT to enable users to perform actions across thousands of applications. The GPT-powered integration opens up a wide array of automation possibilities, allowing users to leverage the power of AI to streamline their workflows and increase productivity.

These examples illustrate the versatility and applicability of GPT models in various domains. The possibilities for creating innovative and intelligent applications are virtually endless.

How to Build a GPT

Open AI has made building GPT models more accessible and user-friendly. During Open AI Dev Day, they showcased the GPT Builder, a tool that guides users through the process of creating their own customized GPT. The GPT Builder simplifies the development process and eliminates the need for extensive coding knowledge.

By providing instructions and allowing customization options, the GPT Builder enables users to define the purpose and functionality of their GPT. Users can upload specific documents or transcripts to train the model, making it highly tailored to their unique requirements.

The GPT Builder also provides configuration options, such as enabling custom actions and defining response parameters. Through a user-friendly interface, developers can Create and fine-tune their GPT models with ease.

Conclusion

Open AI Dev Day showcased the latest advancements in AI and their practical applications in business and everyday life. With the introduction of GPT-4 Turbo, improved function calling, reproducible outputs, and the Assistant API, Open AI continues to push the boundaries of what AI can achieve.

The reduced pricing for GPT models further democratizes access to powerful AI capabilities, making them more affordable and accessible to developers and businesses of all sizes.

The examples demonstrated during the event highlight the vast potential of GPT models across various industries. Whether it's enhancing educational experiences, automating workflows, or providing intelligent design assistance, GPT models prove to be invaluable tools for improving efficiency and innovation.

As Open AI continues to refine and develop their GPT models, the future of AI looks brighter than ever before. The possibilities are boundless, and we eagerly anticipate the groundbreaking applications that developers and innovators will create using Open AI's technology.

So, that's all for this episode covering the Open AI Dev Day highlights. Stay tuned for more exciting updates in the world of AI, and don't forget to like and subscribe to our podcast. See you next time!

Highlights

• Open AI Dev Day showcased groundbreaking advancements in AI.
• GPT-4 Turbo offers a massive 128k context window and knowledge of world events up to April 2023.
• Pricing for GPT-4 Turbo has been significantly reduced, making it more affordable for developers.
• Improved function calling and reproducible outputs enhance the precision and control of model outputs.
• GPT-3.5 Turbo provides a 16k context by default at a lower price point, making it more accessible for fine-tuning.
• The Assistant API enables developers to build agent-like experiences in their applications effortlessly.
• Real-world examples demonstrate the versatility and value of GPT models in various domains.
• The GPT Builder simplifies the process of building customized GPT models without extensive coding knowledge.

FAQ

Q: What is GPT-4 Turbo?
A: GPT-4 Turbo is Open AI's most advanced model, offering a 128k context window and knowledge of world events up to April 2023. It provides unparalleled capabilities for natural language processing and understanding.

Q: What are the pricing changes for GPT-4 Turbo?
A: Open AI has significantly reduced the pricing for GPT-4 Turbo. Input tokens now cost 1 cent per thousand, while output tokens are priced at 3 cents per thousand, making it more affordable for developers and businesses.

Q: What are reproducible outputs in GPT models?
A: Reproducible outputs refer to Open AI's beta feature that allows developers to achieve deterministic outputs in chat completions. While chat completions are non-deterministic by default, developers can use the seed parameter and system fingerprint field to receive mostly deterministic outputs across API calls.

Q: What is the Assistant API?
A: The Assistant API is a beta release by Open AI that enables developers to build AI assistants with specific instructions, additional knowledge, and interaction with models and tools. It offers capabilities such as persistent threads, context management, code interpreter retrieval, and function calling.

Q: How can I build my own GPT model?
A: Open AI provides the GPT Builder, a user-friendly tool that guides users through the process of building customized GPT models. Users can define the purpose, upload specific documents or transcripts, and configure the model's functionality.

Q: Are GPT models suitable for educational purposes?
A: Yes, GPT models have proven to be valuable for enhancing educational experiences. Code.org, for example, leverages GPT to enhance its computer science curriculum, while Canva uses GPT for natural language-based design assistance. These applications demonstrate the potential of GPT models in the educational domain.