GPT 4o mini: The Game-Changing Model from OpenAI

Mervin Praison
18 Jul 202411:15

TLDRThe video introduces GPT 40 mini, a cost-effective AI model from OpenAI with superior accuracy and multimodal capabilities, allowing for the processing of extensive texts and images. It boasts a 128,000 token context length, making it suitable for real-time applications and AI agent integration. The script demonstrates its proficiency in coding, logical reasoning, and safety measures, highlighting its potential to revolutionize AI applications with its fast response times and competitive pricing.

Takeaways

  • πŸš€ GPT 40 mini is a new, cost-effective model from OpenAI, offering lower prices compared to GPT 3.5 Turbo and Google's Gerini Flash.
  • πŸ“š It boasts a 128,000 token context length, allowing it to process a full book or around 2,500 pages in one go.
  • πŸ–ΌοΈ As a multimodal model, GPT 40 mini can accept both text and visual inputs, enabling image-based inquiries.
  • ✍️ When tasked with writing a poem in a thousand words, GPT 40 mini demonstrates impressive speed of generation, suitable for real-time applications and chatbots.
  • πŸ”’ GPT 40 mini scores 82% on MLU and outperforms GPT-4 on chat preferences in LMC's leaderboard, showing high accuracy.
  • πŸ’° The cost for 1 million input tokens is significantly lower at 15 cents, compared to 35 cents for Gerini Flash, and 60 cents for output tokens.
  • πŸ”§ It excels in reasoning tasks, math, coding proficiency, and multimodal reasoning, making it a versatile tool for various applications.
  • πŸ”— GPT 40 mini uses the same tokenizer as GPT 4, which means it can handle non-English texts as well.
  • πŸ›‘οΈ The model refuses to assist with illegal activities, demonstrating a commitment to safety and ethical guidelines.
  • πŸ” In a test with a codebase, GPT 40 mini identifies errors and provides a general review, showing its capability in code analysis.
  • πŸ€– The model's strong function calling performance allows for integration with AI agents, as demonstrated by its use in a multi-agent workflow for research tasks.

Q & A

  • What is the name of the new model from OpenAI mentioned in the script?

    -The new model from OpenAI mentioned in the script is called GPT 40 mini.

  • How does GPT 40 mini compare in cost to other models such as GPD 3.5 turbo?

    -GPT 40 mini is cheaper than GPD 3.5 turbo, making it the most cost-effective model available from OpenAI.

  • What is the context length of GPT 40 mini in terms of tokens?

    -GPT 40 mini has a context length of 128,000 tokens, allowing it to process a full book of roughly 2,500 pages in one go.

  • What does being a multimodal model mean for GPT 40 mini?

    -Being a multimodal model means GPT 40 mini can accept both text and vision inputs, enabling it to process images and answer questions based on them.

  • How fast is the response generation speed of GPT 40 mini when writing a poem in a thousand words?

    -The response generation speed of GPT 40 mini is super fast, as demonstrated when it was asked to write a poem in a thousand words.

  • What are some of the tests that will be conducted to evaluate GPT 40 mini's capabilities?

    -The tests include programming tests, logical and reasoning tests, safety tests, needle and the Hast stack tests, and AI agents tests using Crew AI and Autogen.

  • What is the pricing for 1 million input tokens for GPT 40 mini compared to Google's Gerini Flash?

    -For 1 million input tokens, Gerini Flash costs 35 cents, while GPT 40 mini costs just 15 cents, which is less than half the price.

  • What is GPT 40 mini's performance like in terms of reasoning tasks and coding proficiency?

    -GPT 40 mini excels in reasoning tasks and is good at math and coding proficiency, making it suitable for complex problem-solving.

  • How does GPT 40 mini handle non-English texts?

    -GPT 40 mini uses the same tokenizer as GPT 4, which means it can handle non-English texts effectively.

  • What is the key feature of GPT 40 mini that makes it suitable for running AI agents?

    -One of the key features of GPT 40 mini is its strong performance in function calling, making it suitable for running AI agents that perform tasks collaboratively.

Outlines

00:00

πŸš€ Introduction to GPT 40 Mini: A Cost-Effective AI Model

The video introduces the GPT 40 Mini, a new AI model from Open AI that is positioned as the most affordable option available. It is compared favorably against other models like GPD 3.5 Turbo, Gini Flash, and Cloe HighQ in terms of accuracy and benchmark performance. The GPT 40 Mini is highlighted for its 128,000 tokens context length, allowing it to process a full book of approximately 2,500 pages in one go. It is also a multimodal model, capable of accepting both text and vision inputs, which opens up possibilities for developers to create AI applications at a low cost. The video promises to demonstrate the model's capabilities through various tests, including programming, logical reasoning, safety, and AI agents tests using the 'pris AI' tool.

05:01

πŸ” Testing GPT 40 Mini's Capabilities: Programming and Reasoning Challenges

The script details a series of tests conducted on the GPT 40 Mini to evaluate its programming and logical reasoning capabilities. The model is tasked with solving programming challenges of varying difficulty levels, from simple tasks like returning the sum of two numbers to more complex problems such as generating an identity matrix and finding the least common multiple. The model's responses are tested for accuracy, and the video demonstrates its ability to handle multiple questions simultaneously. The GPT 40 Mini also successfully passes a safety test by refusing to provide guidance on illegal activities. Additionally, the script mentions a 'needle in the Hast stack' test, which involves feeding the entire code base into the model and asking it to identify errors, showcasing its potential for code review and auditing.

10:03

πŸ› οΈ Integrating GPT 40 Mini with AI Agents and Autogen Framework

The final part of the script discusses the integration of GPT 40 Mini with AI agents and the Autogen framework. It describes the process of using the 'pris AI' tool to run crew AI and autogen, which involves creating agents that perform tasks in sequence, such as researching, writing, and editing. The script outlines the creation of a 'agents.yml' file and a 'tools.py' file, which contain the definitions for the agents and the internet search tool, respectively. The video demonstrates the rapid generation of research output on lung disease by the agents, showcasing the model's agentic behavior and its potential for real-time applications. The script concludes with instructions on how to integrate GPT 40 Mini into one's own application using an Open AI API key and encourages viewers to stay tuned for more videos on similar topics.

Mindmap

Keywords

πŸ’‘GPT 40 mini

GPT 40 mini refers to a hypothetical, cost-effective AI model from OpenAI, which is introduced in the video as a game-changer in the field of AI. It is described as being more affordable than its predecessors, such as GPT 3.5 Turbo. The model is highlighted for its ability to process large amounts of text, such as entire books, and multimodal inputs including text and images. This model is central to the video's theme of showcasing advancements in AI technology and its potential applications.

πŸ’‘Accuracy

Accuracy in the context of the video pertains to the precision and correctness of the GPT 40 mini model's responses when compared to other models like Gini Flash, HighQ, and GPT 3.5 Turbo. It is a critical aspect of AI models, as it determines their reliability and effectiveness in various tasks. The video emphasizes that GPT 40 mini outperforms its competitors in terms of accuracy, making it a preferred choice for developers.

πŸ’‘Tokens

In the script, 'tokens' refers to the units of text that an AI model can process at one time. The GPT 40 mini is said to have a context length of 128,000 tokens, which is a significant capacity that allows it to handle extensive inputs like full books. Understanding the concept of tokens is essential for grasping the capabilities of AI models in processing and generating text.

πŸ’‘Multimodal

The term 'multimodal' in the video script indicates the model's ability to process and understand multiple types of input data, such as text and images. This capability is significant as it expands the model's applicability to various scenarios where both textual and visual information is involved, enhancing its versatility and utility in AI applications.

πŸ’‘Real-time application

A real-time application, as mentioned in the video, is a software program that can process and respond to inputs instantly, without noticeable delay. The GPT 40 mini's speed in generating responses is highlighted, suggesting its suitability for creating real-time applications such as customer chatbots, where immediate and accurate responses are crucial.

πŸ’‘Programming test

The programming test in the video script is a series of challenges presented to the GPT 40 mini to evaluate its ability to write and understand code. The test includes tasks of varying difficulty levels, such as creating functions to return the sum of two numbers or generating an identity matrix. These tests demonstrate the model's proficiency in coding, which is a key aspect of its utility for developers.

πŸ’‘Logical reasoning

Logical reasoning is the ability to draw conclusions based on logical principles and evidence. In the video, the GPT 40 mini is tested on its logical reasoning capabilities through questions that require it to process information and provide correct answers. The model's performance in these tests showcases its ability to understand and apply logical principles effectively.

πŸ’‘Safety test

A safety test, as depicted in the video, is designed to evaluate the ethical boundaries and safety mechanisms of the AI model. The GPT 40 mini's refusal to provide guidance on illegal activities, such as breaking into a car, illustrates its adherence to safety protocols and its capacity to discern right from wrong in responses.

πŸ’‘Hast stack test

The Hast stack test in the video refers to a specific type of evaluation where the AI model is fed an entire code base and then asked to identify errors or provide insights based on that code. This test is meant to assess the model's ability to understand and analyze large volumes of code, which is a valuable skill for developers working with complex software projects.

πŸ’‘AI agents

AI agents in the context of the video are autonomous entities that perform tasks by interacting with each other and the environment. The script describes how the GPT 40 mini can be integrated with AI agents to perform complex tasks, such as researching and writing articles on specific topics. This demonstrates the model's potential for协作 and its ability to function within a network of AI-driven processes.

Highlights

Introduction of GPT 40 mini, a new and cost-effective model from OpenAI.

GPT 40 mini is cheaper than GPT 3.5 Turbo, offering better accuracy and performance in benchmarks.

The model supports a 128,000 tokens context length, allowing input of a full book for analysis.

Multimodal capabilities of GPT 40 mini, accepting both text and visual inputs.

GPT 40 mini's rapid response generation, ideal for real-time applications and chatbots.

Upcoming tests on programming, logical reasoning, safety, and AI agents using GPT 40 mini.

GPT 40 mini's performance on the mlu test, outperforming GPT-4 on chat preferences.

Cost comparison with Google's Gerini Flash, showing GPT 40 mini's price advantage.

GPT 40 mini's proficiency in reasoning, math, and coding tasks.

Demonstration of GPT 40 mini's multimodal reasoning with code base analysis.

GPT 40 mini's ability to handle full conversation history for real-time text responses.

The model's use of the same tokenizer as GPT 4, supporting non-English texts.

GPT 40 mini's strong performance in function calling, beneficial for AI agent operations.

Integration of GPT 40 mini with applications using the OpenAI API key.

Coding capability tests with GPT 40 mini, including Python challenges of varying difficulty.

Logical and reasoning tests, showcasing GPT 40 mini's ability to answer multiple questions accurately.

Safety test results, demonstrating GPT 40 mini's refusal to assist with illegal activities.

Needle in the Haystack test using GPT 40 mini to identify errors in a large codebase.

Performance of GPT 40 mini with AI agents, such as crew AI and autogen, for task automation.

Final thoughts on GPT 40 mini's game-changing capabilities at a low cost.

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