OpenAI GPT-4o | First Impressions and Some Testing + API

All About AI
13 May 202413:12

TLDRIn this video, the host shares their first impressions of OpenAI's GPT-40 model, highlighting its ability to reason across audio, vision, and text in real time. They discuss the model's low latency, which averages at 320 milliseconds, similar to human response times, and express excitement about the potential for this latency in a simple API call. The host also mentions the 50% reduction in API costs for GPT-40 and its enhanced capabilities in vision and audio understanding. They conduct a live test using the model to analyze images and provide structured explanations, demonstrating the model's strong performance. Additionally, they compare the speed and token processing between GPT-40 and GPT-4 Turbo, noting a significant improvement in speed with GPT-40. The video concludes with logical tests and a teaser for a follow-up video where they will delve deeper into GPT-40's features and capabilities.

Takeaways

  • 🚀 OpenAI has introduced GPT-40, a new flagship model capable of reasoning across audio, vision, and text in real-time.
  • 📈 GPT-40 is designed to have low latency, averaging around 320 milliseconds, which is comparable to human response times in conversation.
  • 💡 The model is said to be twice as fast and 50% cheaper than its predecessors, with improved capabilities in vision and audio understanding.
  • 📊 GPT-40 supports text or image input and outputs text, although audio input and output are not yet available for testing.
  • 🧐 The speaker is particularly interested in the potential for low-latency API calls, which could significantly enhance user interactions.
  • 📉 The model boasts a large context window of 128k tokens, suitable for most use cases.
  • 🎉 OpenAI plans to make GPT-40 available to all free users, which is a significant development in accessibility.
  • 📚 The speaker took notes during the live stream, noting features like voice input/output, emotion changes in voice, and tone adjustments.
  • 🖼️ A script was written to test the image functionality of GPT-40, analyzing images and providing structured explanations.
  • 📝 The model demonstrated the ability to perform calculations on images, such as verifying the Pythagorean theorem and calculating areas.
  • ⏱️ A comparison between GPT-40 and GPT-4 Turbo showed that GPT-40 is over five times faster in terms of tokens processed per second.
  • 🤔 GPT-40 and GPT-4 Turbo did not solve a logical problem correctly, whereas GPT-4 Turbo solved a different problem accurately.

Q & A

  • What is the main feature of the GPT-40 model discussed in the video?

    -The GPT-40 model is a new flagship model that can reason across audio, vision, and text in real time, with low latency similar to human response times.

  • What is the significance of the low latency in the GPT-40 model?

    -The low latency, averaging 320 milliseconds, is significant because it allows for more natural human-computer interaction and is comparable to human response times in conversation.

  • How does the GPT-40 model's API cost compare to existing models?

    -The GPT-40 model offers a 50% reduction in API cost compared to existing models.

  • What improvements does the GPT-40 model have over previous models in terms of vision and audio understanding?

    -The GPT-40 model is better at vision and audio understanding compared to existing models, although the exact improvements are not specified in the transcript.

  • What was the creator's first test of the GPT-40 model's capabilities?

    -The creator's first test was to use the image functionality of the GPT-40 model to analyze and get responses from images.

  • Why couldn't the creator test the audio capabilities of the GPT-40 model?

    -The creator couldn't test the audio capabilities because, according to the documentation, the model currently accepts text or images as input and outputs text, but audio input/output is not yet available.

  • What was the latency of the GPT-40 model during the tests?

    -The latency of the GPT-40 model during the tests was significantly lower than the GPT-4 Turbo, with a difference that made the GPT-40 model approximately five times faster.

  • What is the token context limit for the GPT-40 model?

    -The GPT-40 model has a token context limit of 128k tokens, which is considered sufficient for most use cases.

  • How did the GPT-40 model perform in the logical test involving the marble problem?

    -The GPT-40 model incorrectly stated that the marble would be on the floor of the microwave, whereas the correct answer was that the marble would remain on the table.

  • What was the result of the comparison between GPT-40 and GPT-4 Turbo in terms of speed and token count?

    -GPT-40 processed at a rate of 110 tokens per second, while GPT-4 Turbo processed at a rate of 20 tokens per second, making GPT-40 over five times faster in this test.

  • What is the creator's plan for further exploration of the GPT-40 model?

    -The creator plans to follow up with a video on GPT-40 on Wednesday after having more time to look into its capabilities and features.

Outlines

00:00

🚀 Introduction to GPT-40 and Its Features

The first paragraph introduces the viewer to a reaction video about OpenAI's Spring update and the release of their GPT-40 models. The speaker expresses excitement about the new model's capability to reason across audio, vision, and text in real time. They mention the model's low latency, which is comparable to human response times, and discuss the potential of this feature for their channel's focus on low-latency interactions. The paragraph also covers the 50% reduction in API cost for GPT-40 and its improved performance in vision and audio understanding. The speaker shares their anticipation for testing the model's image analysis capabilities and expresses a desire to try out the audio functionality, which is not yet available.

05:03

🖼️ Testing GPT-40's Image Analysis Capabilities

The second paragraph details the speaker's attempt to test GPT-40's image analysis functionality. They describe using a script to analyze images from previous videos and generate a structured response explaining the system. The speaker is impressed with the model's quick analysis and the detailed explanation provided for each image, showcasing the model's ability to understand and summarize complex information. They also compare the performance of GPT-40 with GPT-4 Turbo, noting a significant difference in speed and latency, with GPT-40 being over five times faster in processing tokens per second.

10:06

🧐 Logical Testing and Upcoming Follow-Up

The third paragraph involves the speaker conducting some logical tests with GPT-40 and comparing its performance with GPT-4 Turbo. They present a physics problem involving a marble and a cup, and a creative writing task to write sentences ending with the word 'apples'. The speaker notes that while GPT-40 did not solve the marble problem correctly, GPT-4 Turbo performed well in both tests. The paragraph concludes with the speaker's intention to follow up with a more in-depth video about GPT-40 on Wednesday, inviting viewers to share their thoughts in the comments and expressing enthusiasm about the potential of free access to GPT-40 for everyone.

Mindmap

Keywords

💡OpenAI GPT-4

OpenAI GPT-4 refers to the latest generation of language models developed by OpenAI, an AI research lab. The GPT-4 model is described as a flagship model capable of reasoning across audio, vision, and text in real-time. This represents a significant advancement in AI technology, as it suggests the model can process and understand different types of data simultaneously, which is crucial for more natural and human-like interactions with computers.

💡Low Latency

Low latency in the context of the video refers to the short delay or response time between a user's input and the AI's output. The video mentions an average latency of 320 milliseconds, which is comparable to human conversational response times. This is important because it allows for more seamless and interactive communication with AI systems, enhancing the user experience.

💡API Cost

API cost refers to the expenses incurred when using an Application Programming Interface (API) to access a particular service or data. The script mentions that the cost of using the GPT-4 API is 50% cheaper, making it more accessible for developers and businesses to integrate advanced AI capabilities into their applications.

💡Vision and Audio Understanding

Vision and audio understanding are the capabilities of an AI model to process and comprehend visual and auditory information. The GPT-4 model is highlighted for its improvements in these areas compared to previous models, which suggests that it can analyze and interpret images and sounds more effectively, contributing to a more comprehensive understanding in various applications.

💡Image Functionality

Image functionality in the context of the video refers to the AI's ability to analyze and interpret images. The script describes a test where the AI is fed images and expected to provide descriptions and explanations based on those images. This showcases the multimodal capabilities of the GPT-4 model, which can enhance its applications in fields that require visual data analysis.

💡Token Context

Token context refers to the number of tokens an AI model can process and understand within a single input. The GPT-4 model is said to have a context of 128k tokens, which is a significant increase from previous models. This larger context allows the model to handle more complex and longer inputs, improving its ability to understand and generate detailed responses.

💡Voice Input and Output

Voice input and output are features that allow an AI model to receive and respond to vocal commands or questions. The video script discusses the potential for real-time emotion adjustments in the voice output, which could make interactions with AI more engaging and personalized. However, the script notes that voice functionality was not available for testing at the time of recording.

💡Latency in Calculations

Latency in calculations refers to the time it takes for an AI model to perform and return the results of a computation. The video demonstrates a comparison between GPT-4 and GPT-4 Turbo, showing that GPT-4 is significantly faster in processing calculations, with a latency of 110 tokens per second versus 20 for GPT-4 Turbo. This speed improvement is crucial for real-time applications and user satisfaction.

💡Logical Testing

Logical testing involves presenting an AI model with problems that require logical reasoning to solve. The video script includes an example of a 'marble problem' to test the model's ability to understand and apply basic physical principles. Logical testing is important for evaluating the AI's capability to handle complex, real-world scenarios.

💡Free Users

Free users in the context of the video refers to individuals who can access and use the GPT-4 model without any cost. The script mentions that OpenAI plans to make GPT-4 available to all free users, which is a significant development as it implies that a wider audience can benefit from advanced AI capabilities, potentially leading to broader innovation and experimentation.

💡Paid Version

The paid version refers to the access or use of the GPT-4 model that requires financial payment, typically offering additional features, services, or capabilities beyond what is available to free users. The video script raises questions about what additional benefits or features might be available to those who choose to pay for access to GPT-4, suggesting that there may be tiered levels of service or functionality.

Highlights

OpenAI has released their GPT-40 models, introducing a new flagship model capable of reasoning across audio, vision, and text in real time.

The GPT-40 model is particularly exciting for its low latency response times, averaging 320 milliseconds, similar to human conversational response times.

The GPT-40 model is 50% cheaper in API cost and is notably better at vision and audio understanding compared to existing models.

A script was written to test the image functionality of GPT-40, demonstrating its ability to analyze and respond to image inputs.

GPT-40 is expected to be twice as fast and has a context of 128k tokens, suitable for most use cases.

During the live stream, voice input and output capabilities were showcased, including real-time emotion adjustments in the voice.

The GPT-40 model is set to be made available to all free users, which is a significant development in accessibility.

The model performed well in analyzing a series of images related to different AI architectures, providing a structured and comprehensive explanation.

A live test was conducted using GPT-40 to perform mathematical calculations on an image of a triangle, demonstrating its logical reasoning capabilities.

GPT-40 showed significantly lower latency and higher token processing speed when compared to GPT-4 Turbo, with over five times faster performance.

A logical test involving the placement of a marble in a cup was used to compare the problem-solving abilities of GPT-40 and GPT-4 Turbo.

GPT-40 successfully generated nine out of ten sentences ending with the word 'apples', showcasing its ability to follow instructions and generate content.

The video creator expresses excitement about the potential of GPT-40 and plans to conduct more in-depth testing and evaluation in the future.

The GPT-40 model's performance and features are considered strong, with the creator noting the importance of further exploration and practical use cases.

The video includes a comparison of GPT-40 with other models, highlighting the advancements in speed and cost-efficiency.

The creator discusses the potential impact of GPT-40 being available for free and the differences that might be observed in the paid version.

The video concludes with an invitation for viewers to share their thoughts on the GPT-40 model and its implications for the future of AI.

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