In the rapidly evolving world of artificial intelligence, OpenAI has consistently been at the forefront, pushing the boundaries of what’s possible with its state-of-the-art models. The company’s mission to ensure that artificial general intelligence benefits all of humanity has led to the development of some of the most advanced AI models in the world. This article introduces OpenAI’s latest models: GPT-4o and GPT-4 Turbo. These models represent a significant leap forward in AI technology, offering more efficient, cost-effective, and versatile solutions for various applications.
OpenAI is an AI research and deployment company. Its mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. OpenAI is committed to long-term safety, technical leadership, and a cooperative orientation. It aims to build safe and beneficial AGI directly but is also committed to aiding others in achieving this outcome.
Latest OpenAI Model
GPT-4o
GPT-4 Turbo
GPT-4o: The New Flagship Model
GPT-4o, where “o” stands for “Omni”, is the latest flagship model from OpenAI. It was announced on May 13, 2024. A flagship model is used across various industries, including technology, automotive, and more. It refers to the most prominent or highly touted product in a company’s product line.
Here are some key features of GPT-4o:
Multimodal Capabilities: GPT-4o is a multimodal model that can handle multiple data inputs and outputs, including text, audio, and images.
Performance: GPT-4o offers GPT-4 level performance but is much more efficient. It generates text 2x faster and is 50% cheaper.
Improved Capabilities: GPT-4o has improved capabilities across text, voice, and vision. It is much better than any existing model at understanding and discussing the images you share.
Language Support: GPT-4o’s language capabilities are improved across quality and speed.
Availability: GPT-4o is available in the OpenAI API to paying customers.
For example, you can now take a picture of a menu in a different language and talk to GPT-4o to translate it, learn about the food’s history and significance, and get recommendations. In the future, improvements will allow for more natural, real-time voice conversation and the ability to converse with ChatGPT via real-time video.
Use Cases:
Interacting and Singing: Two GPT-4os can interact and sing together.
Interview Preparation: It can help users prepare for interviews by providing relevant questions and answers.
Games: It can play games like Rock Paper Scissors.
Sarcasm: It can understand and generate sarcastic responses.
Math Tutoring: It can help with math problems.
Language Learning: It can help users learn new languages.
Real-time Translation: It can translate languages in real-time.
Coding: It can be used for coding tasks for developers looking to improvise on their personal and industrial projects.
Pricing:
Input Tokens: $5 per million input tokens.
Output Tokens: $15 per million output tokens.
GPT-4 Turbo: The Efficient and Affordable Model
GPT-4 Turbo is a large multimodal model developed by OpenAI. It was launched in November 2023. Here are some key features of GPT-4 Turbo:
Multimodal Capabilities: GPT-4 Turbo can handle multiple data inputs and outputs, including text and images.
Performance: GPT-4 Turbo is more capable, has an updated knowledge cutoff of April 2023, and introduces a 128k context window (the equivalent of 300 pages of text in a single prompt). The model is also 3X cheaper for input tokens and 2X cheaper for output tokens than the original GPT-4 mode.
Use Cases: GPT-4 Turbo is optimized for chat and works well for traditional completion tasks. It can analyze images and provide textual responses to questions about them.
Use Cases:
Summarizing Documents: It can summarize long documents and papers.
Question Answering: It can answer questions using large reference documents.
Chatbots and Assistants: It can be used to develop natural language chatbots and assistants.
Sentiment Analysis: It can classify sentiment from extensive customer feedback.
Legal and Financial Document Parsing: It can parse legal contracts or financial documents.
Content Creation: It has been deployed in content creation.
Customer Service Bots: It can be used in customer service bots.
Coding and Technical Writing: It can assist in coding and technical writing.
Pricing:
Prompt Tokens: $10 per million prompt tokens (or $0.01 per 1K prompt tokens).
Sampled Tokens: $30 per million sampled tokens (or $0.03 per 1K sampled tokens).
How to access these models?
Accessing GPT-4o and GPT-4 Turbo models involves the following steps:
OpenAI API Account: You need to have an OpenAI API account.
Payment: Make a successful payment of $5 or more (usage tier 1).
Access Models: After the payment, you can access the GPT-4, GPT-4 Turbo, and GPT-4o models via the OpenAI API.
For GPT-4o, it will be available in ChatGPT Free, Plus, Team, and Enterprise, and in the Chat Completions API, Assistants API, and Batch API. You can also get started via the Playground.
For GPT-4 Turbo, anyone with an OpenAI API account and existing GPT-4 access can use this model. The most recent version of the model can be accessed by passing gpt-4-turbo as the model name in the API.
Exploring the Capabilities of GPT-4o and GPT-4 Turbo
Feature | GPT-4o | GPT-4 Turbo |
|---|---|---|
Launch date | May 13, 2024 | November 2023 |
Modalities | Text, Audio, Vision | Text, Image |
Latency | Lower than GPT-4 Turbo | Higher than GPT-4o |
Throughput | 109 tokens per second | 20 tokens per second |
Performance in Non-English Languages | Better | Not Specified |
Cost | 50% cheaper than GPT-4 Turbo | More expensive than GPT-4o |
Rate Limits | 5x higher | Lower than GPT-4o |
Vision and Audio Understanding | Better | Not Specified |
GPT-4o is a multimodal model, with a single neural network trained end-to-end across text, audio, and visual data. On the other hand, GPT-4 Turbo follows the traditional transformer-based architecture, optimized for text processing.
Despite their impressive capabilities, GPT-4o and GPT-4 Turbo have some limitations and areas that could be improved:
Complex Data Extraction Tasks: For complex data extraction tasks, where accuracy is key, both models still fall short of the mark.
Classification of Customer Tickets: While GPT-4o has the best precision compared to GPT-4 Turbo when classifying customer tickets, there’s still room for improvement.
Reasoning Tasks: GPT-4o has improved calendar calculations, time and angle calculations, and antonym identification. However, it struggles with word manipulation, pattern recognition, analogy reasoning, and spatial reasoning.
Latency Issues: Some users have reported latency issues with GPT-4o.
Logical Consistency and Factual Accuracy: While improved, logical consistency and factual accuracy are still limited compared to human capabilities.
Nonsensical Outputs: Due to being optimized for engagement, outputs can sometimes be meaningless or hallucinated.
How can I choose between GPT-4o and GPT-4 Turbo for my Project?
Choosing between GPT-4o and GPT-4 Turbo for your project depends on several factors:
Project Requirements: If your project involves processing and understanding audio and visual data in addition to text, GPT-4o would be a better choice as it can reason across audio, vision, and text. On the other hand, if your project primarily involves text and image processing, GPT-4 Turbo could be sufficient.
Performance: GPT-4o has a faster response time and higher throughput than GPT-4 Turbo. If your project requires real-time responses, GPT-4o might be more suitable.
Cost: GPT-4o is 50% cheaper than GPT-4 Turbo. If cost is a major consideration for your project, GPT-4o could be a more economical choice.
Language Support: GPT-4o improves performance on non-English languages compared to GPT-4 Turbo. If your project involves processing non-English languages, GPT-4o might be a better choice.
Rate Limits: GPT-4o has 5x higher rate limits than GPT-4 Turbo. If your project involves making many API calls, GPT-4o could be more suitable.
Conclusion
The introduction of GPT-4o and GPT-4 Turbo by OpenAI marks a significant milestone in artificial intelligence. With their advanced capabilities and improved efficiency, these models push the boundaries of what AI can achieve.
The impact of these models on AI development is profound. They have expanded the scope of handling AI tasks, from real-time translation to customer service. Their ability to reason across different modalities - text, audio, and vision - opens up potential applications. These could range from enhancing accessibility services and improving customer interaction experiences to powering next-generation AI-driven applications.
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