AI Evolution: Dissecting the Key Differences Between GPT-4 and GPT-3
GPT-4 Powers Unprecedented AI Capabilities, Which We'll Compare Against GPT-3
Artificial intelligence (AI) has been transformed by OpenAI's groundbreaking language models, the most recent of which is GPT-4. While GPT-4 has been available for companies for quite some time, it became generally available via API & ChatGPT Plus on March 14th, 2023.
How much better is GPT-4 compared to GPT-3? We’ll walk through their technical specs, and share screenshots comparing GPT-3 to GPT-4.
In that side-by-side comparison, we’ll show why Aaron Rodgers probably should have waited for GPT-4 before requesting a trade from the Green Bay Packers.
Technical Comparison: GPT-4 vs GPT-3
As you can see from the table, GPT-4 is far more powerful than GPT-3. Boasting 1,000x the parameters of GPT-3, and 300x the training data.
Parameters are the weights and biases in a network that help determine a model’s output. They’re adjusted and fine-tuned during the training process to minimize errors and improve the model’s performance.
We could write an article on parameters alone. Simply put, more parameters help models capture more complex language patterns, generalize new tasks better, and deliver improved accuracy and performance.
More parameters require more computational resources, which explains why GPT-4 is only available for the paid version of ChatGPT. As of this writing, GPT-4’s API costs 30x GPT-3.5.
GPT-4: $0.06 / 1K tokens
GPT-3.5: $0.002 / 1K tokens
Training Data: Enhanced Understanding and Responsiveness
Both GPT-3 and GPT-4 rely on large datasets for training. As the prior table shows, GPT-4 has a far more extensive and diverse dataset, with 175 trillion words, compared to GPT-3’s 570 billion.
This helps GPT-4 have a better understanding of current events, emerging technologies, and the evolving cultural landscape.
GPT-4’s Enhanced Capabilities
What can you do with 1,000x the parameters and 300x the training data of GPT-3?
While GPT-3 was already capable of generating human-like text, GPT-4 has made significant strides in language understanding and context awareness.
Additionally, GPT-4 demonstrates a deeper comprehension of complex topics, responds to prompts more accurately, and generates content with increased coherence. We’ll share some examples in the next section.
Enhanced zero-shot and few-shot learning
GPT-4 is better at learning from limited examples, enabling superior performance in a variety of tasks with minimal training data.
Improved context awareness
GPT-4 demonstrates a deeper understanding of context, allowing it to generate more coherent and accurate responses to prompts.
This also helps GPT-4 handle more complex instructions, and answer questions more accurately.
More advanced code generation
GPT-4's improved understanding of programming languages results in more accurate and useful code snippets.
Finer-grained language modeling
GPT-4 can generate content with more nuanced language and style, providing higher-quality text outputs.
Better handling of long-form content
GPT-4's enhanced architecture maintains coherence and context better over longer text passages, improving its performance in tasks such as summarization and long-form content generation.
Improved multilingual capabilities
GPT-4 offers more accurate translations and better understanding of a wider range of languages.
Advanced reinforcement learning
GPT-4's enhanced learning capabilities help it excel in complex reinforcement learning tasks, making it more adaptable to various applications.
As you can see, GPT-4 mostly expands on GPT-3's capabilities, rather than introducing entirely new functions. Below shows what those enhanced capabilities look like.
GPT-4 vs. GPT-3 Side by Side
Let’s show GPT-4’s enhanced capabilities. Here are some prompts in ChatGPT, with GPT-3.5’s Legacy response, followed up by GPT-4’s response.
Prompt: Imagine you are quarterback Aaron Rodgers, who plays for the Green Bay Packers. You decided that you would like to play for a new team, but are still under contract with the Packers. Please develop a strategy that forces the Green Bay Packers to trade you to the team of your choice, while leaving the Green Bay Packers and their fans on good terms.
GPT-3.5
GPT-4: Please note, this plan could actually work
Prompt: Can you summarize the book “Apocalypse Never: Why Environmental Alarmism Hurts Us All” by Michael Shellenberger
GPT-3.5
GPT-4
Prompt: Please help me brainstorm gift ideas for my son's 3rd birthday. He loves dinosaurs.
GPT-3.5
GPT-4
Hopefully you see the differences, which the Aaron Rodgers scenario clearly highlights. GPT-4 has a plan and strategy that could actually work, whereas the legacy plan would have been as successful as the Titanic’s first voyage.
Additional GPT-4 Use Cases
GPT-4's enhanced performance has expanded OpenAI’s potential applications across various industries, including:
Content creation: GPT-4 can generate high-quality content for blogs, social media, and other platforms, saving time and resources for human writers.
Chatbots and virtual assistants: GPT-4's enhanced understanding helps it hold more nuanced and coherent conversations, improving user experience.
Translation: GPT-4's multilingual capabilities enable more accurate translations in a multitude of languages.
Code generation: GPT-4 can understand and generate code snippets more accurately, benefiting developers and the software industry.
While GPT-4 represents a significant leap forward in artificial intelligence, it mostly expands on GPT-3's capabilities, rather than introducing entirely new functions.
Those enhanced capabilities are significant, as the side by side comparisons show. GPT-4 is more thoughtful and nuanced, and can handle something as complicated as being a hall of fame quarterback who would like to move on while maintaining a positive relationship with their fanbase.