GPT-o1 vs GPT-4o: The SMARTEST AI Ever?
Introduction
OpenAI, the company behind ChatGPT, has recently released a new language model called GPT-o1. According to their claims, this model exceeds human PhD-level accuracy on benchmarks for physics, biology, and chemistry problems. GPT-o1 is particularly designed for advanced reasoning tasks, making it more adept at tackling complex questions compared to its predecessor, GPT-4o. In this article, we will delve into how GPT-o1 differs from GPT-4o, showcasing their respective strengths and providing a comparative analysis through a series of prompts.
Key Differences Between GPT-o1 and GPT-4o
The primary distinction between GPT-o1 and GPT-4o lies in their respective design and intended functionality. While GPT-4o is suited for everyday tasks such as summarizing emails, writing text, analyzing images, and generating random facts, GPT-o1 is calibrated for complex reasoning and problem-solving. OpenAI suggests various prompting strategies for each model, emphasizing different approaches based on the intended complexity of the queries.
For GPT-4o, prompts should adhere to a formula, such as the Goal-Context-Expectation (GCE) framework. Users can even assign roles to ChatGPT and set the tone to streamline responses. On the other hand, GPT-o1 thrives on simplicity; prompts should be kept direct and uncomplicated, with OpenAI advising against using "Chain of Thought" prompts.
To illustrate the differences, I compared responses from both models using identical prompts, focusing on various topics to highlight their performance.
Prompt 1: How many jobs will AI replace by 2030?
Upon prompting both models, we observed notable differences. GPT-o1 began by acknowledging its knowledge cut-off date of October 2023, which was not mentioned by GPT-4o. Both models addressed the potential job displacement and creation brought about by AI, citing similar sources. However, GPT-o1 offered additional nuance by referencing the years of the sources and elaborating on influential factors like technological advancements and economic conditions. Ultimately, GPT-o1 concluded that tens to hundreds of millions of jobs could be affected by AI.
Prompt 2: What’s the best approach to negotiating a raise and promotion?
In this exercise, both models were tasked with providing preparation steps for negotiating a raise and promotion. While the approaches were generally similar, GPT-o1 included more detailed advice, suggesting specific quantifiable achievements and their impact (e.g., reducing company costs by a certain amount). GPT-o1 offered a thorough exploration, making it slightly more beneficial for specific scenarios, though both models produced solid advice.
Prompt 3: I’m a farmer and a pig was just born on my farm. How should I record this in my accounting books?
The final prompt delved into a complex accounting scenario that required more nuanced reasoning. Here, GPT-o1 demonstrated its design for intricate problem-solving by engaging in a longer thought process—taking 16 seconds to produce its answer. It presented a more detailed inquiry, asking about fair value and accounting standards, which was absent from GPT-4o’s response. This highlights GPT-o1's capability to generate comprehensive answers in situations where multiple outcomes are possible, emphasizing its potential applications in specialized fields like accounting.
Conclusion
My initial assessments indicate that while GPT-4o and GPT-o1 are comparable for general inquiries, GPT-o1 stands out when addressing complex and multifaceted problems. The new model provides more detailed and nuanced responses, particularly in uncertain or variable contexts. Each model has distinctive advantages, depending on the nature of the question posed. Users must consider the complexity of their queries to determine which model to utilize effectively.
Keywords
GPT-o1, GPT-4o, OpenAI, language model, advanced reasoning, job replacement, negotiation, accounting, complex problems.
FAQ
Q1: What is GPT-o1, and how does it differ from GPT-4o?
A1: GPT-o1 is a newly released language model by OpenAI designed for advanced reasoning and complex problem-solving, while GPT-4o is more suited for general tasks like summarizing text and generating fun facts.
Q2: How should I prompt GPT-4o and GPT-o1?
A2: For GPT-4o, use a structured approach such as the Goal-Context-Expectation formula. In contrast, for GPT-o1, keep prompts simple and avoid complex instructions.
Q3: When should I use GPT-o1 over GPT-4o?
A3: Use GPT-o1 for complex problems requiring nuanced reasoning, while GPT-4o is recommended for general queries that don't require in-depth analysis.
Q4: Can GPT-o1 handle accounting questions?
A4: Yes, GPT-o1 has shown proficiency in providing detailed and nuanced answers to complex accounting scenarios.