If you’re like me and keep a close eye on AI developments, then you’ve probably heard the recent buzz about OpenAI’s o1 model. Announced in September 2024, this new series represents a significant shift in how we think about AI, especially when it comes to tackling complex problems in fields like science, coding, and mathematics. Unlike the previous GPT-4 models, o1 isn’t just about language generation but focuses more on reasoning—it’s designed to think longer and more carefully about the answer before producing it, which is quite exciting.
Although I haven’t had the chance to try it out myself, I’ve been diving into what this model promises, and it seems to have the ability to handle more complex tasks.
Who Can Try the o1 Model?
At the moment, the o1 model is available to ChatGPT Plus and Team users, with Enterprise and Educational users getting access soon after. If you’re subscribed to ChatGPT Plus, you can already experiment with two versions of the model: o1-preview and o1-mini. The first one is the flagship model focused on solving particularly challenging tasks, while o1-mini is a more affordable and faster alternative, especially useful for coding-related tasks.
There are some limitations, though, such as message caps:
- 30 per week for o1-preview and
- 50 per week for o1-mini
but these are likely to change as OpenAI refines the model further.
When Will It Be Available for Everyone?
For now, the public can’t try o1 unless they’re paying for the Plus or Enterprise tiers. However, OpenAI has mentioned plans to eventually roll out access to ChatGPT Free users, especially the o1-mini version, which is both faster and cheaper. This might happen in the coming months, but there’s no fixed date yet. It’s something worth keeping an eye on it, if you would like to try it, but don’t want to pay for subscription just yet.
Videos Worth Watching
On OpenAI’s official o1 page, there are some videos that demonstrate the power and flexibility of this new model. Here are three that caught my attention:
HTML Snake Game
In this video, o1 helps create a classic snake game in HTML. It shows how the model can handle multi-step coding tasks efficiently. This is particularly interesting because it demonstrates o1’s ability to generate and debug code for developers quickly. Even if you’re not into game development, it’s worth watching to see how the model works through the logic step by step.
Solving a Complex Logic Puzzle
This video showcases o1’s reasoning abilities by tackling a complex logic puzzle. What’s fascinating here is how o1 constructs a detailed “chain of thought” before delivering its final answer. It gives you a peek into how the model breaks down intricate problems, something that GPT-4o wasn’t as strong in.
Quantum Physics Challenge
Ever wondered how an AI would handle quantum physics? In this video, o1 goes through the paces of generating complex mathematical formulas needed for quantum optics. This is where o1 really shines—its ability to deal with the sort of difficult, niche problems that you wouldn’t normally throw at an AI. Watching it process these advanced concepts makes it clear why OpenAI is touting this as a breakthrough model for science and research.
I’m curious about how this new model handles basic mathematical tasks, like counting letters in a word. The previous models were not too good at calculations, but if I ask GPT-4o to write a program for this task, it generates a well-functioning script.
The o1 seems to be able to do simple math operations that the GPT-4o couldn’t. 🙂
Why Try Out OpenAI o1? Is It Better Than GPT-4o?
So, what makes o1 worth trying? For one, the model is designed to spend a little more time thinking before it answers. This extra computational effort makes a huge difference in fields like math, physics, and even coding, where the ability to reason and understand the problem before generating an answer is crucial.
For example, o1 outperformed GPT-4o in solving math problems at the International Mathematics Olympiad, solving 83% of the problems compared to GPT-4o’s 13% success rate.
Moreover, o1 is highly specialized for tasks that require multi-step reasoning, like generating scientific hypotheses or debugging complex code. While GPT-4o is still useful for broader, more generalized tasks, o1’s ability to “think” deeply makes it an excellent choice for more technical challenges.
Despite these advantages, there are limitations:
- As an early model, o1 lacks some features that make GPT-4o practical for everyday use, such as browsing the web or handling files and images. So, depending on your needs, GPT-4o might still be the better choice for now if you’re aiming to use these capabilities.
- The operational costs of using the o1 model are significantly higher than those of GPT-4o, with input costs three times greater and output costs four times higher. Additionally, processing speed can be slower for complex queries.
Summary
While I haven’t personally tested OpenAI o1 yet, the early demonstrations and use cases suggest it’s a game-changer for anyone working in fields that require complex problem-solving. Whether you’re a researcher tackling quantum mechanics or a developer debugging code, o1 seems to have the potential to be much more than just a language model—it’s a tool for reasoning.
Right now, only those on ChatGPT Plus or higher tiers can test it out, but with plans to make it accessible to Free users, it’s something I’d recommend keeping on your radar.
