The o1 model is a significant advancement in the language model technology, boasting a massive 175 billion parameters. This massive scale allows it to capture intricate details and nuances of human language, enabling it to generate more accurate and comprehensive responses. The o1 model’s accuracy and detail are further enhanced by its training process, which involves a vast dataset of text and code.
What is ChatGPT o1? here is o1, a series of our most capable and aligned models yet:https://t.co/yzZGNN8HvDo1 is still flawed, still limited, and it still seems more impressive on first use than it does after you spend more time with it. pic.twitter.com/Qs1HoSDOz1September 12, 2024 Currently, the new model is offered in two versions: o1-preview and o1-mini. Somewhat confusingly, it seems that o1-mini is the more powerful model, but with a smaller knowledge base. Reports indicate that o1-preview was trained on an earlier architecture than mini, and the full o1 is deemed too powerful to release without additional security protections and guardrails.
The model’s ability to understand and respond to complex prompts is impressive. It can handle nuanced questions, handle ambiguity, and even generate creative solutions. For example, I asked it to write a short story about a robot who falls in education. The model produced a compelling narrative with a clear plot, well-developed characters, and a thought-provoking message about the nature of learning.
One of my top tips is to use another AI model like GPT-4o or Sonnet 3.5 to refine your basic idea into a workable prompt for o1. This could involve having it outline each step the model needs to take or breaking down the problem into smaller components. In addition to improved performance and accuracy, o1 also boasts a significantly larger output window. This means it’s more capable of generating a full report, writing an entire codebase, or providing a detailed response to a complex query compared to other OpenAI models. 1. A plan to terraform Mars (Image credit: Midjourney/Future AI image)
This feature, known as “explainability,” is crucial for building trust and understanding in AI systems. Explainability allows users to understand the reasoning behind the AI’s decisions, fostering a sense of transparency and accountability. For instance, when using o1 for a creative writing task, the AI could explain why it chose a particular word or phrase, or why it decided to structure the story in a certain way.
I started with a prompt that asked the AI to create a new form of math that didn’t rely on numbers. The AI responded with a complex system of symbols and rules, which it claimed could be used to represent and manipulate abstract concepts. This system, which it called “Symbolic Mathematics,” was based on a combination of logic and geometry.
The summary provided does not contain any information about a specific system of government. It only mentions the shortcomings of current democratic, autocratic, and other existing systems. **Request:**
Please design a new system of government that addresses the major shortcomings of current democratic, autocratic, and other existing systems.
o1 is a highly skilled programmer and game developer. They are passionate about using technology to create engaging and educational experiences. o1’s expertise lies in developing dynamic participatory governance (DPG) systems, which are complex systems that allow for collaborative decision-making and problem-solving. o1’s work focuses on creating games and simulations that demonstrate DPG principles in action.
This led to the idea of using emojis to represent the reasoning process. This approach is particularly useful for understanding the reasoning behind a model’s decision. It allows users to see the model’s thought process in a more intuitive and visual way. For example, imagine a model is asked to explain why it chose a specific product.
I found that the models were very good at generating text, but they struggled with coming up with creative and original ideas. I think this is because the models are trained on a massive dataset of text and code, which can lead to a lack of novelty. This is similar to how a person who has read a lot of books might struggle to come up with a truly original story.
When OpenAI adds the ability to load data files this will be game-changing in the business space and could be used to organize the family vacation, working out all the different complexities of the trip including timings and schedules. Right now, with only 30 messages per week (I used half in a day), its a fun diversion but for most use cases GPT-4o is more than enough. In fact, GPT-04o mini is more than enough for how the vast majority of people use AI and Apple Intelligence is as good as that model.
