Key insights

• ⚙️ OpenAI's new reasoning model, o1, is designed for complex tasks and uses reasoning tokens for thinking before responding.
• 💸 The pricing for the o1 model is $15 per million tokens for the preview version and $3 for the mini version.
• 👩‍💻 Developers can start prototyping with the API, which has a rate limit of 20 requests per minute for tier five users.
• 🎮 Setting up OpenAI model o1 on Cursor for testing and building a space game using NextJS involves selecting and testing models, creating game assets, defining game instructions, and running the code with the initial model.
• 🛠️ Struggling with coding errors and testing a space game using the o1 preview model, comparing it with CLA 3.5, and transitioning to building a system for fetching Bitcoin prices and testing trading algorithms.
• 📊 Comparing CLA 3.5 with o1 preview for trading strategies setup, finding CLA 3.5 easier to set up and yielding better results than o1 preview.
• 🌟 Encountering challenges with a new modeling approach, preferring the previous CLA 3.5 model over o1, but still eager to explore and effectively utilize the new reasoning model in the future.

Q&A

• What challenges did the speaker encounter when trying a new modeling approach?

  The speaker encountered challenges with the strategies in the new modeling approach, preferred the previous model (CLA 3.5) as it was found to be more reliable, and plans to explore and understand the new reasoning model for better use. The speaker remains excited about the potential of the new reasoning model and is eager to experiment further.

• How did the CLA 3.5 model compare with the o1 preview model for trading strategies setup?

  CLA 3.5 was easy to set up and yielded good results, while the o1 preview setup was slower and the instructions were not as clear. CLA 3.5 outperformed the o1 preview in terms of ease of setup and results.

• What issues were encountered when testing the game on the o1 models?

  Issues with score update, controls, and game functionality were encountered when the game was tested on the o1 mini and o1 preview models. Slow response time was experienced specifically on the o1 preview model.

• What does the process of setting up the o1 model on Cursor involve?

  The process includes selecting and testing the o1 model, creating game assets, defining game instructions, and running the code with the initial model for evaluation.

• What is the rate limit for tier five users when using the o1 reasoning model API?

  The API for the o1 reasoning model has a rate limit of 20 requests per minute for tier five users.

• What is the pricing for the o1 reasoning model?

  The o1 reasoning model is priced at $15 per million tokens for the preview version and $3 for the mini version.

• 00:00 OpenAI has released a new reasoning model, o1, designed to think before responding and solve complex tasks. The model uses reasoning tokens, can produce long chains of thought, and is priced at $15 per million tokens for the preview version. Developers can start prototyping with the API, which has a rate limit of 20 requests per minute for tier five users.
• 05:02 Setting up OpenAI model on Cursor and testing its application to build a space game using nextjs and 01 models. The process involves selecting and testing models, creating the game assets, defining game instructions, and running the code with the initial model.
• 09:45 A developer updates their game to add the option for the player to restart the game if they collide with an asteroid. They encounter issues with the game's functionality and performance while testing it on different models.
• 15:16 Struggling with fixing coding errors and testing a space game using 01 preview, comparison with claw 3.5, moving on to building a system for fetching Bitcoin prices and testing trading algorithms.
• 20:21 Comparing model CLA 3.5 with 01 preview for trading strategies setup. CLA 3.5 was easy to set up and yielded good results. 01 preview setup was slower and the instructions were not as clear. CLA 3.5 outperformed 01 preview in terms of ease of setup and results.
• 25:42 The speaker tries a new modeling approach but encounters challenges with the strategies, prefers the previous model, and plans to explore further. However, the speaker remains excited and looks forward to using the new reasoning model more effectively in the future.