o1-preview
An OpenAI model that performs internal reasoning before answering to solve complex problems in science, programming, and mathematics.
Overview
o1-preview
Description of the o1-preview neural network
o1-preview is a preview version of a new series of artificial intelligence models from OpenAI, released on September 12, 2024. The key feature of this model is that it spends additional time on internal reasoning before forming an answer. This approach allows o1-preview to analyze queries more deeply and solve tasks that require high precision and logical thinking.
Unlike previous generations of OpenAI models, o1-preview deliberately sacrifices speed in favor of quality and depth of analysis. This means that answers may take longer to generate, but their accuracy and soundness are significantly higher, especially in complex disciplines. At the same time, the model's chain of reasoning is not disclosed to the user — the company made this decision for security reasons and to maintain competitive advantages.
Architecture and training
The exact architectural details of o1-preview have not been disclosed. It is known that the model is based on a transformer, and training was carried out using new optimization algorithms and reinforcement learning methods. The training data was specifically selected to improve the model's reasoning abilities.
Access and integration
o1-preview is available through the OpenAI API and is also integrated into a number of products, including GitHub Copilot. In addition to the full version, there is a lightweight specialized version called o1-mini.
o1-preview specifications
| Characteristic | Value |
|---|---|
| Model name | o1-preview |
| Release date | September 12, 2024 |
| Developer | OpenAI |
| Architecture | Transformer (exact details not disclosed) |
| Number of parameters | Exact data not disclosed |
| Context window | Exact data not disclosed |
| Training data | Specially curated dataset to improve reasoning abilities |
| Input format | Text |
| Multimodal capabilities | None |
| Training method | New optimization algorithms and reinforcement learning |
| Access methods | Access via OpenAI API, integration into products (e.g., GitHub Copilot) |
| Specialized versions | o1-mini |
| Response speed | Slower compared to previous models due to the lengthy reasoning process |
| Energy consumption | High due to increased computation time |
Frequently asked questions
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