OpenAI’s newly unveiled “Strawberry” model, officially known as OpenAI o1, is not just another AI—it’s a game-changer, designed to tackle some of the most complex challenges in coding, mathematics, and technical reasoning. But have you ever wondered what powers this leap forward? 🤔 We could only speculate, but being in this space, we can only fathom the amount of investment in creating data for training.

Training a model like Strawberry isn’t about feeding it more data; it’s about feeding it the right data. For example:

-Complex Coding Data: The model needs vast datasets from competitive programming platforms and real-world codebases. These datasets allow the model to learn intricate algorithms and improve its problem-solving capabilities in software development. Public Github can be a start, but not enough b/c it does not contain all the steps and contexts.

– Advanced Mathematical Data: High-level mathematical problems and solutions, such as those found in Olympiad competitions, provide the necessary challenges that enable the model to excel in reasoning and quantitative analysis.

– Explainability and Reasoning: Data that includes step-by-step explanations and annotated reasoning processes is essential to train models capable of this level of transparency.

– Human Feedback and Reinforcement Learning: Data generated from real-world interactions, where the model is tested and receives feedback.

At tbrain.ai, we understand the importance of this kind of specialized data. We’re committed to providing the high-quality, complex datasets needed to train cutting-edge AI models like Strawberry, and at the best cost available. 💡 Talk to us if you have a data need for your LLM!

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