We are thrilled to introduce the latest advancements in AI with the o1-mini model on Azure OpenAI Service. This new model is a game-changer, bringing enhanced reasoning capabilities that are particularly useful for tackling complex problems in various fields such as science, coding, and math.
What is the o1-mini Model?
The o1-mini model is adept at complex reasoning tasks, representing a significant advancement in AI capabilities. It can be used by healthcare researchers to annotate cell sequencing data, by physicists to generate complicated mathematical formulas needed for quantum optics, and by developers in all fields to build and execute multi-step workflows.
Introducing Reinforcement Fine-Tuning
Reinforcement Fine-Tuning (RFT) is a new model customization technique that enables developers to customize our models using dozens to thousands of high-quality tasks. By grading the model’s responses with provided reference answers, this technique reinforces how the model reasons through similar problems and improves its accuracy on specific tasks in that domain.
How Does RFT Work?
Graders play a crucial role in RFT by evaluating the responses during training. The grader compares the response generated by the model with the correct answer and gives a score from 0 to 1. This helps the model to reason better and improve its accuracy over time. Unlike Supervised Fine-Tuning (SFT), where the model is given the prompt and the completion at one go, RFT involves defining the graders and helping the model arrive at the logic behind choosing the answer with every new example.
Real-World Applications of RFT with o1-mini -
Reinforcement Fine-Tuning (RFT) unlocks the potential of the o1-mini model to address highly specialized and complex tasks across industries, delivering superior accuracy and domain-specific insights.
- Healthcare: Researchers can fine-tune the o1-mini model using RFT to annotate cell sequencing data with exceptional precision. By leveraging high-quality, graded annotations, the model learns to deliver more reliable and insightful outputs, accelerating breakthroughs in genomics and personalized medicine.
- Physics: Physicists can customize the o1-mini model to generate intricate mathematical formulas for quantum optics. With RFT, the model refines its ability to handle nuanced calculations, empowering researchers to address the most challenging problems in their field.
These tailored fine-tuning processes highlight the flexibility and power of the o1-mini model when equipped with RFT, enabling domain experts to achieve transformative results.
Region Availability
The o1-mini RFT is supported in North Central US and Sweden Central. Initially, it will be a code-first experience, with a user interface to follow later on.
Example: Base Model vs. Reinforcement Fine-Tuned Model
To demonstrate the effectiveness of RFT, we compared the results of the base o1-mini model with the reinforcement fine-tuned o1-mini model on a small dataset.
- Accuracy of Responses: This measures if the model gives out accurate response for a given question/ prompt which is not part of training dataset.
Prompt -
Which of the following will not decrease mother to child transmission of HIV?
A. Avoid breastfeeding
B. Vaginal delivery
C. Zidovudine given to mother antenatally and to neonate after birth
D. Vitamin A supplementation given to mother
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Base model (o1-mini ) |
Reinforcement Fine tuned model ( o1-mini ) |
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The correct answer is: **D. Vitamin A supplementation given to mother** **Explanation:** To determine which option **does not** decrease mother-to-child transmission (MTCT) of HIV, let's evaluate each choice: - **A. Avoid breastfeeding** **Decreases MTCT.** Breastfeeding can transmit HIV from mother to child through breast milk. Avoiding breastfeeding reduces the risk of transmission, especially when safe and feasible alternatives (like formula feeding) are available. - **B. Vaginal delivery** **Potentially Increases MTCT.** Vaginal delivery is associated with a higher risk of HIV transmission compared to a scheduled cesarean section (C-section) performed before the onset of labor and rupture of membranes. Therefore, opting for a vaginal delivery **does not** decrease MTCT and may actually increase the risk compared to a C-section. - **C. Zidovudine given to mother antenatally and to neonate after birth** **Decreases MTCT.** Zidovudine (AZT) is an antiretroviral medication that has been proven to reduce the risk of HIV transmission from mother to child when administered during pregnancy and to the newborn after birth. - **D. Vitamin A supplementation given to mother** **Does Not Affect MTCT.** While Vitamin A is important for overall health and immune function, it is **not** a recognized or effective intervention for reducing the transmission of HIV from mother to child. There is no substantial evidence supporting Vitamin A supplementation as a method to prevent MTCT of HIV. **Conclusion:** - **Option D** (**Vitamin A supplementation given to mother**) does **not** decrease mother-to-child transmission of HIV.
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B
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- Conciseness of responses: To measure along with accuracy, finetuned model is better in giving crisp responses which results in Lower number of input and output tokens.
Prompt:
Which of the following is not true for myelinated nerve fibers?
A. Impulse through myelinated fibers is slower than non-myelinated fibers
B. Membrane currents are generated at nodes of Ranvier
C. Saltatory conduction of impulses is seen
D. Local anesthesia is effective only when the nerve is not covered by myelin sheath
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Base model (o1-mini ) |
Reinforcement Fine tuned model ( o1-mini ) |
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The correct answer is: **A. Impulse through myelinated fibers is slower than non-myelinated fibers** **Explanation:** - **A. Impulse through myelinated fibers is slower than non-myelinated fibers** **Not True.** Myelinated nerve fibers conduct impulses **faster** than non-myelinated fibers. This increased speed is due to a mechanism called **saltatory conduction**, where the action potential "jumps" from one node of Ranvier to the next, reducing the time it takes for the impulse to travel along the nerve fiber. - **B. Membrane currents are generated at nodes of Ranvier** **True.** In myelinated fibers, action potentials are regenerated at the nodes of Ranvier, where the myelin sheath is absent. This allows for the rapid transmission of electrical signals. - **C. Saltatory conduction of impulses is seen** **True.** Saltatory conduction is a hallmark of myelinated nerve fibers, enabling faster and more efficient transmission of electrical impulses compared to non-myelinated fibers. - **D. Local anesthesia is effective only when the nerve is not covered by myelin sheath** **Not True.** Local anesthetics are effective on both myelinated and non-myelinated fibers. In myelinated nerves, anesthetics typically target the sodium channels at the nodes of Ranvier to block nerve conduction. Therefore, the statement that is **not true** for myelinated nerve fibers is **Option A**.
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A
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Conclusion
As we embark on this journey together, we are not just providing a service; we are creating innovations that can define the future of domain-specific AI applications. We look forward to building use cases across various industry verticals with reinforcement fine-tuning.
For more information, please reach out to your Microsoft representatives or account managers.
Updated Jan 08, 2025
Version 2.0
NandiniMuralidharan
Microsoft
Microsoft
