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Home » Building Custom Reasoning Models for Advanced Agentic AI Autonomy

Building Custom Reasoning Models for Advanced Agentic AI Autonomy

March 7, 2025
in AI, How To
Reading Time: 2 mins read
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Introduction: The Need for Advanced AI Reasoning

Empowering AI agents with advanced reasoning is crucial for achieving true autonomy in decision-making and problem-solving. AI systems must go beyond pattern recognition to logical reasoning, enabling them to:

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✅ Break down complex problems into structured reasoning pathways
✅ Make autonomous decisions in real-world applications
✅ Perform multi-step logical inferences for higher accuracy

Whether in healthcare, finance, customer support, or supply chain, AI agents with enhanced reasoning capabilities can revolutionize industries by acting more like human experts.


Developing Reasoning Models With NVIDIA NeMo

Using Open-Source AI Models

This session will demonstrate how to build and customize reasoning models using:

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🔹 DeepSeek-R1 – A state-of-the-art open-source LLM
🔹 Llama – Meta’s advanced language model
🔹 Nemotron – NVIDIA’s highly scalable AI model

These models can be fine-tuned using NVIDIA NeMo and OpenRLHF (Open Reinforcement Learning from Human Feedback) to improve logical reasoning and autonomous decision-making.

Techniques for Enhancing AI Reasoning

1️⃣ Distillation – Extracting knowledge from large models to train smaller, efficient AI agents.
2️⃣ Reinforcement Learning (RLHF) – Training AI models through reward-based learning to enhance decision-making and adaptability.
3️⃣ Model Customization – Fine-tuning open-source LLMs using domain-specific data for industry applications.


Real-World Applications of Reasoning AI Models

📌 Healthcare: AI diagnosis assistants can analyze medical records, suggest treatment plans, and reason through symptoms.
📌 Finance: AI-powered investment advisors can evaluate market trends and predict risks.
📌 Customer Support: Chatbots with logical reasoning can provide personalized responses and solve multi-step queries.
📌 Supply Chain: Autonomous AI decision-makers can optimize logistics, reducing delays and inefficiencies.


Key Takeaways from This Session

🚀 Learn how NVIDIA NeMo enables advanced reasoning for AI agents
🔍 Discover how DeepSeek-R1, Llama, and Nemotron can be customized for enterprise AI
🛠 Explore distillation & RLHF techniques for enhancing AI autonomy
🏆 Understand how AI reasoning can revolutionize multiple industries

🔗 Join the session to unlock the future of autonomous AI agents! 🚀

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