IBM has launched Granite 3.2, the latest version of its Granite AI language models that emphasizes efficiency and practicality for business applications. This version introduces novel chain-of-thought (CoT) reasoning capabilities, allowing AI to deconstruct complex problems into logical steps, mimicking human reasoning. The model employs a Thought Preference Optimization framework, enhancing its performance on various tasks while avoiding the limitations that typically plague models focusing solely on reasoning. This advancement aims to improve user interactions, making AI tools more effective in decision-making processes and delivering insightful responses to complex inquiries.
IBM has unveiled Granite 3.2, a new large language model that incorporates experimental chain-of-thought reasoning capabilities for advanced problem-solving in business contexts.
Unlike traditional reinforcement learning, the Thought Preference Optimization framework enables improved reasoning across a broader spectrum of tasks without losing efficacy.
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