Microsoft Unveils 54 Reasoning Models for Efficient Mathematical Inference
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In a thrilling turn of events, Microsoft has unveiled a lineup of 54 reasoning models, each with its own unique twist. From the powerful 54 reasoning plus to the intriguing 54 mini reasoning, these models promise to revolutionize the world of mathematical reasoning. The team at Microsoft has employed cutting-edge distillation techniques, drawing inspiration from models like Deep Seek R1 to fine-tune their creations. With a focus on predicting longer chains of thought, these models are set to shake up the landscape of inference time scaling.
But the real excitement lies in the details of how these models were trained. Continual training, supervised fine-tuning, alignment training, and reinforcement learning with verifiable rewards all play a crucial role in shaping the capabilities of these reasoning models. Microsoft's vision extends beyond just software - they aim to integrate these models into Windows devices, introducing the world to the revolutionary FI Silica for local use. This move signals a shift towards more efficient and specialized applications, paving the way for a new era of computing.
The concept of a small yet powerful reasoning model has captured the imagination of tech enthusiasts worldwide. By focusing on effective reasoning without the need for exhaustive data, Microsoft is pushing the boundaries of what AI can achieve. The 54 mini reasoning model, with its compact size and impressive performance, serves as a testament to the potential of small-scale AI. As comparisons with other models like Quen 3 1.7 billion reveal subtle nuances in reasoning approaches, it becomes clear that the future of AI is filled with endless possibilities.
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Viewer Reactions for Microsoft Joins the Reasoning Race!!
Karpathy's idea of a small model capable of grounding its responses to RAG or internet search is interesting
Comparison of Phi4 to comparable sized models like Gemini 2.5
Concerns about Microsoft integrating AI models with flagship products like Excel and Outlook
Preference for Qwen 4b in tests for general knowledge and COT logic
Gemini not showing complete thinking, only providing summaries in bullet points
Mixed opinions on Phi-4-reasoning model's performance and verbosity
Appreciation for the mini model Phi-4-r
Criticism towards Microsoft for potentially running models without explicit permission and concerns about data stealing
Mention of Phi-4-reasoning-plus model's tendency to provide excessive output even for simple questions
Highlighting Phi-4-reasoning as the first open weight multimodal reasoning model, but lagging in performance compared to other models
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