𝗙𝗿𝗼𝗺 𝗘𝘅𝗽𝗹𝗶𝗰𝗶𝘁 𝗖𝗼𝗧 𝘁𝗼 𝗜𝗺𝗽𝗹𝗶𝗰𝗶𝘁 𝗖𝗼𝗧
AI models solve hard problems by thinking step by step. This process is called Chain of Thought or CoT.
Most models use Explicit CoT. They write out every single thought before giving an answer. This makes the model slow. It also uses many tokens.
New research shows a better way. Models can move to Implicit CoT. This means the model internalizes the reasoning steps. It thinks through the logic without writing every word down.
This shift changes how AI works. It makes models faster. It makes them more efficient.
How it works:
- Models learn to follow logic patterns.
- They move reasoning from the output to the hidden layers.
- The model solves complex problems with less text.
Training a model to internalize these steps requires specific data and methods. This helps the model maintain accuracy while reducing the cost of generation.
You should watch this area closely. Efficient reasoning is the next step for large language models.
Optional learning community: https://t.me/GyaanSetuAi