The Importance of Context in Machine Learning Models

When starting with machine learning models, a key question is: which model is best suited for the task?. There's a trend towards models with ever-larger context windows. But for tasks with short prompts, like a few paragraphs, is a bigger window always necessary?

Here's where context becomes crucial for effective models. While mimicking human understanding is a goal of NLP, the key lies in teaching machines to grasp the meaning beyond individual words.

Let me share two image with you

What you understand when you see this? and now, look at this

In both images, the girls are happy and smiling. What do you think their intentions are? As humans, we can accurately figure out what's on their minds. Your brain has a lot of information stored, "pre-trained" from your life experiences, and it can process the current task with context, giving you a prompt response.

This context-seeking behavior is a core challenge in NLP and AI – enabling machines to understand language with a human-like depth.

Are you able to identify bigger context needs in your business workflow or short prompts are serving your requirements. Do write to me, I would love to hear from you.

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