ML Fundamentals
Attention Mechanism
Letting an AI focus on the important words in a sentence while ignoring the rest, just like humans pay attention to key details.
Definition
A component of neural networks that allows the model to dynamically focus on the most relevant parts of the input when generating each output token. The core innovation powering Transformer models (like GPT).
Why it matters
The breakthrough that enabled modern LLMs to understand context and long-range dependencies in text.
Related terms in ML Fundamentals
Activation Functions
The "switch" inside a neural network that decides whether a neuron should fire, allowing the AI to learn complex non-linear patterns.
Active Learning
A technique where the AI asks humans to label only the most confusing examples, saving time and money on data labeling.
Anomaly Detection
Finding the "weird" stuff in a dataset, like a credit card charge in a foreign country or a broken machine part.
Artificial General Intelligence (AGI)
A hypothetical "super-AI" that can learn and do any intellectual task a human can do, not just one specific thing.
From vocabulary to outcomes
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