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Deep Learning

This tag is for discussing, sharing articles, and asking questions primarily on deep learning - a subfield of machine learning.

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Kaggle Getting Started Competition -- Petals to the Metal

Kaggle Getting Started Competition -- Petals to the Metal

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9 min read
When Chaos Wins: Adding Noise Improved My Snake AI's Stability

When Chaos Wins: Adding Noise Improved My Snake AI's Stability

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5 min read
How RNNs Work — Remembering Previous States in Sequential Data

How RNNs Work — Remembering Previous States in Sequential Data

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4 min read
FP32, INT4, and Everything Between - What I Learned About Precision on Mobile

FP32, INT4, and Everything Between - What I Learned About Precision on Mobile

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7 min read
SANA-WM in 5 quick facts

SANA-WM in 5 quick facts

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1 min read
How I Build Cat vs Dog Classifier

How I Build Cat vs Dog Classifier

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1 min read
How Self-Driving Cars Understand Traffic: AI Vision Explained

How Self-Driving Cars Understand Traffic: AI Vision Explained

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3 min read
How Neural Networks Work — From Perceptrons to Backpropagation

How Neural Networks Work — From Perceptrons to Backpropagation

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3 min read
How to read an AI's thoughts before it speaks

How to read an AI's thoughts before it speaks

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3 min read
Why does paying more make your LLM reply faster?

Why does paying more make your LLM reply faster?

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3 min read
The Softmax Bottleneck: Why Making LLMs Bigger Doesn't Always Make Them Smarter

The Softmax Bottleneck: Why Making LLMs Bigger Doesn't Always Make Them Smarter

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4 min read
The Exact Prompt Engineering That Makes Our Voice AI Sound Human (Full Prompts Included)

The Exact Prompt Engineering That Makes Our Voice AI Sound Human (Full Prompts Included)

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6 min read
How Large Language Models Work — From Transformers to Conversational AI

How Large Language Models Work — From Transformers to Conversational AI

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4 min read
Lost in the Middle: Why LLMs Quietly Ignore the Centre of Their Own Context Window

Lost in the Middle: Why LLMs Quietly Ignore the Centre of Their Own Context Window

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3 min read
Stop Guessing Which Weights Your Neural Network Actually Learned: Deterministic Initialization That Tracks Every Change

Stop Guessing Which Weights Your Neural Network Actually Learned: Deterministic Initialization That Tracks Every Change

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6 min read
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