Principles for Responsible AI
The rapid development and adoption of Artificial Intelligence (AI), particularly generative AI like Large Language Models (LLMs), has brought forth […]
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Residual Connections in Machine Learning
One of the critical issues in neural networks is the problem of vanishing and exploding gradients as the depth of
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How to Initialize Weights in Neural Networks: A Deep Dive
Weight initialization in neural networks significantly influences the efficiency and performance of training algorithms. Proper initialization strategies can prevent issues
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The Vanishing and Exploding Gradient Problem in Neural Networks: How to Overcome It
Two critical issues that often arise in training deep neural networks are vanishing gradients and exploding gradients. These issues can
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How to Choose the Best Learning Rate Decay Schedule for Your Model
The training process involves optimizing a model’s parameters to minimize the loss function. One crucial aspect of this optimization is
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Top 20 Most Influential AI Research Papers of 2024
Here are the 20 influential AI papers in 2024: Mixtral of Experts (Jan 2024) [paper] Vision Mamba: Efficient Visual Representation
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Understanding the Bias-Variance Tradeoff: How to Optimize Your Models
In ML and statistical modeling, the concept of bias-variance trade-off is fundamental to model performance. It serves as a guiding
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SentencePiece: A Powerful Subword Tokenization Algorithm
SentencePiece is a subword tokenization library developed by Google that addresses open vocabulary issues in neural machine translation (NMT). SentencePiece
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WordPiece: A Subword Segmentation Algorithm
WordPiece is a subword tokenization algorithm that breaks down words into smaller units called “wordpieces.” These wordpieces can be common
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Tool-Integrated Reasoning (TIR): Empowering AI with External Tools
Tool-Integrated Reasoning (TIR) is an emerging paradigm in artificial intelligence that significantly enhances the problem-solving capabilities of AI models by
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Tree of Thought (ToT) Prompting: A Deep Dive
Tree of Thought (ToT) prompting is a novel approach to guiding large language models (LLMs) towards more complex reasoning and
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Program Of Thought Prompting (PoT): A Revolution In AI Reasoning
Program-of-Thought (PoT) is an innovative prompting technique designed to enhance the reasoning capabilities of LLMs in numerical and logical tasks.
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