Binay Chandra

Executing LLM-Generated Code

Executing LLM-Generated Code Safely: A Guide to Sandboxing Solutions

1 Comment / Large Language Models, Generative AI /

Generative AI models that write code like GitHub Copilot, ChatGPT, and specialised coding assistants have transformed how developers work. These tools can generate entire functions, debug complex issues, and even create complete applications from natural language descriptions. However, this powerful capability comes with significant risks: what happens when we actually run the code these AI models […]

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Evaluating Large Language Models: A Comprehensive guide on Metrics, Methods, and Best Practices

6 Comments / Large Language Models, Generative AI /

The rise of Large Language Models (LLMs) like GPT-4, Claude, and Llama has reshaped technology—from writing code and emails to powering advanced chatbots. Their abilities often feel magical, but for developers, product leaders, and researchers tasked with integrating this power into real-world applications, a critical question emerges: How do you move beyond impressive demos and

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singular value decomposition

Singular Value Decomposition Simplified: A Practical Guide with Python Code

3 Comments / Linear Algebra, Image Processing /

Singular Value Decomposition (SVD) is a matrix factorization technique that decomposes any real or complex matrix into three simpler matrices that reveal its underlying structure. In essence, SVD breaks down a matrix into its core components, making it easier to analyze and work with, especially in high-dimensional data settings. Ever wondered what goes on behind

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