S L Happy - ML Digest

Catastrophic Forgetting in AI: Why Deep Learning Models Forget and How to Prevent It

Catastrophic forgetting occurs when sequential training on new data degrades a model’s performance on earlier tasks, domains, or capabilities. It […]

AI is getting cheaper, but not in the simple way headlines suggest. Everyday capabilities are spreading into products, laptops, and

What if building the next GPT costs more than building a skyscraper? That question is no longer just a thought

A model can be accurate in a demo and still fail in the product. It may respond too slowly for

Approximate nearest neighbor (ANN) search is a family of algorithms and systems for quickly answering a deceptively simple question: Given

Ask an AI assistant how to calculate a business metric, and the answer may depend on a table schema, a

Imagine asking a librarian for one page that proves a claim. The librarian first runs through the whole building and

Chunking is the process of splitting source documents into smaller pieces before they are embedded and stored in a vector

Ask a friend a hard question, like “How did the failure of Silicon Valley Bank compare to the 2008 financial

Search breaks down when wording changes but meaning stays the same. A user types “I forgot my credentials,” while the

Document ingestion is the first mile of a Retrieval-Augmented Generation (RAG) system. Before retrieval, chunking, or embedding can work, raw

Retrieval-augmented generation (RAG) promises answers grounded in an external knowledge base. In practice, an answer can be wrong because the