Introduction: Evaluating LLM outputs is fundamentally different from traditional ML metrics. You can’t just compute accuracy when there’s no single correct answer, and human evaluation doesn’t scale. This guide covers the full spectrum of LLM evaluation: automated metrics like BLEU, ROUGE, and BERTScore for measuring similarity; semantic metrics that capture meaning beyond surface-level matching; LLM-as-judge… Continue reading
Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Vector Database Optimization: Scaling Semantic Search to Millions of Embeddings
Introduction: Vector databases are the backbone of modern AI applications—powering semantic search, RAG systems, and recommendation engines. But as your vector collection grows from thousands to millions of embeddings, naive approaches break down. Query latency spikes, memory costs explode, and recall accuracy degrades. This guide covers practical optimization strategies: choosing the right index type for… Continue reading
RAG Patterns: Advanced Retrieval Augmented Generation Strategies
Introduction: Retrieval Augmented Generation (RAG) has become the standard pattern for grounding LLM responses in factual, up-to-date information. But basic RAG—retrieve chunks, stuff into prompt, generate—often falls short in production. Queries get misunderstood, irrelevant chunks pollute context, and answers lack coherence. This guide covers advanced RAG patterns that address these challenges: query transformation to improve… Continue reading
Embedding Dimensionality Reduction: Compressing Vectors Without Losing Semantics
Introduction: High-dimensional embeddings from models like OpenAI’s text-embedding-3-large (3072 dimensions) or Cohere’s embed-v3 (1024 dimensions) deliver excellent semantic understanding but come with costs: more storage, slower similarity computations, and higher memory usage. For many applications, you can reduce dimensions significantly while preserving most of the semantic information. This guide covers practical dimensionality reduction techniques: PCA… Continue reading
IoT is not all about Cloud
Recent past, I had multiple discussions with many tech forums and many people have a misconception about IoT and Cloud. Some think whenever we do something like blinking an LED with Raspberry Pi or Arduino is IoT. I just thought of sharing some of my viewpoints on these terminologies. Internet of Things(IoT) – refers to… Continue reading
LLM Latency Optimization: Techniques for Sub-Second Response Times
Introduction: LLM latency is the silent killer of user experience. Even the most accurate model becomes frustrating when users wait seconds for each response. The challenge is that LLM inference is inherently slow—autoregressive generation means each token depends on all previous tokens. This guide covers practical techniques for reducing perceived and actual latency: streaming responses… Continue reading