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Natural Language Processing
Text, speech, translation, and retrieval with modern NLP techniques.
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Latest in Natural Language Processing
What counts as a large cosine similarity?
1+ hour, 47+ min ago (457+ words) Machine learning represents words as vectors and measures the similarity of words by the angles between the vectors. where θ is the angle between the vectors, and so This is the cosine similarity between the words represented by x and…...
Puzzle Solution Revealed - Transformer: Need for Position Embedding
4+ hour, 45+ min ago (15+ words) Introduce position embedding, residuals and layers ▶ Watch the 7-minute... Tagged with llm, transformers, machinelearning, ai....
What Are Embeddings? How AI Converts Meaning Into Numbers
6+ hour, 35+ min ago (1590+ words) Consider these two sentences: "I want to buy a phone with a long-lasting battery." and "Which smartphone should I choose if I don't want to charge it frequently?" The wording barely overlaps. No shared phrase, almost no shared vocabulary. Yet…...
Language is a routing problem, not a translation problem
8+ hour, 56+ min ago (228+ words) Most teams approach a multilingual support bot as a translation problem. Wire up a translation layer, send everything to one big model, done. We did roughly that the first time, and it mostly worked — until we looked at the bill…...
How to Create a Mental Health AI Agent: Features, Compliance, and Real-World Cost Guide | create-mental-health-ai-agent
11+ hour, 11+ min ago (1145+ words) Mental health applications are moving beyond simple chatbots. With advances in large language models, natural language processing, speech technologies, and retrieval-augmented generation, developers can now build AI agents capable of handling more complex conversations and workflows. But building an AI…...
“Machine translation is still broken for most of the world's languages”: Cohere builds non-reasoning for a reason
2+ day, 3+ hour ago (203+ words) Cohere's North Small Translate beats DeepL and Google Translate on WMT26 across 50 languages — but commercial use requires a Model Vault license....
What Are Embeddings? How AI Represents Meaning as Numbers
2+ week, 2+ day ago (1027+ words) Embeddings are dense numerical vectors learned so that items with useful semantic or behavioral relationships occupy nearby regions of a representation space. This guide explains the mechanism, trade-offs, evaluation, and controls that matter in practice. Embeddings deserves a precise explanation…...
Stemming vs Lemmatization: Which NLP Technique Should You Use?
2+ day, 3+ hour ago (770+ words) When working with text, the same word can appear in many forms. For example: connect connected connecting connection To a human, these …...
RNN vs LSTM vs GRU for Sequential Data
2+ day, 8+ hour ago (460+ words) A simple guide to understanding RNN, LSTM, and GRU, how they work, their differences, and where to use them. Sequential data is data where the order of …...
Vectors: How Numbers Turns Meaning Into Direction
2+ day, 11+ hour ago (1288+ words) When we say -’ The boy is playing in the garden.’ we see words. Now a language model can only interpret numbers. Before an AI system can compare …...