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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
Analyze trends, Measure sentiment, Predict what comes next
6+ hour, 33+ min ago (108+ words) Turn social-media posts or documents into a structured narrative analysis, then ask questions about the corpus in any language. Demo: A complete run on Reddit WallStreetBets with 43,976 posts covering the January 2021 GameStop short squeeze Two real questions asked to the…...
JEV Classifier: 5.43x as Fast as Haiku, 96% Lower Cost
1+ day, 9+ hour ago (1424+ words) An Auto Router pays for classification before the selected model can answer. In our benchmark, TypeSafe JEV classified requests 5.43x as fast as Haiku, comparing median classifier latency: 126.81 ms versus 688.40 ms. Registry-priced classifier cost was 96.12% lower, rounded to 96% in the title…...
Machine Learning Use Cases: 10 Ways Machine Learning is Used in the Real World
16+ hour, 9+ min ago (702+ words) Modern ML now combines data, models, tools, and workflows across many industries. AI agents and multimodal systems are expanding machine learning from prediction toward practical task execution. Video services, online stores, music apps, and social platforms use ML to predict…...
# Beyond Transformers: A Mathematical Critique of Cross-Lingual Diffusion Architectures
20+ hour, 5+ min ago (424+ words) The current state of multilingual NLP is dominated by transformer-based architectures that often treat cross-lingual alignment as a secondary optimization task. For researchers and engineers working with low-resource languages or requiring strict semantic preservation, the "black box" nature of proprietary…...
The Death of Token Generation: Why Classifiers Are Winning Again
17+ hour, 4+ min ago (226+ words) Most artificial intelligence models are built to talk. If you ask a standard chatbot a simple yes or no question, you will likely get …...
A model doesn't read text: what a tokenizer decides for you
1+ day, 47+ min ago (1022+ words) Originally published at cchinchilla.dev. Part 1 of From code to weights, a 12-part series on ML fundamentals for engineers. A language model has never seen a letter. It sees integers. Somewhere between your string and the first matrix multiply there's…...
I Counted the Words in My Prompt — Then Learned Why AI Doesn’t Actually Read Words
23+ hour, 9+ min ago (1041+ words) I thought AI saw the same words I saw. Then I learned about tokens. When I type something into ChatGPT, I see …...
Machine Learning Concepts: The Bigger Picture
1+ day, 5+ hour ago (27+ words) When you start learning AI, machine learning can feel confusing because there are so many new terms. Supervised learning, unsupervised learning …...
How I Built a 150 GB Multilingual & Code Dataset for Central Asian AI (And Fought Out-of-Memory Errors for 10 Hours)
2+ day, 2+ hour ago (326+ words) Hi Dev.to! While tech giants are competing to train LLMs on trillions of English tokens, there is a severe shortage of high-quality open-source datasets for Central Asian languages (Kyrgyz, Kazakh, Uzbek, Tajik). Technical corpora for these regions are scarce,…...
"machine learning"~2 — phrase and proximity search in Whoosh
2+ day, 3+ hour ago (362+ words) When users type quotes around words, they mean it. "machine learning" should not match a page that happens to contain machine in one paragraph and learning three paragraphs later. Bag-of-words scoring alone can't express that intent — you need phrase and…...