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Natural Language Processing
Text, speech, translation, and retrieval with modern NLP techniques.
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Machine Learning Concepts: The Bigger Picture
2+ hour, 20+ min 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)
23+ hour, 18+ min 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
1+ day, 56+ min 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…...
Inside the Resume Parsing Pipeline: Where Extraction Breaks
1+ day, 4+ hour ago (1010+ words) If you’re building or evaluating an ATS integration, resume parsing looks simple from the outside and gets genuinely interesting once you look at where it fails. Here’s the pipeline, stage by stage, and the specific failure mode at each step....
Your LLM Has Never Read a Word: Tokenization Explained for Developers
1+ day, 8+ hour ago (1016+ words) You type a sentence into ChatGPT and it looks like normal English. The model doesn't see it that way. In fact, it never sees words at all. Before the model processes anything, your text is converted into a sequence of…...
Applied Sciences, Vol. 16, Pages 9294: Large Language Models in the Analysis of Radar Plotting Images in Accordance with COLREGs
1+ day, 8+ hour ago (392+ words) The development of artificial intelligence (AI) opens new possibilities for the automatic interpretation of radar images in maritime navigation. Traditionally, the interpretation of radar indications requires the experience of the officer of the watch, who assesses the risk of collision…...
Linkup Research Releases SPARSEUP: A 149M-Parameter Open-Source Sparse Embedding Model
1+ day, 9+ hour ago (450+ words) Linkup research team releases SPARSEUP, an open-source learned sparse embedding model. The model runs on a 149M-parameter ModernBERT backbone and ships under Apache 2.0. Linkup team reports 56.4 average nDCG@10 on BEIR-13. It calls this the strongest public vocabulary-based sparse encoder it…...
Is transformer attention really a Hopfield network?
1+ day, 10+ hour ago (549+ words) One line to carry: one update step of a modern continuous Hopfield network equals scaled dot-product attention under a specific identification of queries, keys and values; that is an identity of operation, not a history of how transformers were built,…...
Translating Full Books with LLMs: Our Chunking Strategy for Long-Form Context
1+ day, 14+ hour ago (374+ words) How we built a pipeline that preserves context across 100k+ token books using Python, FastAPI, and Claude's context window. So we needed a chunking strategy that preserves cross-chapter context: terminology, character voice, consistent style. We split the book into overlapping chunks,…...
How many tokens is 1,000 words? A conversion cheat sheet for LLM prompts
1+ day, 16+ hour ago (334+ words) If you only want the number: 1,000 words of ordinary English is roughly 1,300 tokens. Going the other way, 1,000 tokens is roughly 750 words, or about 4,000 characters. That is the whole answer for estimating. The rest of this post is the table, the…...