Tokenization under the hood: BPE, WordPiece, SentencePiece, and Unigram compared
Tokenization under the hood: BPE, WordPiece, SentencePiece, and Unigram compared You deploy a chatbot. English queries average 42 tokens each. Then a …
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Samiksha AI: Universal Review & comment Analyzer
Hey DEV Community! I recently participated in a hackathon and built Samiksha AI , a universal review and comment analyzer designed to turn messy custo…
Translating 'I missed you' so it doesn't land like a form letter
I was trying to tell someone something real in her first language — not "I missed you" from a dropdown, but the version that sounds like a person said…
Is Siri AI? How Apple's Voice Assistant Really Works
Apple finally gave Siri the kind of upgrade people have been asking for, on and off, for years. The new Siri AI is not just better speech recognition …
The hard part of an AI quiz generator isn't the questions — it's the wrong answers
If you wire an LLM up to "write me 10 multiple-choice questions about photosynthesis," you'll get something that looks great in the demo and falls apa…
CareerPilot AI:AI Resume Analyzer
In the modern job market, hiring managers and talent acquisition teams face an overwhelming influx of job applications. For a single opening, hundreds…
Can LLMs save themselves from verbosity?
« Je n'ai fait celle-ci plus longue que parce que je n'ai pas eu le loisir de la faire plus courte. » — Blaise Pascal, Lettres provinciales , Lettre X…
Питон по Пассову: как NLP помог сделать Python понятным гуманитариям
О том, почему вводный курс Python для гуманитариев лучше начинать не с калькуляторов и абстрактных циклов, а с текста, частотности и осмысленных иссле…
I Built the Resume-vs-JD Scorer Every ATS Uses — In 30 Lines of JavaScript
🌐 Live demo: https://dev48v.infy.uk/solve/day1-resume-jd-match.html Day 1 of SolveFromZero — pick a real hackathon problem, ship the working solution.…
Understanding Attention in Transformers — Intuition Before Equations
When people first hear about Transformers, they often encounter words like Query, Key, Value, and Attention Heads and feel confused. But the main idea…
The Context Compression Pattern
Pattern Defined Precise Definition: Context Compression is an inference pattern that utilizes a specialized "selector" model or a ranker to distill la…
Bridging the Rigidity Gap: Deploying Secure Agentic RAG in Healthcare Governance
In the healthcare industry, data is both an organization's most valuable asset and its most heavily guarded liability. While industries like e-commerc…
The Macro Failure of "One-Size-Fits-None" Reporting: Why Healthcare Providers Fail to Act on Patient Feedback - Part I
Every month, healthcare jurisdictions pool millions of dollars into collecting Patient-Reported Experience Measures (PREMs). Millions of text files an…
Prompting styles - Basic
Query which we ask the LLM is referred to as prompt. The way in which we provide prompt to LLM makes a difference and there are different ways to to p…
I built an AI contract review and reader tool for plain-language contract understanding
I recently launched SpotClause, a small AI contract review and reader tool. The idea came from a simple problem: contracts are often difficult to read…
Лингвистика + статистика = NLP
Как-то так получилось, что я NLP-инженер, который закончил Московский государственный лингвистический университет. Мне нравится ковыряться в коде и мо…
Dual Encoder vs Cross-Encoder: Why Your RAG Pipeline Needs Both
My RAG pipeline looked fine on paper. Fast retrieval. Decent cosine scores. But when I tested it with real queries, the top results were always a litt…
How I Built Semantic Discussion Clustering Without Embeddings (and Why It Was Good Enough)
The Problem I wanted to monitor discussions around products, bugs and trends across communities. Examples: Reddit Hacker News GitHub Issues Forums Mos…
I Built a Multilingual Spam Detection Dataset with 149K+ Messages Across 23 Languages
Spam detection datasets are surprisingly bad once you move outside English. Most public datasets are: tiny, outdated, English-only, SMS-only, or missi…
Day 6 - Embedding - RAG
In the previous post, we saw what chunking is and the various methdologies of chunking. In this post, we are going to see the next stage of the RAG pi…
Hybrid Search Blueprint Series: Semantic Boosting
This article was written by Erik Hatcher . This is the third and final article of this hybrid search series. First, we surveyed the (hybrid) search la…
Day 4 - Chunking continued - RAG
Semantic Chunking Lets Consider two paragraphs A and B, focussing on strings in python. para A focus on typecasting and para B focus on accessing char…
Generation 1 — Standalone Models (2018–2022)
The Foundation of Modern AI Systems When people think of tools like ChatGPT, they often assume the intelligence comes from a single powerful system th…
What Reddit Can Teach Us About Women’s Watch Preferences (Python + NLP Project)
Most “what watch should I buy?” discussions online skew heavily male. A friend wanted to launch a women’s watch, so I helped with a small data analysi…
How to Make xt850 Match xt 850
TL;DR Since version 23.0.0 , Manticore can make searches like xt850 match xt 850 using bigram_delimiter together with digit-aware bigram_index modes. …
Did My LoRA Learn Tenacious Style—or Just Memorize Augmented Patterns?
In Week 11 Tenacious-Bench, we trained a LoRA adapter on Tenacious-style B2B sales emails using Supervised Fine-Tuning (SFT). We got a real performanc…
Auto-Furigana in the Browser — Lazy-Loading kuromoji.js's 4 MB Dictionary from a CDN to Annotate Japanese Kanji With Their Readings
Furigana are the small hiragana annotations that sit above kanji to show how they should be read. Schoolbooks, kid manga, and language-learning materi…
LLM Study Diary #2: Tokenization
Background I did some research online and found a nice course that teach how to build LLM from scratch. The course is shared public online and all the…
How to Add Sentiment Analysis to Any App in 5 Minutes (Free API)
Most text analysis solutions fall into one of two problems: Too expensive — OpenAI API costs money for every call Too complex — Hosting your own Huggi…
Part 2: Vector Embeddings in simplest terms
This is my Day 2 of learning AI fundamentals where I will be covering the following concepts: Vector Embeddings How Tokenisation and Vector Embeddings…