How Hugging Face's Transformers Added UltraBERT with Layer-Specific Rotary Embeddings
Why UltraBERT Integration Matters The Hugging Face Transformers library is a cornerstone for NLP research and applications, providing a unified inte…
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I Distilled a 568M Multilingual Model Into a 37M Japanese-English Encoder — Here's What Survived
Cross-lingual retrieval distillation, compression, and the honest cost table. Scope note: English-to-Japanese retrieval only. EN-JA eval is syntheti…
A Mixed-Language Test Set for WhatsApp Assistants in Gulf Businesses
Disclosure: I run NxFlowAI, an automation agency serving UAE businesses remotely from Mumbai. This post is a vendor-neutral testing pattern. Custome…
Day 31: The Transformer Decoder Architecture
What Is a Transformer Decoder? A transformer decoder is a type of neural network for generating sequences, such as sentences, one piece at a time. Y…
FRIDA Decisions: быстро думать на русском
FRIDA Decisions — открытая модель быстрого мышления для русского языка. Она выбирает вариант из списка, ставит оценку по шкале, отвечает «да» или «н…
Your intent classifier is 12 points worse in Portuguese: benchmarking Laya, Strands Decider and Qwen3 embeddings
A conversational agent first has to decide what the customer wants. I measured that step for customer-service messages in Brazilian Portuguese (PT-B…
Работа с текстом без LLM? Продолжаем развивать парсер Real AI SA
Итак, прошло уже больше 2х лет с момента моей последней статьи Пора рассказать, что происходит в жизни проекта и сколько уже потратили на его реализ…
How to extract clean article text, author and date from news URLs
Copying an article out of a web page sounds easy until you try it at scale. You get menus, cookie banners, related links and ads mixed into the text…
chunklet-py v3.0.0: a smaller install, a smarter chunker, and no more global state
There's a new chunker that learns its own boundaries, two heavy dependencies moved to optional extras, and a few configuration changes that stop you…
Teaching a Computer Word Meaning Without a Dictionary
When I started learning Natural Language Processing (NLP), one question bugged me: how does a computer understand words? The honest answer is that i…
My First Steps into Word Embeddings with Word2Vec
Explain what word embeddings are and why they matter: so, Word embeddings are numerical representations of words. Each word is represented by a list…
Decision models are English-first. I measured them in Japanese, then built one.
What happens to System One decision models outside English: a position prior in Laya, an open Japanese model, a translated benchmark, and what trans…
What I Learned About Word Embeddings While Building a FAQ Chatbot
When I set out to build a simple FAQ chatbot for Python programming questions, I thought I'd be done in a weekend. I was wrong — but in the best way…
Бендер как диавол
Искал скрытые библейские цитаты и намеки в тексте советского романа «12 стульев» с помощью Python и что у меня получилось. Читать далее
Day 25: Bahdanau vs. Luong Attention
What Is Attention in Sequence Models? Attention is a technique that allows neural networks to focus on the most relevant parts of their input when g…
Гибридный RAG на Налоговом кодексе: восемь находок, семь потерь
守 (Сю) — это про то, как, сохранив себя, достичь своей лучшей версии. При чём здесь RAG? Да при том, что, прежде чем рваться к агентным RAG и GraphR…
Автоматизация проверки информационных моделей на соответствие нормативам с использованием дескрипционной логики
Авторы: Денис Олегович Турыгин, программист-разработчик отдела разработки инновационных систем ООО «Нанософт разработка» denis.turygin@nan…
300 классов, 400 сэмплов и никакого промптинга: ЛЛМ как энкодер для классификации
Когда речь заходит о ЛЛМ и классификации, первая мысль — попросить модель сгенерировать класс через промптирование модели с описанием правил и добав…
Как мы обучили детектор джейлбрейков для русскоязычных AI-агентов
Привет, Хабр! На связи команда R&D в Just AI, мы занимаемся исследованиями в области NLP и GenAI, чтобы продукты компании держали статус SOTA на…
# Beyond Transformers: A Mathematical Critique of Cross-Lingual Diffusion Architectures
Beyond Transformers: A Mathematical Critique of Cross-Lingual Diffusion Architectures The current state of multilingual NLP is dominated by transfor…
Питон по Пассову 2: методика изучения иностранных языков программирования
В статье рассматривается применение принципов методики обучения иностранным языкам при построении занятий по программированию: от имитативных и подс…
Can multilingual AI improve product search on international marketplaces?
International marketplaces may support several languages, but their search engines often perform much better in English. A shopper can describe exac…
Why we built recall-first search on PostgreSQL
Our careers page search often felt broken. Searching for “Java” could return JavaScript roles. A misspelling could produce no results at all. Search…
What Are Embeddings? How AI Converts Meaning Into Numbers
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 i…
🇲🇦 Building SILMA-Darija: Open LLMs for Moroccan Arabic & Arabizi
🇲🇦 Building SILMA-Darija: Open LLMs for Moroccan Arabic & Arabizi Most Arabic models struggle with Moroccan Darija. When you talk to them in Dar…
Word Sense Disambiguation: How NLP Understands Word Meaning in Context
Here is a sentence that will break most computers. “I went to the bank.” Did you go to a financial institution to withdraw money? Or did you sit dow…
Sentiment Analysis of Apple Tweets: An NLP Approach
The Business Challenge When Apple launches a new product, social media explodes with customer reactions. Support teams get overwhelmed, marketing se…
How I Engineered the World's First Khattak Pashto LLM (Qwen2 + LoRA)
Standard Large Language Models (LLMs) are incredible, but they have a massive blind spot: rural and regional dialects. While standard Pashto is supp…
Day 15: Visualizing Embeddings with t-SNE and PCA
Previously, on Day 14: Explained how word embeddings represent words as vectors, the limitations of classic approaches like one-hot encoding, and ho…
Was TinyStories the Domain or the Vocabulary?
I have been running a long series of experiments on whether small models can be made to behave usefully, and one obvious thing to borrow is whatever…