Achieving 10,000x training data reduction with high-fidelity labels

Google just showed it is possible to reduce LLM training data by up to 10,000x while maintaining or even improving model performance!

Trigonometric Identities the Euler Way

I have always believed that mathematics is about thinking rather than memorizing. The trigonometric identities were among the things we were told to memorize at school, and not only I struggled with that but I also actively rebelled against this approach. For me, mathematics is fundamentally about having a minimal but sufficient set of definitions and axioms, understanding them deeply, and then deriving everything else from these foundations. During one of my Complex Analysis lectures in my undergraduate Applied Mathematics studies, I was introduced to Euler's formula. When I discovered how it could be used to derive some of the most important trigonometric identities, I was more than relieved. I could finally derive the identities easily whenever I needed them, instead of relying on rote memorization, or panicking about my failure to memorize them.

NanoNets OCR for Handwritten Notes

Nanonets has released Nanonets-OCR-s, a state-of-the-art small 3B image-to-markdown OCR model that goes far beyond traditional text extraction. The model is available on Hugging Face and integrated with their docext tool for immediate use. Medium post can be found here.

Contextualized Evaluations

"When we ask a language model a question, we often leave out important context. A query like, "Is coffee good for you?" seems straightforward, but a quality response depends on hidden context about the user (e.g., does the user have high blood pressure? Are they pregnant?)."

A Job Postings Tool: A Guide to MLX-LM Server and Tool Use with the OpenAI Client

Building intelligent applications that can interact with real-world data requires more than just Large Language Models (LLMs), it requires the ability to call external functions and tools. Tool calling transforms a conversational LLM into an agent that can execute code, query APIs, and perform tasks. In this blog post, we are going to create a job search assistant using the MLX-LM Server, connect it to the OpenAI client , and utilise the Qwen3-8B model’s tool‐calling abilities. We are going to build a tool that scrapes job postings from DEV.BG, a popular Bulgarian job board, and provides intelligent responses about available positions.

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