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distributed-systems

A collection of 5 posts

The Natasha Problem: Why Your Data Pipeline Only Fits One Person

data-engineering

The Natasha Problem: Why Your Data Pipeline Only Fits One Person

For most folks, you probably don’t think about clothing sizes. There’s a number, you pick it, you try on the clothes, and if they fit, then congrats, you’re that number. But how’d they pick that number? And why does every style/line/person fit slightly differently?

A Picture Is Worth Ten Thousand Tokens

ai-infrastructure

A Picture Is Worth Ten Thousand Tokens

DeepSeek's new OCR model achieves 97% accuracy while using one-tenth the tokens by rendering text as images. The computationally "heavy" modality turns out to be the efficient one, which should make us question some basic assumptions about how we architect these systems.

NVIDIA Built the Most Powerful Chips Ever. Google Trained the World's Best AI Without Them.

ai-infrastructure

NVIDIA Built the Most Powerful Chips Ever. Google Trained the World's Best AI Without Them.

In 2020, NVIDIA released the A100 with 54 billion transistors, 80GB of memory, and 2 TB/s bandwidth. It was VERY BIG and VERY FAST(tm). In 2022, the H100 arrived with 80 billion transistors, the first Transformer Engine optimized for the neural network architecture behind ChatGPT, and performance gains

From Pandas to Upstream Control: The Evolution PyData Needs Next

Data Engineering

From Pandas to Upstream Control: The Evolution PyData Needs Next

The Python data stack gave us Pandas, Dask, and Arrow. But we've created a new crisis: the ingest-it-all-first tax that's drowning us in noise.

WTF Do You Spend $300B On?: The Oracle-OpenAI Deal Decoded

Data Infrastructure

WTF Do You Spend $300B On?: The Oracle-OpenAI Deal Decoded

Discover the challenges and expenses behind OpenAI's $300 billion Oracle deal, revealing a true AI cost breakdown: 80% data prep, 20% training