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Polars is a DataFrame library written in Rust on the Apache Arrow memory format, and the speed comes less from the language than from the model. The model? Describe your work as expressions, and the Polars query engine plans them out.

Learn about private AI browsing for data professionals.

Explore seven open-source ChatGPT alternatives, from lightweight local chat interfaces and document assistants to agent platforms, multi-user setups, and complete self-hosted AI workspaces.

A closer look at TypeSafe AI's Jev, what it actually does, what is genuinely new, and where the hype goes too far.

Learn how to build a Python AI agent with the OpenAI Agents SDK, using tool calling and function tools to automate multi-step workflows.

Almost every slow Polars script lacks in terms of one of these two: its expression engine written and executing in Rust across every core at its disposal, and its query optimizer that rewrites your work before any of it runs.

In this second article in our short series on SLM optimization techniques we focus on the reuse of the prompt prefix with a key-value cache.

This article covers five prompt optimization strategies such as: prompt optimization, prompt engineering, LLM output quality, few-shot prompting, chain-of-thought, structured outputs.

See how SerpApi's Markdown output can cut search-result token usage by up to 74%, reducing AI agent costs and context-window overhead.

This article walks through how ChatGPT Work specifically earns its reputation, where the underlying models genuinely hold up against the competition, and where the honest limits are.