examples
examples on Beyond Market Intelligence: a running collection of 3 stories we have gathered and hand-picked because they are worth your time. Every post here touches on examples in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around examples, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Good Machine Learning Posters [D]
Preparing for ECCV 2026 and seeking inspiration for impactful machine learning poster design? You're in the right place. We've gathered a community discussion highlighting exceptional ML/CV posters—a valuable resource for crafting a compelling visual presentation of your work. To further enhance your understanding of current trends, explore our analysis of "Sliding-window attention beats linear on long-context reasoning," demonstrating practical solutions for optimizing large language models. Discover examples and strategies to elevate your poster and maximize its impact at the conference.
How to Create Custom Skills in Claude: A Step-by-Step Guide
Tired of repeating instructions and workflows in every Claude conversation? Custom Skills offer a powerful solution, packaging reusable templates, scripts, and reference materials to streamline your AI interactions. This guide provides a step-by-step walkthrough for creating these skills, empowering teams to maintain consistency and accelerate productivity. Discover how to transform Claude into a more efficient and predictable tool – a critical evolution for data-driven workflows.
Prompt Compression Techniques: How to Reduce LLM Costs Without Losing Important Context
Large language models frequently process more information than necessary, driving up costs and potentially obscuring crucial details. Prompt compression techniques offer a solution, reducing prompt size while preserving essential meaning and instructions. This allows for more efficient token usage, faster response times, and improved clarity for the model. Explore strategies to streamline your prompts and optimize performance—discover how to transform your LLM interactions for greater efficiency. For a deeper dive into related challenges, see "AI agents aren't confidently wrong because of bad context."