online services

3 stories filed under online services on Beyond Market Intelligence. The newest of them: “Google opens Gemini to developers, reshaping how apps reach users”, “Spotify's new index unlocks low-latency queries without copying data”, and “Finding the Right Compute for Your AI Inference Workloads”. Google is opening Gemini to developers, and that changes how apps reach people. Spotify's new external indexing architecture for Apache Parquet data lakes is a smart answer to a persistent problem: why copy data into a separate database just to get fast point queries? Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every online services story on Beyond Market Intelligence, newest first.

Google opens Gemini to developers, reshaping how apps reach users
TechCrunch

Google opens Gemini to developers, reshaping how apps reach users

Google is opening Gemini to developers, and that changes how apps reach people. Instead of users hunting through stores, businesses can now bring services directly into AI experiences. It's a practical step toward discovery that feels less like searching and more like asking. For anyone building for this future, the shift is worth exploring. And if you're designing for users where connectivity is scarce, our piece on offline-first AI offers a useful counterpoint.

Spotify's new index unlocks low-latency queries without copying data
InfoQ

Spotify's new index unlocks low-latency queries without copying data

Spotify's new external indexing architecture for Apache Parquet data lakes is a smart answer to a persistent problem: why copy data into a separate database just to get fast point queries? By mapping lookup keys directly to Parquet file locations, the team enables targeted reads from cloud storage without duplicating datasets. It's a practical move that keeps analytics, machine learning, and online services on the same source of truth.

Machine Learning

Finding the Right Compute for Your AI Inference Workloads

Sourcing compute for inference workloads is a puzzle most teams know well, and this post gets straight to the point. The ask for real experiences with services like RunPod or Vast.ai is smart; those pain points are where practical answers live. It's a grounded way to cut through the noise. We appreciate the directness here, and the survey feels like a natural next step for anyone who's been there.