recall@10
recall@10 at Beyond Market Intelligence is a file of 3 stories. The newest of them: “Bring GPU-accelerated nearest-neighbor search to Apple Silicon with mlxVS”, “Discover how AI finds paintings by color scheme across 48,000 masterpieces”, and “Whitetree: smarter nearest-neighbor search for streaming sensor data”. If you're feeling constrained by running GPU-accelerated nearest-neighbor search only on NVIDIA hardware, mlxVS changes that for Apple Silicon users. Finding a painting by its color palette has always been a slow, computationally expensive task, until now. 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 recall@10 story on Beyond Market Intelligence, newest first.
Bring GPU-accelerated nearest-neighbor search to Apple Silicon with mlxVS
If you're feeling constrained by running GPU-accelerated nearest-neighbor search only on NVIDIA hardware, mlxVS changes that for Apple Silicon users. This open-source library ports NVIDIA cuVS algorithms, exact k-NN, k-means, NN-Descent graphs, and CAGRA, to MLX, delivering impressive speed on a MacBook Pro M3 Pro. It's a practical, accessible tool for anyone exploring faster vector search without leaving the Apple ecosystem. For deeper coverage on AI model behavior, see "Three Small AI Models Falter When Told Their Answers Are Wrong."
Discover how AI finds paintings by color scheme across 48,000 masterpieces
Finding a painting by its color palette has always been a slow, computationally expensive task, until now. Palette Atlas reduces 48,000 masterpieces to 128-color vectors and uses a clever embedding trick to make search practical. The sliced Earth Mover's Distance approach hits 78% overlap with exact results while running in under a millisecond. That's the kind of practical innovation that makes you wonder what other data tasks are waiting for a smarter approximation.
Whitetree: smarter nearest-neighbor search for streaming sensor data
A dynamic exact index for streaming nearest-neighbor search is rare, and whitetree makes a strong case for it. The key insight: scipy's cKDTree has a fixed per-query cost, so maintaining several small trees beats rebuilding one large one. The numbers are compelling, especially the 1,100 steps per second on a 200k-point sliding window. It's a practical, well-measured contribution, and the open question about missed benchmarks is worth exploring.