Welcome to the Daft blog
Join us as we explore innovative ways to handle multimodal datasets, optimize performance, and simplify your data workflows.
VLAs are dead, long live World Action Models - a summary of Jim Fan's Robotics End Game talk
Jim Fan argues robotics will follow the exact LLM playbook - and VLAs are already being replaced by World Action Models.
VLAs are dead, long live World Action Models - a summary of Jim Fan's Robotics End Game talk
Jim Fan argues robotics will follow the exact LLM playbook - and VLAs are already being replaced by World Action Models.
What is physical AI - is it more than just hype?
Physical AI has become a real trend, but is there something real here or is it just hype?
Daft Extensions Featuring daft-h3: Native Rust Performance, Community Owned
Daft now supports native extensions via Apache Arrow's C Data Interface. daft-h3 is the first community extension — 9 Rust-native H3 geospatial functions, 3–16x faster than Python UDFs.
Daft v0.7.10: 30 contributors, 41 new features, distributed asof joins
30 contributors shipped Daft v0.7.10 — the most participation in any Daft release to date. The result: 41 new features and functions across distributed joins, duplicate detection, temporal arithmetic,
Audio transcription at scale with daft.AudioFile
How to transcribe thousands of audio files with Whisper using daft.AudioFile — handling resampling, silence splitting, and worker-resident model loading without the boilerplate.
Image Embeddings: Tutorial & Examples
Learn about the concept of image embeddings, their various use cases, and best practices for handling them in data processing workflows.
daft.File: Lazy Metadata Filters
Filter millions of files by path, size, and content type before opening any of them. Cheap operations first, expensive operations on the survivors.
Multimodal Embeddings: Tutorial & Examples
Learn multimodal embedding techniques for cross-modal search, recommendation systems, and content moderation applications.
Daft v0.7.9: Temporal Arithmetic, Video Frame Decoding, and Native UUID
Migrating ETL workloads from Spark means hitting gaps in date arithmetic — functions like `date_add`, `date_diff`, and epoch conversions that Spark users take for granted. Daft v0.7.9 closes that gap
