Eventual Blog

open source · Everett Kleven

What I learned re-evaluating VLADBench on the latest VLMs

GPT-6 Astra and Claude Opus 5.5 top the leaderboard, but the cost-performance frontier is a more interesting story.

open source · YK Sugi

Cutting dead frames from DROID: 500 hours of robot data in 32 seconds

The robot state recorded next to the video tells you which frames matter before you decode any pixels. Trimming all of DROID takes 32 seconds on a laptop.

open source · YK Sugi

How we made our LeRobot video reader up to 15× faster

LeRobot has emerged as the dominant open format for robot learning data, but decoding frames is expensive. Here's how we made Daft's native LeRobot reader up to 15× faster.

open source · Shreyas Garimella

Finding a Needle in the Haystack: Querying Physical AI Data with Daft

Pose + semantic search over Apple's EgoDex hand-manipulation dataset with Daft: SigLIP embeddings meet hand-pose geometry. Ctrl+F for physical AI data.

open source · Colin Ho, Chris Kellogg

Disk is the data plane: Flight Shuffle in Daft

How Daft rebuilt distributed shuffle around Arrow Flight, local disk, and streaming reads to handle multi-terabyte workloads.

open source · Euan Lim

Scaling As-of Joins

How we built, broke, and re-built our ASOF joins — 5.5x faster, half the memory of pandas, and scaled to a distributed cluster.

open source · Daft Team

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.

open source · Desmond Cheong

Multimodal Embeddings: Tutorial & Examples

Learn multimodal embedding techniques for cross-modal search, recommendation systems, and content moderation applications.

open source · ByteDance Volcano Engine (Volcengine LAS Team)

Tuning Daft's Distributed UDFs: Lessons from ByteDance

Learn from the ByteDance Volcengine LAS Team on how to optimize Daft UDFs on Ray. Discover the formula to evenly distribute data across actors.

open source · Cory Grinstead

Introducing Dynamic Batching: Auto-Tuning for Daft Pipelines

Manually tuning batch sizes is hard. So I implemented dynamic batching to never deal with it ever again.

open source · YK Sugi

How We Use AI Coding Agents

Our engineering team's best practices for working with AI coding agents.

open source · Everett Kleven

Multimodal Structured Outputs: Evaluating VLM Image Understanding at Scale

Leveraging ablation for contrastive image understanding evaluation in Daft

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Eventual Blog | Data Curation for Physical AI