DISCURSIVE
The Pi0-Fast Libero-10 Baseline Is 25 Points Low
Nvidia's Openness Promise Leaves Out Hosting, Gating and Licensing
Perceptron Ships 36B Robot Weights Under Apache-2.0
Model Success Rate May Count the Wrong Runs
RoboDojo Scores 32 of 34 Robot Policies Under 10% Success
Dyna-2: A Million Hours of Human Video, Zero Robot Frames
Gemini Robotics Released One Policy from Feet to Fingertips
5k Hours of Tactile Data, and Four Ways to Get It
Nvidia Puts a 4B World Model on the Robot [Weekly Physical AI Roundup]
Turning robot video into training-ready data
Xiaomi Opens a 38B World Model Built to Generate Robot Data
Querying Physical AI Data with Daft
LeRobot v0.6.0 Adds World Models, Reward Models, and an Open GR00T
A Push on Tactile Data, and a Warning That the Benchmark Was Leaking
Hours of Humanoid Teleop, Recorded in Real Homes
Knowledge curation (not search) is the AI big data problem
Cutting LLM Batch Inference Time by Half with Dynamic Prefix Bucketing
Agentic systems are just query engines for unstructured data
Benchmark: Spark vs. Ray Data vs. Daft on Multimodal Workloads
Show HN: Flotilla, the Distributed Engine for Multimodal Pipelines
Profiling multimodal workloads: lessons from Daft
Processing 24T tokens for LLM training with 0 crashes (what made it possible)
We Hit 100% GPU Utilization–and Then Made It 3× Faster by Not Using It
Elasticsearch Was Great, but Vector Databases Are the Future
Have you faced any challenges of using Elasticsearch for vector search?
We heard from many that it'll get expensive quickly, and the performance is suboptimal. Any thoughts?
BGE-M3 vs. Splade
Enhance information retrieval with learned sparse embeddings
Re:The Illustrated Word2Vec
on Friday April 19, 2024 @06:29PM (#40092640)
Yeah, we usually just say vector embeddings are the numerical representation of that piece of unstructured data. This glossary page put it together quite nicely. https://zilliz.com/glossary/vector-embeddings