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DISCURSIVE

26 karmajoined 11 tahun yang lalu

Submissions

Querying Physical AI Data with Daft

eventual.ai
1 points·by DISCURSIVE·4 hari yang lalu·0 comments

LeRobot v0.6.0 Adds World Models, Reward Models, and an Open GR00T

topicqueue.substack.com
1 points·by DISCURSIVE·5 hari yang lalu·0 comments

A Push on Tactile Data, and a Warning That the Benchmark Was Leaking

topicqueue.substack.com
2 points·by DISCURSIVE·13 hari yang lalu·0 comments

Hours of Humanoid Teleop, Recorded in Real Homes

topicqueue.substack.com
3 points·by DISCURSIVE·20 hari yang lalu·0 comments

Knowledge curation (not search) is the AI big data problem

daft.ai
3 points·by DISCURSIVE·6 bulan yang lalu·0 comments

Cutting LLM Batch Inference Time by Half with Dynamic Prefix Bucketing

daft.ai
2 points·by DISCURSIVE·8 bulan yang lalu·0 comments

Agentic systems are just query engines for unstructured data

daft.ai
3 points·by DISCURSIVE·8 bulan yang lalu·0 comments

Benchmark: Spark vs. Ray Data vs. Daft on Multimodal Workloads

daft.ai
1 points·by DISCURSIVE·9 bulan yang lalu·0 comments

Show HN: Flotilla, the Distributed Engine for Multimodal Pipelines

daft.ai
2 points·by DISCURSIVE·10 bulan yang lalu·0 comments

Profiling multimodal workloads: lessons from Daft

daft.ai
1 points·by DISCURSIVE·10 bulan yang lalu·0 comments

Processing 24T tokens for LLM training with 0 crashes (what made it possible)

daft.ai
1 points·by DISCURSIVE·11 bulan yang lalu·0 comments

We Hit 100% GPU Utilization–and Then Made It 3× Faster by Not Using It

daft.ai
17 points·by DISCURSIVE·11 bulan yang lalu·11 comments

Elasticsearch Was Great, but Vector Databases Are the Future

thenewstack.io
16 points·by DISCURSIVE·2 tahun yang lalu·7 comments

Have you faced any challenges of using Elasticsearch for vector search?

1 points·by DISCURSIVE·2 tahun yang lalu·0 comments

BGE-M3 vs. Splade

zilliz.com
1 points·by DISCURSIVE·2 tahun yang lalu·0 comments

Enhance information retrieval with learned sparse embeddings

zilliz.com
1 points·by DISCURSIVE·2 tahun yang lalu·0 comments

The emerging trend of vector databases

zilliz.com
2 points·by DISCURSIVE·2 tahun yang lalu·0 comments

The Future of Vector Database

zilliz.com
1 points·by DISCURSIVE·2 tahun yang lalu·0 comments

Milvus Supports NVDIA's Graph Index

zilliz.com
2 points·by DISCURSIVE·2 tahun yang lalu·0 comments

Zilliz Cloud Jan 2024 Launch

zilliz.com
1 points·by DISCURSIVE·2 tahun yang lalu·0 comments

comments

DISCURSIVE
·2 tahun yang lalu·discuss
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
DISCURSIVE
·2 tahun yang lalu·discuss
Yup. Back in time, they wrote an article about cloud repatriation (https://a16z.com/the-cost-of-cloud-a-trillion-dollar-paradox...) and used a very nich use cases to extrapolate to all the cloud workload just to support their own portfolio company. So many people in the industry just thought it was a joke:)
DISCURSIVE
·3 tahun yang lalu·discuss
In the past six months since I started to work on the vector database space, I keep hearing from developers that the phase before they can convert unstructured data into vector embeddings is the most challenging part. Hence we released this Pipelines product in public preview, aiming at solvelve this problem. We would really appreciate your feedback and comments to see if this is a viable path.