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DISCURSIVE

26 karmajoined 11 lat temu

Submissions

Querying Physical AI Data with Daft

eventual.ai
1 points·by DISCURSIVE·4 dni temu·0 comments

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

topicqueue.substack.com
1 points·by DISCURSIVE·5 dni temu·0 comments

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

topicqueue.substack.com
2 points·by DISCURSIVE·12 dni temu·0 comments

Hours of Humanoid Teleop, Recorded in Real Homes

topicqueue.substack.com
3 points·by DISCURSIVE·19 dni temu·0 comments

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

daft.ai
3 points·by DISCURSIVE·6 miesięcy temu·0 comments

Cutting LLM Batch Inference Time by Half with Dynamic Prefix Bucketing

daft.ai
2 points·by DISCURSIVE·8 miesięcy temu·0 comments

Agentic systems are just query engines for unstructured data

daft.ai
3 points·by DISCURSIVE·8 miesięcy temu·0 comments

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

daft.ai
1 points·by DISCURSIVE·9 miesięcy temu·0 comments

Show HN: Flotilla, the Distributed Engine for Multimodal Pipelines

daft.ai
2 points·by DISCURSIVE·10 miesięcy temu·0 comments

Profiling multimodal workloads: lessons from Daft

daft.ai
1 points·by DISCURSIVE·10 miesięcy temu·0 comments

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

daft.ai
1 points·by DISCURSIVE·11 miesięcy temu·0 comments

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

daft.ai
17 points·by DISCURSIVE·11 miesięcy temu·11 comments

Elasticsearch Was Great, but Vector Databases Are the Future

thenewstack.io
16 points·by DISCURSIVE·2 lata temu·7 comments

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

1 points·by DISCURSIVE·2 lata temu·0 comments

BGE-M3 vs. Splade

zilliz.com
1 points·by DISCURSIVE·2 lata temu·0 comments

Enhance information retrieval with learned sparse embeddings

zilliz.com
1 points·by DISCURSIVE·2 lata temu·0 comments

The emerging trend of vector databases

zilliz.com
2 points·by DISCURSIVE·2 lata temu·0 comments

The Future of Vector Database

zilliz.com
1 points·by DISCURSIVE·2 lata temu·0 comments

Milvus Supports NVDIA's Graph Index

zilliz.com
2 points·by DISCURSIVE·2 lata temu·0 comments

Zilliz Cloud Jan 2024 Launch

zilliz.com
1 points·by DISCURSIVE·2 lata temu·0 comments

comments

DISCURSIVE
·2 lata temu·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 lata temu·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 lata temu·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.