bobvanluijt

10 ms·

91.
State of Databases Survey 2023(stateofdb.com)
5 points by bobvanluijt 3y ago|0 comments
92.
by bobvanluijt 3y ago
[...] mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE.
93.
MeshCODE: A unified theory of storing binary data in the brain(frontiersin.org)
3 points by bobvanluijt 3y ago|1 comments
94.
Discovery: Metals can heal themselves(newsreleases.sandia.gov)
90 points by bobvanluijt 3y ago|28 comments
95.
by bobvanluijt 3y ago
Article in nature: https://www.nature.com/articles/s41586-023-06223-0
96.
Otomi – Self-Hosted PaaS for Kubernetes(github.com)
1 points by bobvanluijt 3y ago|0 comments
97.
The open source learning curve for AI researchers(supervised.news)
155 points by bobvanluijt 3y ago|35 comments
98.
by bobvanluijt 3y ago
Ooo very cool
99.
Explainer Video – Lost in the Middle: How Language Models Use Long Context(youtube.com)
5 points by bobvanluijt 3y ago|3 comments
100.
by bobvanluijt 3y ago
Based on this research paper: https://arxiv.org/pdf/2307.03172.pdf
101.
by bobvanluijt 3y ago
It was great fun!
102.
The Future of LLMs with Arthur, MosaicML, LangChain, and Weaviate [video](youtube.com)
64 points by bobvanluijt 3y ago|2 comments
103.
Weaviate OSS Vector Database(github.com)
2 points by bobvanluijt 3y ago|1 comments
104.
Weaviate 1.20 Released(weaviate.io)
6 points by bobvanluijt 3y ago|1 comments
105.
by bobvanluijt 3y ago
* Multi-tenancy – A scalable, efficient and easy solution for use-cases with many tenants per Weaviate cluster. * PQ + Re-scoring – Product quantization (PQ) allows for faster vector search - now at basically no cost to accuracy! * Autocut
106.
Unstructured – OSS libraries and APIs to build custom preprocessing pipelines(github.com)
3 points by bobvanluijt 3y ago|0 comments
107.
Revolutionizing AI Search with Weaviate: An Interview with CEO Bob van Luijt(devblogs.microsoft.com)
4 points by bobvanluijt 3y ago|1 comments
108.
by bobvanluijt 3y ago
This was a fun interview, maybe others like it too.
109.
Thoughts on Pricing a Vector Database
6 points by bobvanluijt 3y ago|1 comments
110.
by bobvanluijt 3y ago
Congrats! Very cool. I also love the collaboration with Weaviate!
111.
by bobvanluijt 3y ago
Very cool!
112.
What Neeva's quiet exit tells us about the future of AI startups(supervised.news)
121 points by bobvanluijt 3y ago|89 comments
113.
How to Create Your Own ChatGPT Plugin(weaviate.io)
3 points by bobvanluijt 3y ago|0 comments
114.
We Just Launched a Tom’s Hardware AI Chatbot. Here's Why(tomshardware.com)
4 points by bobvanluijt 3y ago|1 comments
115.
by bobvanluijt 3y ago
Also, the concept of generative feedback loops is described here: https://weaviate.io/blog/generative-feedback-loops-with-llms
116.
Why large context windows are a good thing for vector DBs (and vice versa)
16 points by bobvanluijt 3y ago|2 comments
117.
by bobvanluijt 3y ago
That depends a bit on the scale and use case specifics. But commoditized billion-scale vector search is indeed a thing. We published this for Weaviate in December last year https://weaviate.io/blog/sphere-dataset-in-we
118.
by bobvanluijt 3y ago
Thanks, that's nice feedback
119.
by bobvanluijt 3y ago
Weaviate ( https://weaviate.io ) | REMOTE (US / Europe) Weaviate is an open-source vector database. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of
120.
by bobvanluijt 3y ago
Ha, great question! Coincidentally, at Weaviate, we are thinking about this too! There are a few ways to do this with AirByte ( https://docs.airbyte.com/integrations/destinations/weaviate/ ) or (potentially) wi

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