Building and navigating attribution graphs for Large Language Models
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Open-sourcing circuit tracing tools
The Dataverse Project: 750K FAIR Datasets and a Living Knowledge Graph
"I'm Ukrainian and I'm wearing a suit, so no complaints about me from the Oval Office" - that's the start of my lecture about building Artificial Intelligence with Croissant ML in the Dataverse data platform, for the Bio x AI Hackathon kick-off event in Berlin. https://lnkd.in/ePYHCfJt
* 750,000+ FAIR datasets across the world forcing the innovation of the whole data landscape.
* A knowledge graph with 50M+ triples.
* AI-ready metadata exports.
* Qdrant as a vector storage, Google Meta Mistral AI as LLM model providers.
* Adrian Gschwend Qlever as fastest triple store for Dataverse knowledge graphs
Multilingual, machine-readable, queryable scientific data at scale.
If you're interested, you can also apply for the 2-month #BioAgentHack online hackathon:
• $125K+ prizes
• Mentorship from Biotech and AI leaders
• Build alongside top open-science researchers & devs
More info: https://lnkd.in/eGhvaKdH
model2owl: Transform UML into a formal OWL ontology and SHACL shapes
Transform UML into a formal OWL ontology and SHACL shapes - OP-TED/model2owl
Knowledge Representation Markup Language (KRML)
What if creating Linked Open Data was less like coding and more like writing? Could anyone extend the Semantic Web by sharing a document? Publish a knowledge… | 13 comments on LinkedIn
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph…
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
✨ Attention Information Extraction Enthusiasts ✨ I am excited to announce the release of our latest paper and model family, ReLiK, a cutting-edge… | 33 comments on LinkedIn
MLX-graphs — mlx-graphs 0.0.3 documentation
Apple presented MLX-graphs: the GNN library for the MLX framework specifically optimized for Apple Silicon. Since the CPU/GPU memory is shared on M1/M2/M3, you don’t have to worry about moving tensors around and at the same time you can enjoy massive GPU memory of latest M2/M3 chips (64 GB MBPs and MacMinis are still much cheaper than A100 80 GB). For starters, MLX-graphs includes GCN, GAT, GIN, GraphSAGE, and MPNN models and a few standard datasets.