Optimizing Memory and Retrieval for Graph Neural Networks with WholeGraph

Nvidia introduced WholeGraph as a breakthrough designed to optimize memory storage & retrieval for large-scale #GNN training

This post evaluates its performance

#AI #EmergingTech

buff.ly/4cUrpNp

Graph experts #JobAlert :

The Microsoft Fabric Graph team in Barcelona is hiring

Software Engineer and Manager roles of varying seniority levels.

#Azure #Microsoft #Graph #Analytics #Graph DB

buff.ly/3xuD3yu

.Aerospike closes $109M in growth capital investment

As CEO noted, the funding will be used investment to take innovation to the next level and meet growing demand for Aerospike’s graph & vector solutions

#GraphDB #AI #Funding #Business #Market #News

buff.ly/4ajJ7bJ

Exploring the Potential of Large Language Models in Graph Generation with LLM4GraphGen

* Understanding of structure rules
* Ability to capture structural type distributions
* Utilization of domain knowledge

#AI #LLMs #EmergingTech #Research #DataScience

buff.ly/3IY0Jhf

Connected Data London is back, and we want YOU to be part of the journey!

Due to popular demand, we are extending our poll for a few more days.

Share your thoughts, shape our agenda, and win a FREE ticket to the London 2024 event to chart the course together for a data-driven…

.@Neo4j partners w Microsoft, unfolds strategy to power #GenAI apps w #cloud platforms & Graph RAG

We caught up w Sudhir Hasbe to discuss how this works & what it means, domain landscape & Neo4j's strategy

Next up, Databricks & Snowflake

#GraphDB #AI #LLMs

buff.ly/4aaRRkg

Constructing Knowledge Graphs: A Guide to Using OpenAI and Pyvis

KGs offer a powerful tool for data exploration & insights

This guide introduces concepts & details the creation process using #LLMs

#AI #DataScience #KnowledgeGraph #Python #Tutorial

buff.ly/498FFix

Do you want to talk to the thought leaders in Language Models, Ontologies and Knowledge Graphs?

You will soon get your chance to in the upcoming Connected Data London 2024, but till then..another day, another AI Assistant by Jay Yu.

After Mike Dillinger and Tony Seale,…

Interested in Applications of Network Science and Graph #MachineLearning in #DataScience ?

#CfP for researchers & early career scientists to showcase their work @ SIAM Conference on Mathematics of Data Science;

Open till April 1

#AI #Analytics #Research

buff.ly/43z3XkG

All machine learning models are best expressed as graphs

Efficient processing of graph-based networks involves large sparse data structures that consist of mostly zero values, and next generation architectures should avoid unnecessary processing.

Graph processing is the key to…

🔥 #AI Model for Personalized Audiobook Recommendations at Spotify 🎧

#GNNs & two-tower models
📚 Handles data sparsity
⚡ Decouples user-item interactions for scalability & latency
💡 Leverages podcast preferences for audiobooks; boost by 23% / 46%

buff.ly/43rHAxx

Talk like a graph: Encoding graphs for large language models

Teaching #LLMs to reason w graphs

Performance depends on:
1) The graph encoding method
2) The nature of the graph task
3) The structure of the graph

#AI #Research #EmergingTech #DataScience

buff.ly/3TgE5Ft

The Limitations of Cosine Similarity and the Case for Knowledge Graphs in AI

A big part of the underlying assumptions for AI built upon vector similarity. The notion that using embeddings to represent concepts, metrics like cosine similarity can retrieve relevant information.…

🧠 New Graph Neural Network Technique 🔥

NVIDIA researchers developed WholeGraphStor, a novel #GNN memory optimization

Storing entire graphs in a compressed format reduces memory footprint, accelerates training/inference

#EmergingTech #AI #DataScience

buff.ly/49Ok5RL

A Survey of Graph Neural Networks in the real world: Imbalance, Noise, Privacy and OOD Challenges

Graph-structured data exhibits universality and widespread applicability across diverse domains, such as social network analysis, biochemistry, financial fraud detection, and…

PyGraft: An #OpenSource Tool for Synthetic #KnowledgeGraphs

KG challenges:
- Limited/biased benchmark datasets 
- Data privacy
- Need for diverse datasets to evaluate #ML

PyGraft addresses these, providing a way to generate realistic synthetic KGs

#AI

buff.ly/4a4tmEQ

Would you like to help shape our next event, and win a free ticket?

Our poll is still running!

If you are a Knowledge Graph, Graph Data Science / AI, Graph Database and Semantic Technology professional or enthusiast, here's your chance.

In anticipation of the return of…

What do graphs have to do with novel hardware architectures for AI workloads?

The Connected Data podcast is back featuring a panel that explores the interrelationship between graph processing and novel AI hardware architectures.

Hosted by ZDNet's Tiernan Ray with panelists…

AI for Complex Networks: Potential, Methodology & Application

#Research reviews potential advantages of #AI in overcoming complex network challenges

Includes Graph embeddings, Graph #neuralnetworks , Dynamic graph learning

#Networks #Science #Analytics

buff.ly/48I5Hcr

Neural Scaling Laws on Graphs

New #research investigates scaling properties of deep graph models such as graph #neuralnetworks & transformers

Verifies validity on graphs, establishes formulations to describe scaling

#EmergingTech #AI #DataScience

buff.ly/4326WSA