Daniel Lokshtanov’s work explores the limits of what computers can solve, paving the way for advances in artificial intelligence and computational efficiency.
With its new ‘Computer’ tool, the generative AI firm hopes to make it easier for companies to glean new context from often-siloed data.
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New framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysis
BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the ...
Debate and discussion around data management, analytics, BI and information governance. In a guest blogpost, Neo4j’s Alyson Welch explains why Large Language Model AI systems can’t move beyond ...
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Graph-based AI model finds hidden links between science and art to suggest novel materials
Imagine using artificial intelligence to compare two seemingly unrelated creations—biological tissue and Beethoven's "Symphony No. 9." At first glance, a living system and a musical masterpiece might ...
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