What could you build if you had the embeddings of ALL of wikipedia? The Embedding Archives: Millions of Wikipedia Article Embeddings in Many Languages https://
hubs.li/Q01Mg6_C0 We’re publishing ~100 million embedding vectors, covering Wikipedia in 10 languages. Get them now!
AI
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Wikipedia Embeddings Archives: 100 Million Vectors Across 10 Languages
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erwin Data Modeler Enables Lakehouse Data Structure Visualization
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#Lakehouse @erwininctweets Data modelers can now model and visualize lakehouse data structures with erwin Data Modeler to build Logical and Physical data models that fast-track their migration. Learn more
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LTM Library Release: Long-Term Memory for AI Systems
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We will release our LTM (long-term memory) library in a week or two. It's a layer above the vector database, helping you store and retrieve memories and pre-process and post-process them to maximize retrieval quality. We have focused on dialogue memories but plan to look at
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Climate Modeling with Limited Data: Key Research Challenges
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@rendx gave a great talk today tackling the major challenges of modelling when assessing climate and risk impacts when data is limited, which affects so much of the world. We need more work with this focus.
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Active Learning Enhances Antarctic Climate Research Understanding
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Great presentation from @tom_r_andersson on day 2 @Climformatics Active learning improve how we understand the Antarctic. Impressive work. See the paper here: https://
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Congratulations on Important Achievement After Years of Hard Work
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Congratulations to the many people who worked hard on this over multiple years. There's a long way to go, but this is an important start. Congrats to Samy Bengio, @rajiinio @SashaMTL for guiding this over the line.
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GroqChip Advantages in HPC with Large Data Structures
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Register to hear from Ernesto Bonomi about GroqChip™ advantages and use in HPC calculations with dense and large data structures. #AI #DataAnalysis #HPC https://
eventbrite.it/e/biglietti-hi
gh-performance-computing-on-tensor-streaming-processors-for-large-scale-619612526747
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NIST Funding: Advancing AI Evaluation Standards and Transparency
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With more funding NIST could: design novel evaluations, investigate the scientific validity of existing evaluations, develop technical standards for how to red team AI systems, design disclosure standards to enhance transparency, and more.
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Congress Investment in NIST for Safer AI Systems
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As Congress evaluates funding levels for 2024, we encourage it to consider an ambitious investment in NIST as a strong step towards creating safer, more innovative AI systems. You can read more in our full post here:
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NIST AI Budget Increase Proposal Reaches Fifteen Million Dollars
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Our proposed $15 million increase is 3X NIST’s requested AI budget, but this figure is not unprecedented – it’s the same amount of funding requested for FY 2022 and FY 2023 (these requests were ultimately only partially met).