"compute isn't primarily for training. It's for creating better data" => watch this space – cool things coming soon
DATA
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LLM Privacy: Protecting Sensitive Data from Accidental Exposure
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6. Privacy matters more than ever LLMs can accidentally expose sensitive information if you’re not careful. Learning to use them responsibly isn’t optional—it’s a must. (Unless you want to be the person who accidentally leaks proprietary data)
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Databricks Supports Virtue Foundation Global Health Data Initiative
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We're thrilled to support the Virtue Foundation in its mission to advance global health. As part of our #DatabricksForGood initiative, we helped build a solution to keep core datasets up-to-date, accurate, and readily accessible. These datasets are integrated into a #GenAI
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DeepSeek Privacy: US/EU Hosted Open Source Model
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DeepSeek on Perplexity is hosted in US/EU data centers – your data never leaves Western servers. The open source model is hosted completely independent of China. Your privacy and data security is our priority.
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Free MLops Repository with Talks Books and Papers
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This repository on ML operations has free talks, books, papers and more: https://
bit.ly/MLops Developed by @visenger -
Document Databases and AI Workloads: Compatibility Myths Debunked
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"Equivalent" . It might be good (and I hope it *is* good in its own right – JSON-native, document-style databases are critical for AI workloads, in particular), but let's not play make believe on compatibility. (Note F's 2.0 blog where they ack perf/etc has been relative)
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Synthetic Data’s Role in AI Training and Data Privacy
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Ahead of #DataPrivacyDay, SAS' Brett Wujek explains the valuable link between the protection of personal data and synthetic data. Within just a few years, about half of the data used to train AI will be synthetic. This matters for you and your business. http://
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Data Mix Specification Impact on Model Performance
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unclear tbh, data mix is not specified. probably is the big reason for performance
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Business AI Strategy Focus: Agents, Data, Training 2025
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Here’s where we predict businesses will focus their efforts in 2025:
– Infrastructure: Scaling AI agents & systems.
– Data Advantage: Leveraging data for a competitive edge.
– AI Training: Driving adoption & human-in-the-loop processes. How is your organization strategizing with -
RL Model Achieves Superhuman Snark on Human Cope Chains
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applying large-scale RL to chains of cope written by human seethers, we observe an “lmao moment” upon which the model spontaneously exhibits superhuman snark