That's a valid point. The team tried hard to decontaminate the data. Also note that there's generalization into more challenging benchmarks such as HiddenMath and IMO-Bench.
DATA
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Perfect AI retrieval enabling personal assistants with long-term memory
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It all depends on how perfect will be the retrieval, reasoning and integration over all those tokens. Assuming it will be perfect: 1) personal assistant with long-term memory, remembering all my preferences, learned skills, chats, me using my desktop etc 2) upload the entire
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Private AI Models and Stable Diffusion Training Data Explained
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Yep, he suffers from extreme levels of Low IQ, thank his parents I don't train on private data The users upload their own 20-30 photos, create their own private AI model, and take private AI photos with that The base models from Stable Diffusion are trained on public web data
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Data Privacy in AI Training: Slack vs Stable Diffusion
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Slack is training on messages in a PRIVATE community Stable Diffusion is trained on LAION, a data set of PUBLIC images on the internet You not seeing the difference on purpose to make a point shows you're a low IQ nitpicking nerd
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AI Training Data Privacy: Slack vs Stable Diffusion
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Slack is training on private messages in a private community Stable Diffusion is trained on LAION, a data set of public images on the internet
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Molly Harras Wins 2024 Grand Prix Analytics Championship
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A huge congrats to Molly Harras on winning the 2024 Grand Prix! This victory is even more special as it marks the 15th anniversary of this incredible event. Here's to celebrating your remarkable achievement and 15 years of data brilliance! #AnalyticsForAll #AlteryxInspire pic.twitter.com/yBSzh8qdfU
— Alteryx (@alteryx) 18 mai 2024A huge congrats to Molly Harras on winning the 2024 Grand Prix! This victory is even more special as it marks the 15th anniversary of this incredible event. Here's to celebrating your remarkable achievement and 15 years of data brilliance! #AnalyticsForAll #AlteryxInspire
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AI Integration Simplifies MLOps and ETL Pipeline Complexity
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By bringing AI directly to data developers and organizations can avoid the complexity of building and integrating MLOps and ETL pipelines as well as migrating and duplicating data across multiple environments. Check this out: https://
superduperdb.com -
Open-source Framework for Building AI Applications in Databases
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AI in your Database. An open-source framework for building AI Applications right in your databases:
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SuperDuperDB Simplifies AI Integration on Existing Data Infrastructure
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SuperDuperDB eliminates complex MLOps pipelines, specialized vector databases – and the need to migrate and duplicate data by integrating AI at the data’s source, directly on top of your existing data infrastructure. This simplifies building and managing AI applications.
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LLMs Transform Retail: GenAI Unlocks $660 Billion Potential
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Discover how Large Language Models (LLMs) are transforming retail! From enhanced customer service to streamlined logistics, GenAI could unlock $660 billion for retailers. Our experts explore how to use advanced RAG pipelines and function calling for AI agents in retail. Delve