Source2Synth Synthetic Data Generation and Curation Grounded in Real Data Sources discuss: https://
huggingface.co/papers/2409.08
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… Large Language Models still struggle in challenging scenarios that leverage structured data, complex reasoning, or tool usage. In this paper, we propose
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Source2Synth: Synthetic Data Generation from Real Data Sources
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Production ML Acceleration and Compound AI Systems in Enterprises
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What’s driving the acceleration of production ML? Why are enterprises choosing compound AI systems? This episode of The Ravit Show answers these questions and deep dives into findings from the State of Data + AI report. Watch here: https://
dbricks.co/4dWTcNn @RavitJain -
Smart Factory Logistics Automation Eliminates Manual Inventory Processes
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⚙️ Innovative Inventory Solutions! Learn how @BossardAmerica’s Smart Factory Logistics system detects part usage, triggers reorders and eliminates manual processes. Watch Scott Hunt’s full demo at #IMTS2024! #sponsored #bossard_iiot #Industry40 #LogisticsTech @GregorianCT1 pic.twitter.com/eyYrRxOXhr
— Lucian Fogoros (@fogoros) 12 septembre 2024Innovative Inventory Solutions! Learn how @BossardAmerica’s Smart Factory Logistics system detects part usage, triggers reorders and eliminates manual processes. Watch Scott Hunt’s full demo at #IMTS2024! #sponsored #bossard_iiot #Industry40 #LogisticsTech @GregorianCT1
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French Audio Datasets Available on Hugging Face Platform
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peut être ici: https://
huggingface.co/datasets?modal
ity=modality:audio&language=language:fr&sort=trending
… cc @sanchitgandhi99 @yoachlacombe @eustachelb -
Web-Scale Data: Legal Risks and Compliance Requirements
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Voilà! Overall, dealing with web-scale data is inherently risky and requires due care and good faith to reduce legal risk. In lawsuits, the burden of proof quickly shifts onto the defendants (because it's an affirmative defense) and they need to provide evidence of compliance.
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Fair Use Licensing for AI Datasets: Legal Compliance Strategy
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Use an appropriate license compatible with Fair Use. LAION's creation of the dataset required one or more Copyright Exceptions with strict terms. Picking a license that respects the terms of these exceptions would reduce legal risk significantly, and show good faith.
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Partner with IWF upfront to prevent illegal content in AI datasets
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Partner with IWF upfront, not when problem arise! LAION knew about the risks of illegal content (e.g. child abuse) being in their dataset. It would have been sensible to partner with professional organizations like IWF to check files *before* publishing the dataset.
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User Generated Content Exclusion from AI Training Datasets
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Exclude social media and UGC websites. Popular websites that host user generated content or personal profiles could have been excluded from the dataset. Platforms don't have full rights to their users private information, and avoiding that kind of content reduces legal risk.
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LAION criticized for partnering with questionable data hosting site
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Don't partner with dubious websites to host files! LAION shouldn't have requested TheEye, a questionable "archival" website, to host their data in order for them to link to it! Maybe instead get approval from platforms like HF so they share legal responsibility for hosting.
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Respecting Manual Opt-Out Requests After Fact
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Provide opt-out after the fact. To operate in good faith, manual opt-out requests should also be respected after the fact too. Because the dataset format allows users to bypass and override opt-out client side, not honoring request makes LAION look complicit in infringement.