See how Snorkel helped build a labeled dataset to gain crucial insights into key climate change trends. https://
buff.ly/4b0gKPS #naturallanguageprocessing #datalabeling
@snorkelai
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Snorkel Builds Climate Change Dataset Through Data Labeling
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Data-efficient robustness improvement for foundation models
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Exciting work from our academic collaborators! Foundation models often struggle out of the box—and @dyhadila & collaborators propose a new data-efficient way to make them robust!
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Machine Learning Cost Problem: Data and Model Optimization
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Dr. Ce Zhang, Professor in Computer Science at ETH Zürich delves into machine learning's cost problem, the interrelation of data and model problems, and how to discern valuable data problems from those that can needlessly consume time and resources. https://
buff.ly/3wfsYoS -
Making NLP Accessible to All Languages: Bridging Global Gaps
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How do we make NLP accessible to all languages, not just the dominant few? Sebastian Ruder, a Research Scientist at Google leads a thought-provoking discussion on the future of NLP and its potential to bridge language gaps in technology. https://
buff.ly/4bjMD5L -
Fine-tuning LLMs with Enterprise Data for Business Automation
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While Llama 3 and Phi-3 are amazing breakthroughs, they must be trained on enterprise data before they can be trusted to automate critical business functions. AI data development is the key to fine-tuning LLMs for domain-specific tasks. https://
buff.ly/3UpUVST -
AI accuracy depends on training data quality and enterprise development
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Dataconomy is spot on. The accuracy of AI depends on the data it's trained on. Incorporating enterprise data in AI/ML models is difficult and time-consuming. That's why AI data development is so critical. Read the full story: https://
buff.ly/4a3VqrA -
Latest Machine Learning Research: Weak Supervision and Information Theory
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Stay informed about the latest machine learning research with the University of Wisconsin's Frederic Sala and Snorkel AI's Paroma Varma, co-founder and Head of Machine Learning. https://
buff.ly/4dnVHIz #machinelearning #informationtheory #weaksupervision #AI #education" -
Microsoft Advances in Speech, Translation, Captioning, and NLP
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Hear about Microsoft's AI breakthroughs in speech recognition, machine translation, image captioning, and most notably, NLP. https://
buff.ly/3JJXjip -
Smithsonian Institution Leverages AI for Data-Driven Insights
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The Smithsonian Institution is stepping into the future with data-driven AI projects. Mike Trizna of the Smithsonian Data Science Lab is leveraging AI to transform the Smithsonian's wealth of data into actionable insights. https://
buff.ly/3UE0sqa -
Weak Supervision in AI: Automation and LLM Integration
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Explore the future of weak supervision in AI and get in-depth insights on automating the weak supervision pipeline, multimodal integration, and the intersection of weak supervision with large language models. https://
buff.ly/4b0h9BS