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Explore how human-in-the-loop AI empowers communication assistance, overcoming complex challenges in our remote-first reality for clearer, more effective writing.
Explore human-in-the-loop machine learning applications at JPMorgan Chase, focusing on practical datasets and methodologies in computer vision and natural language processing.
Explore MLCommons' mission to transform machine learning through benchmarks, best practices, and data. Learn about public datasets' importance and the organization's tools for dataset creation.
Explore responsible data-centric AI in healthcare with Stanford expert James Zou. Learn about ML algorithms for biomedical applications, deployment challenges, and data evaluation techniques.
Explore how addressing data issues can improve machine learning models, focusing on cost-effective solutions and identifying crucial data problems to optimize resources.
Explore challenges and opportunities in detecting data distributional shift, a crucial aspect of AI robustness and reliability in real-world applications.
Learn strategies for effective data selection in AI, focusing on quality over quantity to enhance model performance and efficiency.
Leverage NLP to rapidly analyze vast climate change literature, extracting key trends and insights. Scale labeling process for 600,000 research articles using Snorkel AI, enabling efficient data-driven climate risk assessment.
Explore Landing AI's journey in democratizing AI, focusing on manufacturing challenges, data-centric techniques, and the evolution of Landing Lens for faster iteration and improved performance.
Explore DataPerf, a benchmark suite for evaluating ML data quality and optimization algorithms. Learn about the need for data-centric AI benchmarks to advance research and improve real-world applications.
Learn techniques for rapidly creating annotated training data to build accurate and robust AI systems using clinical reports.
Explore KeyBank's innovative recommender systems for enhancing banker productivity. Learn about challenges, opportunities, and data-centric approaches in financial sector implementation.
Explore how machine learning and high-quality data can revolutionize drug development, predicting outcomes and designing safer, more effective therapies faster and at lower costs.
Explore data-centric AI in pharma: personalized doctor education, patient treatment optimization, and real-world data utilization for predictive modeling at AstraZeneca.
Discover AI-powered tools for cleansing datasets, enhancing model training accuracy. Explore Cleanlab's innovative approach to data-centric AI and its practical applications.
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