Latest posts
- How a big four consulting firm used NLP to monitor news for audits with Snorkel Flow
- A big four consulting company wanted to use AI to analyze news articles and extract crucial information that would be helpful to their vast team of auditors. Using Snorkel Flow, the data science team was able to automate data labeling and build an NLP application in a matter of days… ... - Building Trustworthy AI applications with data-centric AI
- AI is generally accepted as necessary for organizations across private and public sectors to build (or maintain) a competitive advantage. However, a major challenge to adopting AI successfully is our ability to build reliable, predictable, and equitable solutions. A critical flaw with traditional approaches to developing AI is the reliance… ... - Top-10 US bank uses AI/ML to triage loan documents based on risk exposure
- To meet the requirements of unexpected regulatory changes brought on by the pandemic, a top-10 US bank needed to urgently adapt its underperforming model-centric artificial intelligence and machine learning development approach to a data-centric one. The team used Snorkel Flow to automatically classify thousands of loan documents and extract critical… ... - How Schlumberger uses Snorkel Flow to enhance proactive well management - Schlumberger is the world's leading provider of technology and services for the energy industry, operating in over 120 countries. The company provides well maintenance and analytics services to the world's biggest oil companies, and it believes that large-scale data analysis and artificial intelligence/machine learning will help them remain a leader… ...
- How a global custodial bank automated KYC verification with Snorkel Flow - A global custodial bank built a data-centric AI application using Snorkel Flow to save its team of experts thousands of hours of manual information extraction for KYC verification as part of customer onboarding. In just a few weeks, the team was able to extract 50+ attributes from various document formats,… ...
- How Memorial Sloan Kettering Cancer Center (MSKCC) used Snorkel Flow to scale clinical trial screening
- MSKCC, the world’s oldest and largest cancer center, sought to identify patients as candidates for clinical trial studies by classifying the presence of a relevant protein, HER-2. Reviewing patient records for HER-2 is onerous; clinicians and researchers must parse through complex, variable patient data. By unblocking training data labeling and… ... - Improving upon Precision, Recall, and F1 with Gain metrics
- This blog post introduces variants of Precision, Recall, and F1 metrics called Precision Gain, Recall Gain, and F1 Gain. The gain variants have desirable properties such as meaningful linear interpolation of PR curves and a universal baseline across tasks. This post explains what these benefits mean for you, how the… ... - Summer 2022 Snorkel Flow release roundup
- On the heels of the second annual Future of Data-Centric AI event, we’re energized by what we learned from data scientists, machine learning engineers, and AI leaders who are adopting data-centric approaches to accelerate AI success. The Snorkel Flow platform provides these teams with a seamless workflow across training data… ...
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