Trusted AI: Bringing trust back into AI through open source (sponsored by IBM)
As businesses move beyond experimentation to full-blown AI projects across the enterprise, they’re recognizing that there’s more to successful implementations than simply having the right datasets, AI models, and scalability. Increasingly, dimensions of trust, including fairness, robustness, and explainability, are important metrics that help evaluate AI model behavior.
Join Animesh Singh to learn how IBM leverages the power of open source to bring trust back in AI, using popular open source projects for adversarial AI defense and attacks, bias detection and mitigation, and datasets and model explainability.
This session is sponsored by IBM.
What you'll learn
- Discover how IBM leverages open source
Animesh Singh is a senior technical staff member (STSM) and program director for the IBM Watson and Cloud Platform, where he leads machine learning and deep learning initiatives on IBM Cloud and works with communities and customers to design and implement deep learning, machine learning, and cloud computing frameworks. He has a proven track record of driving design and implementation of private and public cloud solutions from concept to production. Animesh has worked on cutting-edge projects for IBM enterprise customers in the telco, banking, and healthcare industries, particularly focusing on cloud and virtualization technologies, and led the design and development first IBM public cloud offering.
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