AI Safety and Reliability // Petar Tsankov // MLOps podcast #218 clip

MLOps.community · Beginner ·📐 ML Fundamentals ·2y ago
Join us at our first in-person conference on June 25 all about AI Quality: https://www.aiqualityconference.com/ Huge thank you to LatticeFlow AI for sponsoring this episode. LatticeFlow AI - https://latticeflow.ai/ MLOps podcast #218 with Petar Tsankov, Co-Founder and CEO at LatticeFlow AI, A Decade of AI Safety and Trust. Straight from Davos, Petar Tsankov discussed the ongoing challenge of deep learning in mission-critical applications — dealing with edge cases, achieving model generalization, and the potential dangers in adversarial environments. Experts like Apostol Vasilev from NIST emphasize the need for fundamentally secure design in ML systems, and Petar echoed these thoughts. To keep up with future challenges and breakthroughs in Machine Learning and AI, listen to the MLOps Community Podcast. // Abstract Embark on a decade-long journey of AI safety and trust. This conversation delves into key areas such as the transition towards more adversarial environments, the challenges in model robustness and data relevance, and the necessity of third-party assessments in the face of companies' reluctance to share data. It further covers current shifts in AI trends, emphasizing problems associated with biases, errors, and lack of transparency, particularly in generative AI and third-party models. This episode explores the origins and mission of LatticeFlow AI to provide trusty solutions for new AI applications, encompassing their participation in safety competitions and their focus on proving the properties of neural networks. The profound conversation concludes by touching upon the importance of data quality, robustness checks, application of emerging standards like ISO 5259 and ISO 40001, and a peek into the future of AI regulation and certifications. Safe to say, it's a must-listen for anyone passionate about trust and safety in AI. // Bio Co-founder & CEO at LatticeFlow AI, building the world's first product enabling organizations to build performant, safe, an
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