Building Trust in Your AI
AI can deliver compelling business results, but do you know for a fact you are using the best available AI model for your data? Do you know what to expect after deploying? Is there a risk of performance degradation or bias? Many AI projects fall short of expectations due to poor model performance or the unintended consequences of inaccurate AI decisions. What if there was a universal way for MLOps/AIOps to evaluate and monitor the performance and behavior of AI models, both pre-deployment and ongoing, no matter the vendor or features used? In this session, we will review the pitfalls of opaque AI models, and discover how to evaluate, compare, and monitor performance and behavior across AI models, for better AI model trust and explainability. We will also demonstrate the Veritone Clarity product, showing how you can easily select the best AI model for the job, detect drift, and correct it to achieve better business outcomes.
Session ID: LT1514 Presentation Type: Live Session (Replay Available)
Date / Time: [Day 1] Mon. Sep. 14, 2020 @ 15:00 ET (US)
Presented by:Transform audio, video, and other data sources into actionable intelligence with Veritone’s aiWARE. Click for more details and additional sessions and content.
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