The AI Frontier in Time-Series Forecasting: Implications for business

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Element AI and QuantumBlack, a McKinsey company

About this talk

This webinar stars Jacomo Carbo, Chief Science Officer at QuantumBlack and Nicolas Chapados, Chief Science Officer at Element AI. They discuss the technical and business gains in time-series forecasting and provide insights into tackling the challenges that lie ahead. Time-series forecasting analyzes past data to predict what might happen in the future. It is central to just about every industry, and for good reason: sometimes even a tiny improvement in accuracy (eg, better prediction of inventory turnover, budget needs, consumer trends) can translate into millions of dollars of operational savings or revenue generation. Until recently, pure machine learning models for time-series forecasting produced underwhelming results, but advances in other areas, such as transfer learning and generalization, have changed the game.

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Element AI develops AI-powered solutions and services that help people and machines work smarter, together. Founded in 2016 by serial entrepreneurs including JF Gagné and A.M.Turing Award recipient, Yoshua Bengio, PhD, Element AI turns cutting-edge fundamental research into software solutions that exponentially learn and improve. Its end-to-end offering includes advisory services, AI enablement tools and products that help large organizations operationalize AI for real business impact. Element AI maintains a strong connection to academia through research collaborations and takes a leadership position in policymaking around the impact of AI technology on society.