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Unifying Data Science and Business: Artificial Intelligence Augmentation and Integration into Production Business Applications

On Demand

Type

  • Session

Format

  • Hybrid

Track

  • Data Science, Machine Learning and MLOps

Difficulty

  • Beginner

Room

  • Moscone South | Upper Mezzanine | 156

Duration

  • 35 min
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Überblick

Why is it so hard to integrate Machine Learning into real business applications? In 2019 Gartner predicted that AI augmentation would solve this problem and would create will create $2.9 trillion of business value and 6.2 billion hours of worker productivity in 2021. A new realm of business science methods that encompass AI-powered analytics that allows people with domain expertise to make smarter decisions faster and with more confidence have also emerged as a solution to this problem. Dr. Harvey will demystify why integration challenges still account for $30.2 billion in annual global losses and discuss what it takes to integrate AI/ML code or algorithms into real business applications and the effort that goes into making each component, including data collection, preparation, training, and serving production-ready, enabling organizations to use the results of integrated models repeatedly with minimal user intervention. Finally, Dr. Harvey will discuss AISquared’s integration with Databricks and MLFlow to accelerate the integration of AI by unifying data science with business. By adding five lines of code to your model, users can now leverage AISquared’s model integration API framework which provides a quick and easy way to integrate models directly into live business applications.

Session Speakers

Ian Sotnek

Director of Product

AI Squared, inc

Jacob Renn

Chief Technology Officer

AI Squared, inc.

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