Accelerating AI Results in the Enterprise with Nick Werstiuk (IBM)

178 views · Published 12 October 2018 · 32:39 · Indexed 20 September 2026

Channel: Databricks · 2018 · Science & Technology

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With the great promise of AI comes great challenges. This includes moving from PoCs to early production and then to a shared service environment supporting multiple data scientists, projects or data sets. Accelerated model development, training and deployment are also keys to creating AI value. Based upon dozens of AI installations, the IBM Systems AI Infrastructure Reference Architecture provides the ability to grow and accelerate the entire AI workflow. With sophisticated tools to simplify and speed hyper parameter optimization, plus faster, more efficient job training leading to higher model accuracy, this reference architecture reduces complexity and speeds time to results to deliver on the promise of AI.

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