Presented By O’Reilly and Intel AI
Put AI to Work
April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY

Artificial intelligence strategy: Delivering deep learning

Chris Benson (Practical AI)
4:50pm–5:30pm Tuesday, May 1, 2018
Implementing AI, Interacting with AI
Location: Sutton North/Center
Average rating: ***..
(3.00, 2 ratings)

Who is this presentation for?

  • CTOs, CDOs, and CAIOs

Prerequisite knowledge

  • A high-level understanding of modern AI approaches, especially deep learning

What you'll learn

  • Learn how to create a strategy for delivering deep learning into production
  • Understand how deep learning is integrated into a modern enterprise architecture
  • Explore AI implementation strategies, the prerequisite data strategies that specific AI strategy depend upon, and the trade-offs that each approach implies

Description

Google CEO Sundar Pichai asserts that while the last decade was about mobile first, the next decade will be about AI first. Within the worlds of artificial intelligence and machine learning, deep learning is where a continual stream of the most exciting advancements are being made, from self-driving cars, self-organizing drone swarms, computer vision, and conversational interfaces to advanced industrial robots, speech recognition, and emotion recognition. It is amazing AI that works today, and it is the driving force behind the current AI/ML revolution.

Deep learning will impact nearly every industry on the planet, and there will be countless opportunities to take advantage of this technology. Over the next decade, deep learning models will become common microservices within enterprises architectures. Software engineers will be expected to design, develop, and deploy deep learning microservices into production.

However, reaping the benefits of deep learning is hard to achieve. Success requires a well-considered AI strategy that accommodates business drivers, data acquisition and preparation, model architecture, algorithm selection, robust cloud infrastructure, service integration, and delivery mechanisms. Chris Benson walks you through creating a strategy for delivering deep learning into production and explores how deep learning is integrated into a modern enterprise architecture. Along the way, Chris analyzes various AI implementation strategies, the prerequisite data strategies that specific AI strategy depend upon, and the trade-offs that each approach implies, drawing on real-world examples from Honeywell, a global leader in applying artificial intelligence to advanced robotics and the internet of things.

Photo of Chris Benson

Chris Benson

Practical AI

Chris Benson is Chief AI Strategist at Lockheed Martin RMS APA Innovations, where their mission is to use AI to disrupt from within, before they can be disrupted from without. He came to Lockheed Martin from Honeywell SPS, where he was Chief Scientist for Artificial Intelligence & Machine Learning. Chris built and operationalized Honeywell’s first dedicated AI team from the ground up. Before that he was on the AI Team at Accenture.

As a strategist and thought leader, Chris is among the world’s most in-demand professional keynote speakers on artificial intelligence, machine learning, emerging technologies, and visionary futurism. His inspirational keynotes are known for their passion, energy, and clarity. He is a seasoned storyteller who delights in captivating his audiences with inspiring narratives and insightful analysis at conferences, broadcasts, interviews, forums, and corporate events around the world.

Chris is an innovative hands-on solutions architect for artificial intelligence and machine learning – and the emerging technologies they intersect – robotics, IoT, augmented reality, blockchain, mobile, edge, and cloud.

He is Co-Host of the Practical AI podcast, which reaches thousands of AI enthusiasts each week, and is also the Founder & Organizer of the Atlanta Deep Learning Meetup – one of the largest AI communities in the world.

Chris and his family are committed animal advocates who are active in animal rescue, and strive to make strategic improvements on specific animal welfare issues through advocacy for non-partisan, no-kill, and vegan legislation and regulation.