Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK
Schedule: AI in the Enterprise sessions
In order to successfully deploy AI and automation technologies, organizations must work through a series of assessments:
- What are the key technologies (hardware and software) and what are their limitations?
- How much data does one need to use these technologies?
- How does one organize and hire for AI?
- What types of problems or tasks lend themselves to automation? What are some initial use cases one can consider?
We’ve assembled trainings, tutorials, and sessions designed to help attendees understand how to move forward with best practices, tools, and technologies used at many leading companies.
9:00 - 17:00 Monday, 8 October & Tuesday, 9 October
Location: Hilton Meeting room 3/4
Angie Ma (ASI Data Science),
Jonny Howell (ASI Data Science),
Emanuele Moscato (ASI Data Science)
Average rating:
(2.00, 1 rating)
Angie Ma and Jonny Howell offer a condensed introduction to key AI and machine learning concepts and techniques, showing you what is (and isn't) possible with these exciting new tools and how they can benefit your organization.
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9:00–17:00 Tuesday, 9 October 2018
Kristian Hammond (Northwestern Computer Science)
Average rating:
(4.50, 2 ratings)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making.
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11:05–11:45 Wednesday, 10 October 2018
With the growing buzz around data science, many professionals want to learn how to become a data scientist—the role Harvard Business Review called the "sexiest job of the 21st century." Francesca Lazzeri and Jaya Mathew explain what it takes to become a data scientist and how artificial intelligence solutions have started to reinvent businesses.
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11:05–11:45 Wednesday, 10 October 2018
Ashok Srivastava (Intuit)
Ashok Srivastava explains how to make your organization AI ready, determine the right AI applications for your business and products, and accelerate your AI efforts with speed and scale.
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11:55–12:35 Wednesday, 10 October 2018
Paco Nathan (derwen.ai)
Deep learning works well when you have large labeled datasets, but not every team has those assets. Paco Nathan offers an overview of active learning, an ML variant that incorporates human-in-the-loop computing. Active learning focuses input from human experts, leveraging intelligence already in the system, and provides systematic ways to explore and exploit uncertainty in your data.
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13:45–14:25 Wednesday, 10 October 2018
Diego Saenz (Accenture)
What do the world's most innovative and fastest growing companies have in common? They are in industries with a high level of VC funding. Accenture has analyzed five years of VC investment data to discover the AI use cases and technologies that are attracting the most money and will drive enterprise AI innovation. Diego Saenz explains where the top 10 investors in AI are placing big bets.
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14:35–15:15 Wednesday, 10 October 2018
Mariya Yao (Metamaven)
Executives are being asked to "innovate with AI,” but the barriers to successful adoption for most enterprises are organizational, not technical. Mariya Yao explains why effective application of AI requires extended interdisciplinary coordination between executive and functional teams, investments in retraining your workforce, and the cultivation of an open, experimental, data-driven culture.
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16:50–17:30 Wednesday, 10 October 2018
Simon Greenman (Best Practice AI)
We're experiencing an AI gold rush. Tech giants, corporations, startups, and governments are investing billions, and headlines about AI have reached fever pitch. It's dizzying to keep track of the latest AI developments and claims. Join Simon Greenman to learn who can and who will make money in this gold rush—and who will become economic casualties along the way.
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11:55–12:35 Thursday, 11 October 2018
Christopher Nguyen (Arimo)
Christopher Nguyen shares lessons learned implementing multiple AI commercial projects at Panasonic. Along the way, Christopher discusses a number of use cases at various stages of implementation maturity and explains what AI really means today in enterprise products, where the key opportunities are, their impact, and key success factors in the adoption of AI across the enterprise.
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13:45–14:25 Thursday, 11 October 2018
Philip Carnelley (IDC)
AI is a key innovation accelerator for digital business transformation. To help you with your strategic roadmap, Philip Carnelley shares IDC's research into the AI market across hundreds of European organizations and explains why organizations should establish a digital platform based on big data, AI, and cloud technologies, with an intelligent core, as part of their transformation strategy.
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16:50–17:30 Thursday, 11 October 2018
As organizations turn to data-driven strategies, there's been increasing interest in creating AI centers of excellence (COEs). Benjamin Wright-Jones and Simon Lidberg take you through the building blocks of a center of excellence and describe the value for organizations embarking on data-driven strategies.
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