Presented By O’Reilly and Intel AI
Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK

Impact of AI on Business and Society

 

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9:35–9:50 Wednesday, 10 October 2018
Location: King's Suite
Secondary topics:  Text, Language, and Speech
Amy Heineike (Primer)
Human-generated knowledge bases like Wikipedia have excellent precision but poor recall. Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text and describe what it learns in human-readable text. Read more.
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11:05–11:45 Wednesday, 10 October 2018
Location: Park Suite Level: Beginner
Secondary topics:  AI in the Enterprise
Francesca Lazzeri (Microsoft), Jaya Mathew (Microsoft)
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. Read more.
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13:45–14:25 Wednesday, 10 October 2018
Location: Park Suite Level: Intermediate
Secondary topics:  Financial Services
Martin Goodson (Evolution AI), Mark St. John Qualter (RBS)
Martin Goodson and Mark St. John Qualter share the results of a yearlong feasibility study on the introduction of AI into the onboarding process at the Royal Bank of Scotland (RBS). Along the way, Martin and Mark share their experiences in translating this complex business process into a high-performance computational system. Read more.
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16:00–16:40 Wednesday, 10 October 2018
Location: Park Suite Level: Intermediate
Secondary topics:  Interfaces and UX
Alice Zimmermann (Google)
Average rating: ***..
(3.00, 1 rating)
Fueled by the growth of messaging apps, conversational interfaces are quickly becoming an essential component of every service and product. Join Alice Zimmermann to learn how Google approaches the emerging UX challenges in its conversational agent platform. Along the way, Alice discusses the opportunities in this space and the future of conversation agents. Read more.
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16:00–16:40 Wednesday, 10 October 2018
Location: Hilton Meeting Room 3-6 Level: Intermediate
Secondary topics:  Computer Vision, Financial Services
GIORGIA FORTUNA (Machine Learning Reply)
Many industries, including banking, financial sectors, and insurance, continuously face the problem of detecting fraudulent activities. Giorgia Fortuna explores state-of-the-art innovations in fraud detection and explains how unsupervised ML fits into the picture, focusing on signature checks and face recognition. Read more.
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16:50–17:30 Wednesday, 10 October 2018
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Edge computing and Hardware
Kaz Sato (Google)
Average rating: *****
(5.00, 1 rating)
Kaz Sato offers an overview of ML Ops (DevOps for ML), sharing solutions and best practices for bringing ML into production service. You'll learn how to combine Apache Airflow, Kubeflow, and cloud services to build a data pipeline for continuous training and validation, version control, scalable serving, and ongoing monitoring and alerting. Read more.
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11:05–11:45 Thursday, 11 October 2018
Location: Park Suite Level: Beginner
Secondary topics:  Computer Vision, Ethics, Privacy, and Security
Marc Warner (ASI)
Average rating: ****.
(4.00, 1 rating)
How can AI impact national security? Collaborating with the UK Home Office Counterterrorism Unit, ASI Data Science built a tool that removes extremist propaganda from the web. Drawing on this experience, Marc Warner discusses the role of AI in the fight against terror and explains how shared access to this technology may be part of the answer. Read more.
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14:35–15:15 Thursday, 11 October 2018
Location: Park Suite Level: Intermediate
Secondary topics:  Ethics, Privacy, and Security
Aileen Nielsen (Skillman Consulting)
We're in the year of the AI fake out. "Fake news" is the order of the day, as nebulous chatbots have become significant political actors. Startups peddle robotically handwritten notes and algorithmically personalized gifts for our loved ones. Soon we won't even be able to tell if a customer service agent is a real person. Aileen Nielsen asks, How should we redefine intelligence as fakes flourish? Read more.
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16:00–16:40 Thursday, 11 October 2018
Location: Blenheim Room - Palace Suite Level: Advanced
Secondary topics:  Ethics, Privacy, and Security, Interfaces and UX
Marie Johnson (Centre for Digital Business Pty Ltd)
What does a workforce augmented by digital humans look like? Marie Johnson shares the story of the creation of Nadia, the world’s first digital human for service delivery. Drawing on her experience developing the concept and leading the delivery, Marie presents a framework to help leaders meet exponential changes across industries augmented by digital humans, including healthcare. Read more.
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16:00–16:40 Thursday, 11 October 2018
Location: Park Suite Level: Intermediate
Secondary topics:  Temporal data and time-series
Ira Cohen (Anodot)
With the more applications of machine learning-based applications, the complex algorithms that automate behaviors can get out of control. Ira Cohen explains how to catch problems and glitches early on by using machine learning algorithms to monitor these algorithms for anomalous behavior. Read more.
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16:00–16:40 Thursday, 11 October 2018
Location: Hilton Meeting Room 3-6 Level: Intermediate
Secondary topics:  Interfaces and UX
Archisman Majumdar (Mphasis)
Archisman Majumdar and Jai Ganesh describe the effects of AI techniques on frontend GUI development—specifically, the use of automatically generated code and architecture from text descriptions—and share deep learning techniques for text-to-image creation and template-to-code generation, along with cloud technologies in automated deployment, management, and scaling of such applications. Read more.
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16:50–17:30 Thursday, 11 October 2018
Location: King's Suite - Balmoral Level: Beginner
Secondary topics:  Financial Services, Temporal data and time-series
Johnnie Ball (Fluidly)
Average rating: *****
(5.00, 1 rating)
Cashflow is responsible for 80–90% of UK SME failure. Fluidly uses the wealth of financial data available through APIs to instantly predict cashflow. Johnnie Ball details how the company built an automated cashflow engine, explores the challenges faced in applying AI to financial data, and explains how machine learning can redefine how we think about established approaches to modeling. Read more.