Day 2 - 26 April 2019

AI Technology Solutions

This track covers the full spectrum of AI technologies, how they are being developed and the real life scenarios where they are being utilised.  Expect to hear about chatbots, visual recognition technologies, robotics and machine learning.

09:40AM

Pete Trainor

Author, Mental Health Campaigner and Co-Founder

Us Ai

Associated Talks:

09:40AM - Day 2

View AI Technology Solutions: Chair’s Welcome and Opening Comments

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AI Technology Solutions: Chair’s Welcome and Opening Comments

. Pete Trainor, Author, Mental Health Campaigner and Co-Founder , Us Ai
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10:00AM

Dr. Maya Dillon

UK Lead for AI and Azure

Microsoft

Associated Talks:

10:00AM - Day 2

View Case Study: Microsoft

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Case Study: Microsoft

. Dr. Maya Dillon, UK Lead for AI and Azure, Microsoft
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10:30AM

Lauren Kunze

CEO

PandoraBots

Associated Talks:

12:00PM - Day 2

View Panel: Harnessing the powers of chatbots for business

10:30AM - Day 2

View From 0 to 100 Million Messages a Day: Steps to Build, Optimize, and Scale Enterprise Grade Intelligent Agents

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From 0 to 100 Million Messages a Day: Steps to Build, Optimize, and Scale Enterprise Grade Intelligent Agents

Drawing on real customer case studies, this talk will detail the design and technical considerations involved in building “intelligent” agents with real traction and real business results. You will learn:

  • When machine learning is effective–and when it isn’t
  • What types of human resources are required
  • An actionable chatbot development roadmap
. Lauren Kunze, CEO, PandoraBots
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11:00AM

Kevin Yu

Director AI Infrastructure

Facebook

Associated Talks:

11:00AM - Day 2

View Challenges of Data, Features, and Compute at Facebook Scale

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Challenges of Data, Features, and Compute at Facebook Scale

AI and ML at Facebook is being used at ultra large scale. Facebook’s AI Usage has grown exponentially over the last 2 years and is accelerating. Almost any dimension such as model size, data size, feature size, number of unique users, number of models, etc is exhibiting the same exponential growth rates. This growth pushes Facebook’s AI infrastructure to scale not only compute for inference and training, and also for a critical component of data and feature processing and engineering. Diverse business applications for AI results in a large amount of experimentation, thus driving the cost and importance of AI engineer developer efficiency.

Creating pipelines which are affordable and efficient while improving developer efficiency is critical to enabling the sustained scaling of AI at Facebook. Facilitating exabytes of training and features along with low latency inferencing is changing the nature of data processing systems. In this talk, we will outline the challenges of growth and scale and how these challenges are changing how we build our data and processing systems.

. Kevin Yu, Director AI Infrastructure , Facebook
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11:30AM

Networking Break

12:00PM

AI Technology Showcase

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12:10PM

Mark Dunn

Director - Data as a Service

Lexis Nexis

Associated Talks:

12:10PM - Day 2

View Solo: Optimising entity due diligence with robotics process automation

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Solo: Optimising entity due diligence with robotics process automation

  • Entity due diligence market drivers (ie. why is it important)
  • Entity due diligence process (ie. what companies do)
  • Where RPA fits (ie. benefits of RPA)
. Mark Dunn, Director - Data as a Service, Lexis Nexis
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12:20PM

Mauro Arruda

CEO

Smartia Ltd

Associated Talks:

12:20PM - Day 2

View Industry 4.0 – Surely its all about data and analytics… is it?

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Industry 4.0 – Surely its all about data and analytics… is it?

Companies recognise that there is an enormous value in the data they create and they are making plans to capitalise on it as quickly as possible.

Manufacturing is leading the way, both as one of the largest producers of data from factory systems, machines and sensors, and as one of the leading adopters of the new technologies that make up big data and artificial intelligence.

However, the rapid evolution of big data technologies, coupled with an incredible level of complexity of industrial automation and robotic systems, has led to “analysis paralysis” at some manufacturers. Questions of where to start and how to apply these technologies along with the uncertainty at the potential scale of deployments, are preventing some companies from moving forward, especially with specific use cases seemingly so unique at this point in time.

In this presentation, Smartia will discuss 7 steps for setting up a successful industrial data and AI framework.

. Mauro Arruda, CEO, Smartia Ltd
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12:30PM

Mark Braithwaite

Technical Specialist

Wolfram

Associated Talks:

12:30PM - Day 2

View AI : Experts not required

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AI : Experts not required

A fast paced, interactive and example driven exploration showcasing the AI capabilities of the Wolfram Programming Language. This presentation will demonstrate how sophisticated AI tools can be rapidly developed and deployed to extract new insights from your data and improve decision making.

. Mark Braithwaite, Technical Specialist, Wolfram
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01:00PM

Networking Break

02:30PM

Joleen Liang

Partner

Squirrel AI Learning

Associated Talks:

02:30PM - Day 2

View Case Study: Squirrel AI Learning

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Case Study: Squirrel AI Learning

To follow soon…

. Joleen Liang, Partner, Squirrel AI Learning
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03:00PM

Jos Keulers

Sales Director EMEA

NGD Systems, Inc.

Associated Talks:

03:00PM - Day 2

View Computational Storage Accelerating AI Applications

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Computational Storage Accelerating AI Applications

Distributing compute power to storage nodes creating so-called computational storage leads to greater scalability, simpler upgrading, and better fault tolerance. The approach is well-suited to modern applications including real-time analytics, artificial intelligence, machine learning, virtual and augmented reality, autonomous systems, IoT, and cybersecurity. It also reduces the strain on system-level resources and networks. It is particularly valuable now that new technologies such as NVMe and persistent memory have greatly increased the speed of storage accesses, often overwhelming the ability of other parts of systems to keep up.

. Jos Keulers, Sales Director EMEA, NGD Systems, Inc.
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03:20PM

Pete Trainor

Author, Mental Health Campaigner and Co-Founder

Us Ai

Associated Talks:

09:40AM - Day 2

View AI Technology Solutions: Chair’s Welcome and Opening Comments

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Reema Patel

Programme Manager

Ada Lovelace Institute

Associated Talks:

03:20PM - Day 2

View Panel: AI for social good

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Richard Freeman, PhD

Lead Data & Machine Learning Engineer

JustGiving

Associated Talks:

03:20PM - Day 2

View Panel: AI for social good

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Emma Lawton

Digital Strategist

Parkinson's UK

Associated Talks:

03:20PM - Day 2

View Panel: AI for social good

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Kristina Barrick

Head of Programme, Digital Commission

Scope

Associated Talks:

03:20PM - Day 2

View Panel: AI for social good

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Panel: AI for social good

• How is AI being successfully applied to challenge social problems?
• What are the potential uses of AI to solve social and ethical problems?
• AI’s impact across Health, Environmental Sustainability and Public Welfare

Moderator: . Pete Trainor, Author, Mental Health Campaigner and Co-Founder , Us Ai
. Reema Patel, Programme Manager , Ada Lovelace Institute
. Richard Freeman, PhD, Lead Data & Machine Learning Engineer, JustGiving
. Emma Lawton, Digital Strategist, Parkinson's UK
. Kristina Barrick, Head of Programme, Digital Commission, Scope
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04:00PM

Session Close

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