Day 2 - 29 November 2018

Big Data for Industry

Over the next few years, data and analytics will become even more crucial across all industries.  Day 2 will look at case study examples of how big data is being applied in practice, the rewards and challenges of implementing these strategies.

09:15AM

Alex Glaser

Vice President

Harbor Research

Associated Talks:

09:15AM - Day 2

View Big Data for Industry: Chairman’s Welcome

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Big Data for Industry: Chairman’s Welcome

. Alex Glaser, Vice President, Harbor Research
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09:30AM

Pawel Osterreicher

Director of Strategy & Business Development

deepsense.ai

Associated Talks:

09:30AM - Day 2

View Keynote: AI and Its Promise to Business: Narrow AI vs General AI

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Keynote: AI and Its Promise to Business: Narrow AI vs General AI

AI is a red-hot topic, even overhyped, some say. We will show why the latter group may well be right–about general AI, anyway. One thing’s for sure: we’re not going to have personal AI assistants anytime soon. Narrow AI applications–that is, practical, focused ones–are a different matter altogether. We believe such applications in business will deliver on their promise and revolutionize the world as we know it.

. Pawel Osterreicher, Director of Strategy & Business Development, deepsense.ai
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10:00AM

Brett Marsh

VP of Sales

Call Journey

Associated Talks:

10:00AM - Day 2

View Unlock every conversation and deliver voice data to the enterprise

03:45PM - Day 2

View Panel: The Revolutionising of Customer Experiences through AI

10:30AM - Day 1

View Keynote Panel: Driving Digital Transformation through AI & Deep Learning

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Unlock every conversation and deliver voice data to the enterprise

Are you making decisions based on incomplete data?  The first step in harnessing the power of analytics is having the right data set spanning the whole customer journey.  Leaving voice data unexplored and unused means you many be missing a wealth of insights that can directly impact business performance, customer experience and risk management. Join this session with Call Journey to learn

  • The 4 industry trends driving the need for voice data
  • Use cases and impact of voice data across the organization ( Customer Experience, Marketing, Sales, Contact Center, Risk & Compliance)
  • The blueprint on how you can easily add voice to the enterprise data mix.  
. Brett Marsh, VP of Sales, Call Journey
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10:30AM

Networking Break

11:00AM

Ameen Kazerouni

Lead Data Scientist

Zappos Family of Companies

Associated Talks:

11:00AM - Day 2

View Machine Learning in Production: From Research to the Customer

12:15PM - Day 2

View Panel: AI in retail and ecommerce.

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Machine Learning in Production: From Research to the Customer

If you had to describe the Machine Learning process in 5 steps, from research to customer, what would they be? This is a question I often ask candidates interviewing for the Zappos Data Science team. My hope is that one of them will be able to tell me, so I can stop trying to figure it out myself. There used to be a time when we didn’t have enough data but we had ideas. Today we not only have the data, but we also have the ideas implemented as models. The real challenge now is to put those models into production. In today’s talk we will go over the Dos and Donts of deploying Machine Learning and Artificial Intelligence solutions at scale and bridging the gap between research and production environments.

. Ameen Kazerouni, Lead Data Scientist, Zappos Family of Companies
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11:30AM

Alex Glaser

Vice President

Harbor Research

Associated Talks:

09:15AM - Day 2

View Big Data for Industry: Chairman’s Welcome

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Stuart Taubman

Vice President of Dark Fiber Business Development (West Region)

Zayo Group

Associated Talks:

11:30AM - Day 2

View Panel: The big data crunch: Transforming healthcare

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Dr. Ren-Hao Pan

Chief Executive Officer

La Vida Tec

Associated Talks:

11:30AM - Day 2

View Panel: The big data crunch: Transforming healthcare

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David Ledbetter

Senior Data Scientist 

Children's Hospital Los Angeles 

Associated Talks:

11:30AM - Day 2

View Panel: The big data crunch: Transforming healthcare

02:30PM - Day 2

View Panel: AI for social good

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Panel: The big data crunch: Transforming healthcare

  • How much data does the healthcare industry have? What isn’t being utilised?
  • Assessing the sheer amount of data the healthcare industry has and why it will take a long time to be digitised
  • The rise of the Internet of Things – apps, wearable devices, sensors – in creating new data streams
  • How other data – food shopping purchases, social media – can be utilised
  • How this can all fit together to create a more streamlined, holistic view of the patient
Moderator: . Alex Glaser, Vice President, Harbor Research
. Stuart Taubman, Vice President of Dark Fiber Business Development (West Region) , Zayo Group
. Dr. Ren-Hao Pan, Chief Executive Officer, La Vida Tec
. David Ledbetter, Senior Data Scientist , Children's Hospital Los Angeles 
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12:15PM

Networking Lunch

01:00PM

Ryan Prox

S/Constable in Charge, Crime Analytics Advisory & Development Unit (CAADU)

Vancouver Police Department

Associated Talks:

01:00PM - Day 2

View Big Data in Public Safety: Fueling AI in an Ethical and Transparent Way

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Big Data in Public Safety: Fueling AI in an Ethical and Transparent Way

The Vancouver Police Department is known worldwide for its pioneering work in the field of intelligence-led policing, and is the first police service in Canada to deploy a machine-learning, predictive system directly on police mobile computers.  With a focus on high-end analytics, combined with competitive technology, the Department has achieved stunning results in reducing crime rates.

Key to this success is the use of ‘big data’ repositories that are required for deep learning and are the foundation of advanced crime forecasting technology. However, big data pose significant challenges to law enforcement, both in acquiring, storing and accessing decades of data, but also ensuring that the data is free of biases and prejudices, which could predispose forecasting outcomes.

Following the implementation of predictive technology and the consequent deployment of resources based on the forecasting, has helped to reverse skyrocketing residential burglaries. What sets this deployment apart from previous examples of predictive policing, is the way in which the technology was used, with the application of innovative policing practices in combination with advanced evaluative methodology to help guard against over-policing in ethnically and socio-economically diverse neighbourhoods.

. Ryan Prox, S/Constable in Charge, Crime Analytics Advisory & Development Unit (CAADU), Vancouver Police Department
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01:30PM

Emilio Billi

CTO

A3Cube Inc

Associated Talks:

02:50PM - Day 1

View Panel: The (Big) Data challenge

01:30PM - Day 1

View Computing architecture challenges to extract value on big data

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Computing architecture challenges to extract value on big data

The introduction of the machine learning and AI into the industry will provide to the production chain enormous benefits at many levels, making real new kind of manufacturing processes and delivering to the market better products and services, AI will permit to optimize the costs and the resources to achieve the best level of quality and productivity.

Machine learning is a substantially a computational process. To that end, it is inextricably tied to computational power and computing architectures. The computational power and the computing architecture shape the speed of training and inference in machine learning and therefore influence the rate of progress in the technology. But, these relationships are more nuanced than that: hardware shapes the methods used by researchers and engineers in the design and development of machine learning models.

This paper aims to dig more deeply into the relationship between computational power and the development of machine learning chowing how the right computing architecture and the capability to fit the problem needs permits to achieve better results in shorter time and opens many new opportunities in the adoption of the AI into the industry.

. Emilio Billi, CTO, A3Cube Inc
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02:00PM

Networking break

02:15PM

Bin Mu

Chief Data & Analytics Officer

Brighthouse Financial

Associated Talks:

02:15PM - Day 2

View Transforming into Big Data Analytics

03:45PM - Day 2

View Panel: The Revolutionising of Customer Experiences through AI

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Transforming into Big Data Analytics

Bin Mu, the Head of Data and Analytics of Brighthouse Financial, will share the journey and experience of the transformation to Big Data Analytics in a Brighthouse Financial, which just separated from Metlife in 2017.

Brighthouse Financial is in the process of separating from Metlife’s systems and environments.  We are setting up our research environment and implementing Big Data analytics, which include transition into 100% open source analytics tools (Python/PySpark), and developing the integrated data environment with SAP HANA and BDS.  This transformation includes not only setting up the Hadoop ecosystem, integrating with SAP HANA enterprise system, but also transition of the skillset of the Data and Analytics team.

. Bin Mu, Chief Data & Analytics Officer , Brighthouse Financial
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02:45PM

Samith Gunasekara

Head of AI and Machine Learning Boeing AnalytX

Boeing

Associated Talks:

02:45PM - Day 2

View Future of aviation innovation through ML

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Future of aviation innovation through ML

As we embark on our 2nd century enterprise digital transformation, Boeing is driving growth with portfolio of analytics-driven products and services using Artificial Intelligence and Machine Learning.

At its core, we are making a difference in the aviation industry by delivering a new generation of manufacturing and logistic experiences. I will discuss how we are driving change internally and externally to drive growth with:

  • Digital Transformation: Driving Data Growth
  • Avionics transformation using Machine Learning
  • Key Learnings: Driving Innovation while staying compliant and secure
  • Advance manufacturing using IoT and Machine Learning
  • Future of aviation innovation using AI and Machine learning

 

. Samith Gunasekara, Head of AI and Machine Learning Boeing AnalytX, Boeing
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03:15PM

Session Close

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