Virtual Show Day One: Monday, 15 June

DRIVING RESULT-BASED INNOVATION – ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

11:30 am - 11:40 am Introduction by Seth Adler, Editor, AIIA Network to the Virtual Edition of 3rd Artificial Intelligence Week

Seth Adler - Editor AIIA, Network
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Seth Adler

Editor AIIA
Network

11:40 am - 12:00 pm ACCELERATING AI AND MACHINE LEARNING IMPLEMENTATION IN YOUR ORGANIZATION

Terence Hung - Chief of Future Intelligence Technologies, Rolls-Royce

Establishing or building single machine-learning model is rather easy and inexpensive. However, data scientists in Middle East and Africa especially have to deal with vast amount of data, and have to consider many machine-learning algorithms in their bid to build their best model.

Data scientists are under pressure to speedup up their model building capability due to the organization, which demands, for more and more models to deliver accurate predictions.

This webinar will focus on how you can make your business AI Smart. How can you build and implement multiple machine learning models in your existing infrastructure?

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Terence Hung

Chief of Future Intelligence Technologies
Rolls-Royce

12:00 pm - 12:20 pm EXPLORING THE COMPUTING ADVANCES BEHIND AI AND HOW ORGANIZATIONS ADVANCE BUSINESS USING BOTH MACHINE AND HUMAN INTELLIGENCE

Kirill Petropavlov - Director of AI, Bank of Singapore

In this webinar you will learn about:


The building blocks that enable AI, including machine learning and natural language processing.

Insights obtained from deep learning and natural language understanding.

Techniques that enable a computer to understand interact and communicate with humans.

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Kirill Petropavlov

Director of AI
Bank of Singapore

12:20 pm - 12:40 pm MINIMIZE THE RISK AND MAXIMIZE THE RETURN ON INVESTMENT BY STARTING WITH PROOF OF CONCEPT

Be it a PoC, a pilot project, a pilot programme or a pilot initiative, the title is irrelevant as much as the purpose, which is to get your organization started with AI. A Proof of Concept aims to explore and validate how well a particular business problem can be solved by AI.

POC can be divided in 3 stages of the AI based project:

•      Preparation

•      Development

•      Validation

A Proof of Concept is a best practice to guarantee high ROI on an AI project, and to ensure that the companies’ expectations are being met with the results. For instance, an organization can deploy your AI model into production. This means that you will integrate a machine-learning model into an existing production environment so it can run on a continuous or regular basis. It is one of the last stages in the machine-learning life cycle.

This session will deep dive into the case study on how PoC has been successful for an organization and how important it is deploy Proof of Concept?  

12:40 pm - 1:00 pm WHAT COULD AI DO FOR AN ORGANISATION? REVIEW OF CURRENT REAL-WORLD EXAMPLES

There are numerous definitions as to what constitutes a system to be artificially intelligent. For organizations wishing to implement AI what tangible use cases should you focus on to deliver business value? This webinar provide real world examples of AI in action, dispelling the myths and focusing on the value it can drive.


·        Real world AI applications generating business value

·        Cross sector practical applications of AI

·        Example of an end-to-end automated AI decision capability

1:00 pm - 1:05 pm CLOSING REMARKS