Paid | Applied AI & Big Data

• Reviewing your AI output
• The role of analytics in AI
• How to achieve responsible and ethical AI
• Transforming business processes at scale

• What problems is Big Data helping to solve?
• What data will be used? How will it be generated and analysed?
• Getting value out of customer data whilst maintaining GDPR and customer privacy
• How to encourage Big Data Innovation and stay ahead of the pack.

• How is AI changing the way that healthcare is delivered?
• Machine learning and big data – how to leverage new data sets
• Challenges now and for the future

The talk will present a project for the Motor Neuron Disease Association. The Rolls Royce London AI Hub (part of R² Data Labs) is leading the work in developing an intelligent conversation system, that will enable MND patients to communicate effortlessly and in a spontaneous manner.  The project has been undertaken by a large consortium of tech & engineering companies (Rolls Royce, Microsoft, Google, Intel, Accenture, Dell, Computacenter, etc). The aim of the project is to use Artificial Intelligence to help MND patients tackle some of the symptoms they have to live with.

• What are the challenges of delivering energy in the 21^st century and how can modern technology help?
• Improving performance, resources and safety with the help of AI
• Applying advanced analytics and machine learning for better operations and business optimisation

• Graph theory and fraud detection
• Image processing, Fourier transform and removing atmospheric blur in astronomy
• Inferencing (computer reasoning) and sports coaching
• AI and Mars landers
• Embedded computing and prosthetic senses
• Artificial sentience and simulating people

How Nationwide used both supervised and unsupervised methods for helping our Mortgage Retention team have the tools available to make more data driven approaches to selecting upcoming mortgage rates to optimize between retention of members and increased profit margins.

• Explore current AI applications within the financial & banking sectors
• Automated financial advisors and planning developments, and data driven lending systems
• The future value of machine learning within the finance & banking sectors enabling fraud reduction
• Complying with regulations and addressing ethics
• Bots and conversational banking