Day 2 - 26 April 2019
AI Technology Solutions: Chair’s Welcome and Opening Comments
Dr. Maya Dillon
UK Lead for AI and Azure
10:00AM - Day 2
Case Study: Microsoft
12:00PM - Day 2
10:30AM - Day 2
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
Director AI Infrastructure
11:00AM - Day 2
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.
AI Technology Showcase
Director - Data as a Service
12:10PM - Day 2
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)
12:20PM - Day 2
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.
12:30PM - Day 2
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.
Squirrel AI Learning
02:30PM - Day 2
Case Study: Squirrel AI Learning
To follow soon…
Sales Director EMEA
NGD Systems, Inc.
03:00PM - Day 2
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.
Ada Lovelace Institute
03:20PM - Day 2
Richard Freeman, PhD
Lead Data & Machine Learning Engineer
03:20PM - Day 2
03:20PM - Day 2
Head of Programme, Digital Commission
03:20PM - Day 2
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