AI NI 9: Deep Learning, Image Optimisation, ML Driven E-Commerce & Beyond!

Artificial Intelligence - Northern Ireland
Artificial Intelligence - Northern Ireland
Public group

MCS Group

83 - 91 Adelaide Street · Belfast

How to find us

The door may be closed, but a member of the organising team will be on hand to let you in - there will be a board out front letting you know your at the right place.

Location image of event venue


This AI NI event is kindly supported by MCS group, who generously are offering food, drinks and a venue for our first get together since the HIGHLY successful AI NI Hackathon. This event will present a vast kaleidoscope of topics, touching on specific industry (E-commerce), performance challenges (browser based), cutting edge research and much much more in a series of rapid fire talks. Spaces are limited, so act fast and sign up early to avoid missing out on the varied tapestry of talks at this summer AI NI event.

*Doug Sillars (Google Developer Expert): Using AI to optimise image performance on Browsers*

Doug is is a freelance mobile performance expert, having helped thousands of developers speed up their mobile apps and websites. A Google Developer Expert and the author of O’Reilly’s “High Performance Android Apps,” Doug regularly speaks at conferences, and blogs at He is currently working as a freelance digital nomad, traveling with his family in Europe.

Optimizing image content for every browser and device size can be difficult. Random cropping of images can lead to losing context and features (sometimes as extreme as lopping off the heads of your subjects). In this talk it will be presented how AI can be used to identify the important content in each image, allowing for smart cropping of images. This allows to optimize images further than perviously possible, shrinking page size, and speeding up page load times.

*Chloe Thompson & Jake Young (AI NI): The Future of AI NI Academy*

Jake and Chloe have been working behind the scenes reimagining the future of the AI NI academy. Equipped with an ambitious plan and an enthusiasm to deliver premium (and free!) AI educational content, they both will give a quick overview of what you can expect over the next six months.

*James Wiltshire (Gradient Edge): Machine Learning in E-Commerce*

A new breed of ecommerce company is emerging, completely driven by data and near real-time insights into customer behaviour. These companies can do rapid experimentation and react to customer needs very quickly, by integrating machine learning across their entire commerce system, to provided automated optimisations and to augment human decision making. In this talk James will detail the 5 x pillars of modern e-commerce - with a key element being a data fabric and machine learning layer underpinning everything.

Prior to founding Gradient Edge, James was CTO of Spindrift Group, one of Europe’s leading digital commerce agencies, and was responsible for creating the technology that powers many large e-commerce sites including B&Q, Tesco, El Corte Inglés, Canon and T-Mobile amongst many others.

*Conor McCormick & Christoper O’Hagan: The AI NI Hackathon, Our Story*

Conor and Christopher are two of the members of the winning team that participated in the AI NI Hackathon earlier this year. They will be sharing their own personal journey in navigating the landmark event and discuss the various challenges that they overcame. Keystones of this story will be teamwork, the value of community and the lasting impact the Hackathon has on their day jobs.

*Niall McLaughlin (QUB): Android Malware Detection using Deep Learning*

The number of mobile malware apps is growing every year, making it impossible for human analysts to keep up. At Queen’s University Belfast we have designed a custom deep neural network that has learned to identify Android malware by scanning the code of tens of thousands of malware apps - far more than any person could ever examine by hand. The network learned the subtle cues that indicate malware by looking at the application code, without the need for human experts to tell it what to look for. In this talk, I will explain our malware classification network works, and talk about future directions in malware research.

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