Productising AI: Turn NIPS-level research into products

Why does AI fail?
NIPS #ProtestNIPS – the conference where the most advanced research in machine intelligence is unveiled – can also be an echo-chamber for those who contribute, but rarely apply algorithms to solve real-world problems.

According to MMC Ventures, AI-first initiatives fail because (1) we fail to articulate how it can solve specific business problems, (2) can’t demonstrate ROI before we deploy to production, and (3) because we over-promise on some high-profile AI projects.

What else causes NIPS level research to crumble when deployed in real-world environments? Join us and find out.

Evening narrative
1) Lessons learned with Axyon AI – Commercialising deep learning solutions for banking and finance | Frank Abbenhuis

2) Lessons learned from turning reinforcement learning research into products, with Haitham Bou-Ammar. Haitham leads the Reinforcement Learning team at With over 7 years of experience, gathered at top-tier universities including UPenn and Princeton, in lifelong, transfer, and reinforcement learning (RL), he is responsible for proposing a novel, scalable, and efficient algorithms for RL.

Panel discussion, moderated by Doron Reuter, AI Products & Partnerships, ING

Topic: Productising AI – how do you turn best-in-class R&D into commercially viable products?


1) Amir Saffari – SVP of AI at Benevolent AI has a PhD in Machine Learning and has been working in the field of Artificial Intelligence for more than 17 years, researching and developing ML theory, applications, and, products. He’s numerous publications in top-tier ML conferences and journals and most of his research has been released as open source software. He was part of Sony’s R&D team and has been involved in a few ML startups prior to joining Benevolent AI where he is currently leading the research and development of ML technology for drug discovery.

2) Conan McMurtrie is the Global Head for Product AI at DigitalGenius. He spends his time working with researchers, engineers and product designers building machine learning prototypes, engineering them into production, and ensuring their scalability. Conan holds an MSc in Machine Learning from UCL and an MSc in Science Linguistics from Imperial College London.

3) Nikola Mrksic is the CEO and Co-Founder of PolyAI, a London-based machine learning startup developing the next generation machine learning platform for building conversational user interfaces. Our platform enables the development of machine learning powered chatbots or voice-based agents which perform tasks across many applications, in a wide array of world languages.

Nikola completed his PhD at the University of Cambridge, working with Professor Steve Young. He worked as a machine learning researcher with the Apple Siri team in Cambridge. Before that, he was the first technical hire at VocalIQ, a Cambridge-based dialogue systems startup acquired by Apple in 2015.

Special announcements
1) Launching the Ethics Track with Catalina Butnaru

2) Introducing new City AI London Ambassador, Rodolfo Rosini, Rodolfo has been CEO and founder of several startups over a career spanning over 20 years, working in AI and cybersecurity. Currently, a partner at Zeroth, investing in AI startups worldwide.

Throughout the evening you will also have the opportunity to mingle and network with the team leading AI-centric initiatives at ING. Nibbles and drinks will be provided throughout the evening.

The City AI London crew kindly asks for anyone who does not want to be recorded or photographed to specify their preference prior to the event.

Special thank you to ING
ING is a global financial institution with a strong European base employing 52,000 people, offering retail and wholesale banking services to customers in over 40 countries. The purpose of ING is to empower people to stay a step ahead in life and in business. We aim to do this by incorporating disruptive technologies like AI into our service offering in order to go beyond banking and create a differentiating customer experience. ING’s Wholesale Banking Advanced Analytics Tribe builds end-to-end software products with embedded machine intelligence that bring insights of value to ING’s corporate & institutional clients transforming the way wholesale banking is done – making it 10x better, 10x cheaper and 10x faster. Join us in our quest to use AI to build a trusted and sustainable wholesale banking sector!

November 29, 2018 18:30 – 21:30
ING Bank N.V., London Branch
8-10 Moorgate

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