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CW Technology & Engineering Conference Artificial Intelligence: Underlying technologies – how they work and how they are applied

Brought to you by CW (Cambridge Wireless)

We will be focusing on the technologies underlying the burgeoning field of Artificial Intelligence. As seemingly limitless applications are increasingly discussed in the press we will look past this hype.

About the event

We will be focusing on the technologies underlying the burgeoning field of Artificial Intelligence. As seemingly limitless applications are increasingly discussed in the press we will look past this hype, focusing on three key themes:

What are the key and emerging AI technologies and how are they combined to drive current and future applications?
What are the trade-offs between the increasing number of tools and frameworks and how far can they really take us?
What are the implications for hardware, network infrastructure and storage - what are the limiting challenges, and what is on the horizon to make this more tractable?
The 3rd CW TEC is aimed at technology leaders in industry, as well as young engineers and data scientists, to give them an overview of the subject and to critically examine the associated challenges. Speakers will include leaders in AI research and development from universities and industry

You can follow @CambWireless on Twitter and tweet about this event using #CWTEC.

Hosted by The Computer Laboratory, University of Cambridge

The Computer Laboratory is an academic department within the University of Cambridge that encompasses Computer Science, along with many aspects of Engineering, Technology and Mathematics. It consists of 44 academic staff, 30 support staff, 7 research fellows, 102 post-doctoral research workers and 121 PhD students. We have over 300 undergraduates studying for Part I, II and III of the Computer Science Tripos and 36 graduate students studying for the MPhil in Advanced Computer Science. Its current research areas include bioinformatics, computer architecture, computer vision, distributed systems, graphics and human-computer interaction, logic and semantics, machine learning, natural language processing, networking and wireless communication, operating systems and virtualization, programming, security, and sustainable computing.

Sponsored by: Magna International

Leading global automotive supplier.

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Sponsored by: Innovate UK

Innovate UK is the new name for the Technology Strategy Board - we're the UK's innovation agency, accelerating economic growth. is the Cambridge-based creator of the first principled A.I. decision-making platform.

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Supported by: Myrtle Software

Myrtle accelerates performance critical workloads on FPGAs: devices that are currently being deployed at scale in data centers around the world. Myrtle has realized multiple proprietary deep learning networks as silicon designs so that they execute at a latency and power point that makes them usable in real-world situations. Myrtle is currently targeting its technology at inference workloads in data centers and is involved in a major collaboration to address the safety and verification challenges that currently preventing sophisticated deep learning networks being used in road vehicles


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The information supplied below may be subject to change before the event.


Registration and networking with refreshments



Welcome from CW (Cambridge Wireless)
Robert Driver, CEO, CW
Welcome from our host The Computer Labs
Dr Ian Wassell, Senior Lecturer, University of Cambridge Computer Laboratory
A word from our headline sponsor Magna
David Paul, Director, Corporate Engineering and R&D, Magna International


Scene setting

The Landscape of AI
Phil Claridge, Founder, Mandrel Systems
Peter Whale, Founder, Peter Whale Consulting
An introduction from the AI SIG Champions to the conference day, the key topics to be covered, the structure of the day, and some of the engineering design questions to be covered.


Key and emerging AI technologies:The near-term impact of AI

Professor Steve Young, Professor of Information Engineering, University of Cambridge
A review of the major algorithmic approaches and technological advances that are driving the current uptake of AI.


Key and emerging AI technologies:Under the covers of Deep Learning

Theophane Weber, Senior Research Scientist, Google DeepMind
What is Deep Learning? How is it different from classic neural nets? How is this informed from our understanding of the human brain? What is Deep Learning is good for and not so good for.


Refreshments and networking


Under the covers of a range of other AI technologies

Professor Carl Edward Rasmussen, Professor of Machine Learning, University of Cambridge and Chairman,
This is the counter point to the session on Deep Learning, where we explain some of the other promising areas of AI such as Probabilistic models, Reinforcement Learning (RL) and Multi-agent Systems (MAS).


The revolution of speech recognition technology

Dr Tony Robinson, Founder & CTO, Speechmatics
Speech recognition technology is revolutionising the industry – but how do you make speech recognition work for you?


Panel Session with audience Q&A


A word from our sponsor Vishal Chatrath, CEO and Co-founder,


Lunch and networking


Tools, Frameworks and AI Systems Engineering: Where next for AI?

Professor Neil Lawrence, Professor of Machine Learning, University of Sheffield
Our current generation of artificial intelligence techniques are driven by data. But also we expect to be able to deploy artificial intelligence techniques on data. What does that mean, is it a contradiction? How will this effect the wider technology landscape? Is it simply a matter of refining deep neural nets? Or are more disruptive technologies needed? What will be the challenges of deploying AI systems?


Tools, Frameworks and AI Systems Engineering: Survey of Tools and Frameworks

Dan Neil, Lead Machine Learning Researcher, Benevolent AI
This talk will look at the capabilities of the increasing number of tools and frameworks for AI, and how far they can take us currently. We will then reflect on Benevolent's experience of area where we have needed to augment these with our own in-house tools.


Tools, Frameworks and AI Systems Engineering:NVIDIA’s Artificial Intelligence Platform

Alison B Lowndes, Artificial Intelligence Developer Relations, EMEA, NVIDIA
This talk will combine knowledge of world-wide state-of-the-art research, with NVIDIA’s ecosystem of software, research, training, support and of course hardware. Chips are one part of enabling AI, a field moving faster than chips can be produced. That momentum drives efficiency and forces agility, allowing us to enable AI across the world’s data centres, clouds & ‘at the edge’. Discussion will include the tools we opensource and optimize with partners across academia & Enterprise as well as hints along the path to AGI through neuroscience, and what that means for the real world.


Tools, Frameworks and AI Systems Engineering: Why do we need another processor (solution?) for AI

Simon Knowles, Co-founder & CTO, Graphcore Ltd.
This talk will cover how to design a processor for Machine Intelligence. It will describe the underlying compute workload in today's and future Machine Intelligence applications. It will show how current CPU and GPU processors are limited in their ability to support this new workload and how a new type of intelligence processing unit can be developed which is much more efficient for this fundamental new era of computers.


Processors for real-world AI

Dr Peter Baldwin, Founder, Myrtle Software; Dr David Page, Chief Scientist, Myrtle Software
A number of different processor architectures have been proposed for deployment in AI applications. In this talk, we discuss trade-offs of the alternative approaches for current and future workload


AI: open for all?

Panel session
Chaired by Sobia Hamid, Founder, Cambridge Data Insights
AI will have an increasing impact on business and wider society but can seem like it is driven by a very select set of people. This panel discussion explores the issues we need to resolve to have AI be open to all.


Refreshments and networking


Tools, Frameworks and AI Systems Engineering: System Architectures for AI

Anton Lokhmotov, CEO, dividiti
Keeping up with the fast pace of AI innovation calls for an agile system approach that engages the community in a virtuous co-design and optimisation cycle, where the design of AI applications is informed by the capabilities of computer systems and the design of computer systems is informed by AI applications.


Tools, Frameworks and AI Systems Engineering: System Architectures for AI

Jem Davies, Fellow and General Manager, Machine Learning, Arm Ltd
AI and Machine Learning are currently generating a huge number of headlines. As the near ubiquitous computing platform on devices, Arm has a unique view on the technology and the different implementation approaches needed to make it a success. As AI/ML workloads increase in number and complexity, Jem will discuss how Arm views the challenges, options and opportunities presented, and what is being done to address these new workloads.


Panel Session with audience Q&A

Chaired by James Chapman, VP Product Management, Qualcomm


AI on the Edge

Cyrus Vahid, Principal Solutions Architect, Amazon (AWS)
What drives the partitioning of edge v. cloud? How intelligent can the edge be and how intelligent do we want it to be? Does the edge device really learn?


Closing remarks


Event Close

Event Location

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Location info

Computer Laboratory, University of Cambridge, William Gates Building, 15 J J Thomson Ave, Cambridge, CB3 0FD

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