AI ASSISTANT SUMMIT LONDON SEPTEMBER 19-20, 2019 EVENT REPORT: Highlights, attendee & speaker feedback, agenda overview, photos, videos, interviews & more. Thank you to our sponsors: B AI ASSISTANT SUMMIT 500 3 60 2 DAYS ATTENDEES TRACK ACCESS SPEAKERS 12+ HOURS OF 10 20 13 NETWORKING EXHIBITORS INTERVIEWS SPONSORS JOB ROLES COMPANY SIZE LOCATION CTO and CEO Data Scientists Just me! 2 - 10 US Europe Academics Solutions Architect 11 - 50 51 - 100 UK Asia Software Engineer 101 - 1000 1001+ Other A NOTE FROM THE FOUNDER Since the inaugural summit 3 years ago, Sessions included Interpretation of Natural we've seen rapid progress in the evolution Language Rules in Conversational Machine of AI Assistants, in both their capability and Reading; Scaling Custom Virtual Assistants; impact, increasing in efficiency, accuracy and and How to Build Trust with an AI Assistant. emotional intelligence. At the 2019 edition, we also held the annual At this year's event, we heard from a range of Deep Learning Summit as well as the AI in speakers, from leading industry players Retail and Advertising Summit in parallel, including Salesforce, Samsung and Mozilla, to increase collaboration and cross-industry to influential researchers from DeepMind, learning at the event. UCL and the University of Cambridge, as well as emerging startups such as PolyAI and We're now looking forward to the 2020 San LiveSmart. Francisco edition, to hear further developments from the likes of Google, Viv We also witnessed a development in the Labs and Alexa AI. We hope to see you topics explored at the event, including more there! emphasis on natural language processing and real-world applications. Nikita Johnson CEO & Founder RE•WORK ATTENDEE FEEDBACK “I’ve been coming to your summits since they started and it’s amazing to see how they’ve grown. There are so many AI conferences out there it’s hard to know where to go. It’s busy here which is a telling sign you’ve got it right. They keep getting better!” Ali Shah, ICO “As a Data Scientist it’s nice to have a mix of technical and overview presentations to gain insights into both sides. The organisation, the attendees and the food is excellent. “ Hugo Palmer, Blablacar “It’s a great mixture of business and technical. It’s also excellent to find an AI Conference that is not solely for blokes, and is inclusive.” Andrew Smith, ICS.ai “Meeting some awesome mothers in tech. Great to see so much diversity in the speakers and attendees at s tech conference.” Mahtab Mirmomeni, IBM “I haven’t been to one of your events before and I like that it’s more technical than lots of others. I wish I could be in every session at once though!” Catherine Breslin, Cobalt.ai “I think you have got the format perfect, it’s not all pitches to sell but actual research and application. Over the last 3 years I have attended and the content has gone from new exciting ideas to the actual application of them and it’s great to see.” Nevena Franetic, Shopify AI ASSISTANT SUMMIT This summit focused on AI Assistants: case studies, business insights, research & results of implementation within large companies. Speakers shared their insights & lessons learned to provide advice based on their own experiences, case studies & applications across industries such as retail, utilities and space exploration. EXPERT SPEAKERS INCLUDED: Verena Dieser Aditya Guglani Marzieh Saeidi Thomas Wolf Professor in Artificial Data Scientist Research Scientist Chief Science Officer Intelligence Uber Facebook Hugging Face Heriot-Watt University Krittika D’Silva John Spindler Nikola Mrksic Laura Palacio Garcia Lead Software General Partner Co-founder & CEO Senior Vice President Engineer AI Seed PolyAI LiveSmart Shell Energy Retail Francesca Warner Martin Goodson Fabon Dzogang Jonathon Wright Co-Founder and CEO Chief Scientist and Lead Scientist on European AI Alliance Diversity VC CEO Conversation AI European Evolution AIA ASOS.com Commission PRESENTATION HIGHLIGHTS “What can we expect from virtual assistants in the future? We will see systems become much more customisable, they will have much more information from context and finally-the holy grail- they need to become much more conversational.” Catherine Breslin, Cobalt AI “We’re using end-trend response generation which is really exciting- with dialogue for the first time we have really large data sets from the likes of Reddit, Facebook and Twitter.” Verena Dieser, Heriott Watt “Natural language generation is turning concepts into writing or speech while delivering information. It also conveys the personality in the assistant.” Dan Borufka, Samsung “The change in performance shows the value of AI Assistants and Deep Learning. An Additional 5 million revenue from rolling out deep learning models.” Aditya, Uber AI “Our most popular query? Where is my order! We have to develop capabilities to deal with enquiries like this. These include document classification, sentiment analysis, topic modelling, language generation and named early recognition.” Fabon Dzogang, ASOS “For machines to assist in information gathering it is essential to enable them to answer conversational questions.” Marzieh Saeidi, Facebook AGENDA OVERVIEW DAY 1 CURRENT LANDSCAPE Usually when you present a data driven approach, the role based systems aren’t that strong, but in our case the rules were What can we expect from virtual assistants in really solid. the future? We will see systems become Verena Rieser, Heriot Watt much more customisable, they will have much more information from context and We are doing a lot more with less: less and finally-the holy grail- they need to people and fewer labelled data. This is why become much more conversational. we’re using transfer learning and multitask learning. Catherine Breslin, Cobalt AI John Glover, Aylien Biggest problem in conversational machine reading, as in other areas, is having a large AI Assistants behave poorly when asked data set which is difficult to acquire. some questions. On one hand they want to Marzieh Saeidi, Facebook give the best possible answer while they also want to protect their companies. There are two approaches to developing Dan Borufka, Samsung conversational interfaces. Traditional design and conversational AI. Conversational ai can Transfer learning is a way to try and get include symbolic approaches and data machines to learn from experience. When driven approaches. we have a new task we start with the Michael McTear, Ulster University model we’ve trained rather than starting Sensed information about human behaviour again. can be used to build models and make Thomas Wolf, Hugging Face predictions. But it can also be used to influence the behaviour of the individuals DESIGNING AI ASSISTANTS themselves. Mirco Musolesi, UCL NATURAL LANGUAGE PROCESSING Chatbots give you a hit of dopamine, they make you want to engage and keep engaging. Tim Gane, Lloyds Banking Group Natural language generation is turning concepts into writing or speech while DEPLOYING AI ASSISTANTS delivering information. It also conveys the personality in the assistant. Dan Borufka, Samsung When we applied machine learning, we Empowering customers to speak naturally. found that our models can predict stance We take our encoder and fine tune it. We with an 88% accuracy. embed sentences. Walid Madgy, Alan Turing Institute and Pawel Budzianowski, PolyAI University of Edinburgh DAY 2 START UP SESSION APPLICATIONS OF AI ASSISTANTS IN INDUSTRY & SOCIETY One thing we are keen on is being able to work with a limited amount of data, huge data sets are a waste of time. We are constantly trying new methods, including active learning - through this method we are able to get the We’re working to augment healthcare same accuracy with three times less the solutions for patients like GPS does for training data. navigations. This is really broad so we need Martin Goodson, Evolution AI to start somewhere, so we’ve started with emergency services. They receive around 1 We are aggregating over 450k articles a week billion phone calls a year, so we have so from 15,000 sources to filter out fake news. much data we can use to help citizens. This can be very slow, so we started to look at Lars Maaløe, Corti how we could use tech to speed this up - full automation is not quite there. We have to be We’ll be using two supervised learning 100% accurate as it would be poor if we models. We will be retraining existing can’t. We fact check images too, photoshop models. The reason for that is that they have is a big part of this. We generate images so been retrained on large image data sets. that people can see the claims which have They also have optimal network architecture. been input and what our judgement is it. We We will be taking advantage of these models vectorise claims, capturing the meaning of using transfer learning. This will reduce our the claim which is used to pair the vector to training time which will improve our model similar claims and fact checks in our database performance. - if we find something similar then we can Laura Palocia Garca, Livesmart mark it as true or false. Ben Alter, Logically There is an expectation of conversation to be available 24/7. This is where AI Assistants We use slack data to help build an idea of come in. We have been developing the company culture through archetypes. We something over 5 years- we were the first can provide information on strengths and utility company to have a chatbot. This was a weaknesses as well as recruiting, you can run leap of faith from our management team. and EMMA on candidates to see how they Natalia Konstantinova, Shell Energy Retail would be best fitting in your team. Sam Edds, Bunch AI It’s an exciting time for space exploration, as we send people to the moon, Mars and beyond its important to look after our astronauts health.