Day 2 - 19 April 2018
Dr Milos Milojevic
Industry Analyst, Digital Transformation, IoT & AI
09:35AM - Day 2
AI Technologies: Chair’s welcome and opening comments
AI for Good Foundation
09:50AM - Day 2
04:30PM - Day 1
AI for Good: Bridging Science and Industry for a Better Future
The United Nation’s goals for a better world by 2030 seem unlikely to be reached. Can industry and Artificial Intelligence be the engine to help us close the research and implementation gap on the biggest challenges of our generation? We think so. This talk will cover several successful examples where sophisticated AI systems are having an impact on areas as diverse as food security, the future of employment, and childhood health.
- Why is Artificial Intelligence an ideal framework for tackling massive societal challenges?
- What kinds of problems can we address?
- What is missing? How does AI fit in?
- Examples of successful technical partnerships.
- How do I get my company involved?
10:10AM - Day 2
Is IBM Power9 the best platform to test and deploy AI your projects?
- Hear how IBM’s recent PowerAI announcements compare to x86 based and public cloud based offerings
- What should you consider before starting your Proof of Concept, including the type of data you are analysing
- What is the most effective way forward post PoC
- This discussion is suitable for those in startup mode or large organisations scoping out their AI projects
CEO & Co-Founder
10:30AM - Day 2
09:30AM - Day 2
Your Consumer Insights team will soon be led by a robot
- What if you could ask any question to 2 Billion People who use Messaging Apps every month and get actionable results?
- Waves.ai provides Consumer Insight within hours helping brands to understand what who their customers are and what they really want.
- After building one of Facebook Messengers biggest chatbot ‘Swelly’, Peter M. Buch and the Waves.ai team created it’s b2b facing product to change how Brands make decisions
Kiki de Bruijn
11:30AM - Day 2
AI for coding
A case study presented by a leading AI company about how AI can aid with traditional coding tasks: bug fixing, test writing, finding and fixing exploits, refactoring code, translating from one language to another, and creating original code to fit specifications.
12:00PM - Day 2
10 Microtrends for Applied AI Startups
A ‘micro’ trend is more than a ‘fad’ but less influential than a ‘macro’ trend. Mark Penn, who coined the term, referred to microtrends as “the small forces behind tomorrow’s big changes”
Artificial intelligence, machine learning and blockchain are all macro trends that will persist beyond 10 or 20 years. Microtrends typically last 3 to 5 years before being replaced, or becoming implicit as a result of widespread adoption. An example would be the application of a specific AI technology to a common use case, one which eventually disrupts an entire market horizontal or industry vertical.
Based on 490 interactions with ‘Applied AI’ startups (22% of all Forward Partners’ leads in 2017) and examples from our own portfolio, we share our observations as the leading early stage VC to predict the top AI microtrends over the next 5 years.
Head of Software
12:20PM - Day 2
An analysis of the recent fatal Uber self-driving collision
StreetDrone will be discussing the analysis from the first self-driving car crash in the USA that fatally injured a pedestrian, and the learnings and explanations we can take from the early data. We will be analysing the possible reasons for the accident and suggestions for algorithmically simple solutions.
2 Dam Creative
01:40PM - Day 2
Designing for AI
- What is AI Product Design?
- What are the challenges?
- Good and bad AI Design
- Designing the right Product/Designing the Product right
- What Does the future hold for AI Design
CEO and Founder
02:00PM - Day 2
Democratising computer vision with deep learning
Is AI and deep learning a tool for the masses? Can it be integrated in embedded devices or time critical applications?
In this presentation we are going to discuss how we democratize deep learning by studying the application scenario and hardware platform in order to be able to transfer the knowledge and accuracy of large scale CNN networks in embedded devices, thus making deep learning a powerful tool for everybody. Use cases examples include process automation, surveillance and product identification.
AI for process automation: use cases from healthcare insurance
- Outlining how to train word2vec for interpreting medical services
- Discussing training word2vec on diseases
- Multichannel implementation of the trained models: web, mobile, contact center