1 June 2017
An Introduction to AI in the Enterprise
- What are the key use cases for AI and which industry sectors will experience the most revenue growth over the next 10 years
- Which key AI technologies and combinations of technologies will gain the most market traction
- How will AI software deployments drive sales of hardware and professional services
- How will the market opportunity for AI vary by world region
- What will be the key drivers of AI adoption in each industry and technology category
Keynote panel: The Application of Artificial Intelligence in the Enterprise
Head of Data Science
MHP – A Porsche Company
11:30AM - Day 1
Co-founder / CEO
CEO & Founder
The SaaS Co.
German Research Center for Artificial Intelligence (DFKI)
- How are large companies deploying machine learning & business intelligence
- Is your organisation ready for machine learning?
- How will machine intelligence impact business & society
- Challenges and opportunities for investing in AI
- How will AI redefine management strategies & make your business smarter
Connecting Deep Learning with Internet-of-Things
Head of Data Science
MHP – A Porsche Company
11:30AM - Day 1
- A.I. Research & Pre-Development at MHP and Porsche Digital Lab Berlin
- Why and when to move from Predictive Analytics to Deep Learning?
- Artificial Intelligence @ Real-Life Use Cases in Industry 4.0
- A.I. Platforms-as-a-Service for Internet-of-Things
- Building Data Science Teams and the Research Lab Mode
- Our Future and Responsibility with Artificial Intelligence
Voice-Enable All the Things with Amazon Alexa
EU Alexa Skills Kit
12:00PM - Day 1
Alexa, the voice service that powers Amazon Echo, enables users to interact with devices in a more intuitive way using voice. Developers and device makers can build engaging voice experiences for their services and devices with the Alexa Skills Kit and the Alexa Voice Service. Learn how developers are leveraging Alexa to reinvent experiences from finding a recipe for dinner to connecting the smart home to building voice capabilities into connected cars.
Deploying AI Applications in Enterprises: Challenges and Lessons Learnt
Dr. Anand Rao
Partner, Global AI Lead
PwC Data & Analytics
Artificial Intelligence as a field of study has existed over 60 years, but has been receiving widespread publicity and attention in recent years. While there have been a number of deployments of AI in natural language processing, machine learning, deep learning, conversational interfaces, etc. in the consumer domain, enterprise applications of AI have been fewer and still in their infancy.
In this talk, we focus on specific applications of AI related to modeling disruptive scenarios, understanding sales best practices, predictive maintenance using sensors, and a variety of other enterprise and industrial applications of AI. These applications employ some of the latest advances in machine learning, deep learning, natural language processing and generation, multi-agent systems, simulation, and reinforcement learning. We outline some of the challenges of enterprise and industrial applications and draw lessons from our deployments on how to address them. We conclude with a view towards the future of AI and the need to build ‘trust and transparency’ into the AI applications that we deploy to automate or augment human decision making.
Keynote – Building Trust in AI – The standards and regulation
Lord Tim Clement-Jones
Building Trust in AI – The standards and regulation
- How will AI impact on the transformation of society
- Creating frameworks that permit innovation of social value.
- Examining the sharing revolution – privacy laws, personal consent, transparency fairness and accountability.
Panel: Big Data – Creating Intelligent Data Models
Dr. Andreas Braun
Global Data & Analytics
Chief Customer Officer
- The increased need for big data analytics to drive AI & Machine learning
- How to successfully unlock unstructured data & transform into learnable features
- The advancement of self-service big data tools & its benefit for your organisation
From deep learning to cognitive reasoning – a look at the strengths and weaknesses of different approaches to machine learning
Dr. Dave Raggett
03:15PM - Day 1
- How do we distinguish between AI hype & reality?
- What are the strengths and weaknesses of different approaches to machine learning and their relationship to cognitive reasoning.
- What are the limitations of deep learning fueled by big data and what other approaches my be better suited
- How can machine learning be applied to make sense of data, and turn intent into real-time coordinated control of behaviour.
- Exam new approaches to cognition based upon a fusion of ideas from Linked Data, Computational Linguistics and Cognitive Science to enable cognitive agents, that think more like we do, with applications to human-machine collaboration in a broad range of domains.
AI and computer vision: cameras that see like humans
Co-Founder & CEO
04:00PM - Day 1
AI Development & Platforms
- Understanding the importance of AI & how they make systems smarter
- Building cognitive applications in the cloud with open source data
- How to utilize cloud-based systems for complex computing
AI Start-ups – The hot AI Start-ups for 2017
Meet up – Berlin Machine Learning Group
Pitch 1 – 3D Object Classification via Deep Learning and its Application to Detection tasks.
With advances in Deep Learning object recognition in 2D achieves results which can even outperform humans. In the domain of 3D however there is still need for further research. For this purpose, the goal of my work is to present a classification network trained exclusively on 3D data. Furthermore, not only the task of object classification, but also detection from 3D scenes will be discussed.
Pitch 2 – How AI changes Product Discovery in Fashion E-Commerce
The advent of mobile and AI enables fashion brands to provide consumers new ways of discovering fashion online. Using Cerebel’s search technology brands can build engaging and intuitive search experiences for their apps and destinations, empowering consumers to express their personal style and taste using visual references and natural language descriptions.
Pitch 3 – The rise of voice platform
- Voice is becoming mainstream – Why now?
- How voice platforms work?
- Applied use cases and the future of voice
Pitch 4 – Algotecture – the creator of sophisticated algorithms
With $4trillion in global annual revenue, the AEC industry is ripe for disruption from AI. At Algotecture we create sophisticated machine learning algorithms that will propel the industry forward. Our algorithms represent a paradigm shift from manual coding systems to intelligent designing systems that will help developers and BIM managers to better design, collaborate and automate the entire construction process.
Pitch 5 – Melodrive: Adaptive Music Generation for Interactive Media
Adaptive music is the most effective means to increase immersion in games and VR experiences. However, creating a truly adaptive experience is difficult and time-consuming. Melodrive is an AI music system that can automatically generate adaptive soundtracks, which respond dynamically to players’ interactions in real-time. In our pitch, we describe the challenges of building a creative AI and present the business opportunities.