Accelerate AI Keynote Bernard Marr
Accelerate AI keynote Luciano Floridi
Data Science and Artificial Intelligence technologies are impacting industries transversally, dynamically transforming personalized marketing and sales, supply chain management forecasting, risk management, fraud detection and predictive maintenance.
The Pharmaceutical Industry is lagging behind the transformation, primarily because of its data structure and of regulatory, legal and privacy limitations.
Paradoxically, while Pharmaceutical Research and Development is the area were transformation is most acutely needed because of the high R&D failure rate and ever-growing development cycle times, R&D is also the most refractory to change do to its highly siloed data.
The pervasive “AI Hype” that promises effortless transformation is faced here with the hard requirements of results interpretability and scientific reproducibility.
We present a Data Science strategy to transform Pharma R&D, taking the specific case study of Vaccines, the most impactful Public Health intervention after clean water.
The proposed Data Strategy is based on four pillars: i) Next Generation Data Management and Governance, ii) Completely redefined, patient-centric Information Management Systems, iii) Science-driven advance analytics and machine learning, iv) organizational evolution through a Data Science competency framework.
The overall framework will be discussed, along with concrete examples of successful application.
Dr Sybil Wong Vivian Chang discuses how the maturation of AI technologies is the prelude to an unforeseen step change in humankind’s ability to understand and innovate. Leveraging human expertise to train AI can increase the pace of democratization of science by disrupting the way current research and development is performed and communicated. Ful Details.
Almost every company in the financial technology sector has already started using AI to improve customer experience, gain better insights, reduce costs, prevent fraud and launch new business models. The opportunities are endless – but how can banks capture these in the best possible way and deliver on the AI promise? Jesper will talk about Nordea’s journey to accelerate AI across the organization and how the company is achieving 10x improvements through AI technologies. Full Details.
90% of the information that exists in the world today has been created in the last two years. Smart companies will certainly exploit the power of the new generation of AI and machine learning tools to generate attributable revenue. But advanced deep learning AI instances will also give humans the power to address what have historically been intractable social and cultural problems. Chris Bishop will speak about how we can do both by smartly partnering with algorithms, bots, and machines. Full Details.
Artificial Intelligence is impacting all areas of society, from healthcare and transportation to smart cities and energy. AI won’t be an industry, it will be part of every industry. Alison’s talk will introduce the hardware and software platform at the heart of this Intelligent Industrial Revolution. She’ll provide insights into how academia, enterprise, and startups are applying AI, as well as offer a glimpse into state-of-the-art research from worldwide labs. Full Details
Artificial Intelligence’s unfulfilled expectation is it’s own worse enemy, and between citizens not understanding what it can do for them, and developers not including them in the process, the technologies are lacking transparency and fairness. All parties need to come together to solve this problem, citizens, regulators, vendors, organizations, and entrepreneurs – for AI’s sake and ours. Full Details.
As more and more companies start to have a data science function we also learn the best way to organize and drive the development of data driven products. This talk will teach you some of the best practices from this based on experience from the field. You will hear about what works and what most definitely will lead to failure. Some of the key points touched upon in this talk will be agile development, automation of data science, the value of consumption in production.
As AI continues to disrupt industry, the need to ensure trust in intelligent systems becomes a priority. To achieve trust, systems have to be engineered from the ground up to comply with ethical and societal standards that vary in different cultures. Governments and the European Commission have recently published guidelines and frameworks for AI ahead of possible regulation of AI. The talk discussed these requirements in the light of current AI technology, both from a business and research perspective and dives deeper into some possible technical solutions at an abstract level. Full Details.
illumr helps its clients to better understand and predict patterns of behavior that affect their organization.
It is a deep-tech enterprise data analytics application using a proprietary methodology based on complex self-organising systems.
illumr is drawn from decades’ worth of academic research and has been shown to derive hypothesis-free insights that all existing analytics tools are blind to.
Dr. Lobna Karoui received the Master Degree on “intelligent systems” from the University Paris Dauphine in 2004. Then, she started her PhD research in the University Paris-Sud Orsay and in the Electrical Higher School in Paris, France. Her research interests include the Artificial Intelligence domain, Machine Learning, cognitive science and semantic web. She obtained her PhD in 2008 and presented her research in AI conferences around the World China, India, United States, Australia, London, etc. Based on the Information technology background, her Artificial Intelligence Research and her leadership, she works on applied research to help companies on developing Artificial Intelligence projects for their business and customers : semantic/ sentimental analysis, knowledge discovery, disruptive services, intelligent agents, cybersecurity. As international Speaker, she is invited in Business Events to talk about AI, Leadership and Business
Tengu is a software configuration and automation suite that leverages on the multitude of well-known big data technologies. Tengu offers companies a faster return on investment (ROI) within the ecosystem of big data projects. Real practical benchmarks help decide which setup is most suitable for a company’s needs, lowering the time to get a working and productive big data framework.
Data Science at Scale | Machine Learning | Computer Vision | Intermediate | Workshops
This workshop presents the challenges that the industry faces in adopting AI. Specifically, focusing on how to scale AI. We deep dive into training large-scale models, including looking at modeling and infrastructure aspects. While AI research progress has accelerated over the past years, its wide adoption has been hampered due to scaling challenges. In this talk, I will present the challenges that I found during years of academic and industrial experience with machine learning and computer vision. Specifically, I will dive deep into the scaling challenges that industry faces, including scaling expertise, data, computation and algorithms. Full Details.
Personalised experiences result in happier customers and increased engagement. But true personalisation requires understanding a customer’s personality and communication preferences – from how and when to contact them to the words and images to use – in advance.
Technical limitations have meant that this capability was out of reach for organisations, leaving them with little option but to resort to generic mass communications. Advances in AI and psychology have changed all of this.
Join Igor Volzhanin, CEO at DataSine, to discover:
How the thousands of contact points that companies generate every day can be used to predict the preferences and personality of their customers.
How modern AI techniques can guide marketing departments in creating experiences that will resonate.
How matching content to personality at scale has been able to increase customer engagement by 80%+.
The knowledge of compound bioactivity data against drug targets underpins the discovery of new drugs. However, databases are currently sparse. We will describe a novel deep learning algorithm to capture correlations within protein activity data, as well as between molecular descriptors and protein activities, to impute the missing activities. Unlike many deep learning methods, this approach is capable of being trained using sparse and variable data, typical of those available in drug discovery.
Fluidly is combining machine learning and financial modeling to define a new approach to financial analysis. In this talk, we will explore how Fluidly’s data scientists have rebuilt financial forecasting from the ground up using a variety of machine learning techniques. We’ll discuss the challenges we faced and the lessons we’ve learned that will help others looking to apply AI to raw company data. We will also discuss the opportunities that are opened up by automating highly manual modeling approaches, such as cash flow and another business forecasting. Full Details
Linguistics algorithms in a talent discovery context: applying machine intelligence over large numbers of resumes and job descriptions in real time to identify patterns within the structure and phrasing of language, surfacing relevant people and connecting talent with opportunities at city, country and continent level. The talk will focus on exhibiting embedding of artificial intelligence in existing flows: catering to the talent industry Opening deploys data science at scale, neural networks working in tandem to perform a multitude of business processes faster and with a high degree of accuracy.
Panel Title: Artificial Intelligence; Future Impact on Business & Society
A practical look at the range of AI techniques applied in the finance space (including RPA, Data Analytics, Chatbots and Machine Learning) exploring the challenges with their adoption in the real-world, but also the opportunities that exist for utilizing them. The final section will look to the future and predict the trends we will see in the coming years taking into account topics such as GDPR, Open Banking and the power of Deep Learning. Full Details.
End of the Day 1 of the Conference
Reverse Startup Pitch will provide an audience filled with startups and conference attendees the opportunity to hear directly from Venture Capital Partners about their need for technology or talent, and opportunities for startup collaborations.