Join us at the most exclusive and influential Artificial Intelligence conference in the United States, taking your place alongside more than 100 AI innovators, robotics scientists, machine learning forerunners, data strategists and business leaders who are redesigning the future of information technology, engineering and manufacturing, and the world.
The Artificial Intelligence Leaders Summit offers you the opportunity to:
- Be the first to discover future trends in global data technologies
- Enhance your understanding of the new AI and machine learning technologies that’s making the future happen today
- Identify new opportunities to improve business intelligence
- Build your network of technology and data leaders
Our Artificial Intelligence Leaders Summits have always been popular for good reason – but this will be the best yet!
Summit Topics Include:
- Neural network and cognitive computing
- Embedded software, algorithms, cloud and mobile
- Machine learning algorithm and deep learning architect
- Analytics process optimisation with AI and machine learning
- Computer vision, natural language understanding, and autonomous driving
- Ambient Intelligence, Wearables, immersive experiences, contextual computing, IoT, advanced robotics
And much more...
What You’ll Gain:
MAINTAIN a reputation as a leader in artificial intelligence, machine learning and robotics engineering
LEARN the new skills, techniques and tools you’ll need for exponential growth of your business
CREATE & DEVELOP your data and AI strategy
ENHANCE your professional network, with opportunities to network and collaborate with technology leaders and fellow senior executives
STRENGTHEN your professional development and gain certificate for professional excellence
Confirmed Speakers include:
We’ve hand-picked our Artificial Intelligence Summit speakers for their expertise, experience and influence in data and AI technology and strategy and they all have important, impactful things to say. We know that you’ll get a lot out of them.
The summit will gather the most influential, knowledgeable and innovative AI and data leaders across the globe. But they also must have that “special something”; it could be a unique human touch, a truly individual mind, or the courage to take their organisation through hell and back – and win. We’ve found that this kind of person gives the best to our clients, and gets the best from them.
But we don’t know everybody. If you’re a maverick or an imagineer in the business intelligence landscape, with proven, exciting results, please do consider becoming a Forward Leading speaker. Get in touch. We’d love to find out more about you. Reach out to Pearl Cheng today!
Confirmed Speakers Now Include:
Director, AI Programme
VP, Artificial Intelligence Products Group (AIPG) & GM, Architecture
VP, Data Scientist
CTO / Co-Founder
Wang Professor, Cognitive and Neural System
Chief Technology Officer
Distinguished Research Scientist
Founder & Lead Developer
Principal Program Manager
Jen Zhen Wang
Manager, Data Science
Senior Engineering Manager, Machine Learning
Mina J Hanna
Chair, IEEE-USA Artificial Intelligence & Autonomous Systems Policy Committee
Sr. Machine Learning Engineer & Tech Lead
We co-develop the Summit Agenda with our artificial intelligence leaders group so you can expect a variety of activities, sessions and networking opportunities that will really maximise what you gain.
This year’s agenda just has been released. However, please check back regularly for the continuous add-ups of amazing new speakers.
08:00 – 08:50
08:50 – 09:00
09:00 – 09:30
by Distinguished Research Scientist, HP
HP Inc. is at the forefront when it comes to technology solutions and devices for Printing and Imaging systems and leading vendor of Personal Computers in the world, across customer segments from individual to enterprise. The 3D Printers from HP show glimpse of what’s possible with the 4th Industrial revolution and is at the cutting edge of our Print device portfolio. Similarly the Device-as-Service (DaaS) and Smart device Services (SDS) demonstrate the state-of-art in managed software solutions for the enterprise in PC and Print world. In this talk, we are going to look at how Machine Learning and Data Science is being used to drive these (and other) innovations at HP, transforming the way we incubate, manufacture and maintain our devices throughout their lifetime and how the company is transitioning to the services view of the device world and what the future holds.
09:30 – 10:00
by Chair, AI & Autonomous System Policy Committee, IEEE USA
10:00 – 10:30
by Principal Program Manager, Microsoft
AI intelligence will change how we live, work and play. Microsoft AI and Knowledge are helping shape the next generation of AI-infused technologies for people and cities everywhere. Come learn about the Microsoft AI portfolio and how you can contribute to the change.
10:30 – 11:00
AM Coffee Break
11:00 – 11:30
by Senior Staff & Engineering Manager, Facebook
11:30 – 12:00
by Nevi Kaja, Researcher, Ford Motor Company
In this presentation, we will talk about Chatbots and their ability to transform the customer experience while enabling cost efficiencies. In addition, the underlying technology along with some examples of chatbot platforms will be discussed. This presentation will go over a few Chatbot experiments at Ford and cover some of the learnings as well as challenges faced while building Chatbots. In the end, we will focus the discussion around Chatbot training and the importance of knowledge transfer as a basis for iterative growth.
12:00 – 12:30
Deep Ice-breaking - Get Ready for the AI Challenges
13:00 – 14:00
14:00 – 14:30
by Senior Machine Learning Engineer & Tech Lead, Smule
Nowadays most machine learning literatures focus on novel algorithm designs, however there are less discussing data quality control in the practical environments. To my opinion, there are two major pillars in a successful machine learning application in the industry: data extraction/transformation and model fitting. The process flows from left to right forming a conceptual assembly line, at each stage, certain quality controls are required to guarantee the next stage's inputs are well-defined. Inadequate data quality control step could lead to no conclusion and even worse faulty conclusion on the models, which might eventually results in misleading business decisions. This talk intends to introduce some good practices we've adopted that help us be more confident about the final outcomes.
14:30 – 15:00
by VP Data Scientist, JPMorgan Chase & Co.
In Philosophy, the Unity of Opposites (UOO) defines a situation in which the existence of a situation depends on the co-existence of at least two conditions which are opposite to each other, yet dependent on each other and presupposing each other, within a field of tension (Wikipedia). As a machine learning practitioner and data scientist, I gradually realize that, surprisingly, this UOO is well applicable in a wide range of important ML concepts, in which two opposite conditions co-exist. For example, the model fitting may cause underfitting or overfitting; generalization error contains bias and variance, model selection involves exploration and exploitation, etc. Furthermore, when digging deeper, there are even more key concepts possessing this philosophical trait of "unity of opposites". Understanding those opposites is indispensable to obtain a holistic perspective and deep understanding of ML. In providing practical examples of UOO, I will further decompose ML projects in financial services into "5 Pillars", namely, boundary, data, people, algorithm, and platform. I will show, under UOO, how these 5 pillars achieve the philosophical oneness (and twoness) and help to drive ML decisions in financial services.
15:00 – 15:30
PM Coffee Break
15:30 – 16:15
by Director, AI Program, The Alan Turing Institute
Adrian Weller is the Programme Director for AI at The Alan Turing Institute, the national institute for data science and AI, where he is also a Turing Fellow leading a group on Fairness, Transparency and Privacy. He is a Senior Research Fellow in Machine Learning at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence (CFI) where he leads a project on Trust and Transparency. He is very interested in all aspects of AI, its commercial applications and how it may be used to benefit society. He advises several companies and charities. Previously, Adrian held senior roles in finance. He received a PhD in computer science from Columbia University, and an undergraduate degree in mathematics from Trinity College, Cambridge.
16:15 – 17:00
by Founder & Lead Developer, Infinite 8 Aeronautics
This presentation aims to evaluate the question of how to best integrate A.I. into human society to maximize A.I., utility, acceptance, and assimilation into human society if endowed with the ability to understand human emotion.
The word “robot” was coined by the Czech writer Karel Capek, who penned a play entitled, “R.U.R., for Rossum’s Universal Robots. Deriving the word from the Czech word “robota,” meaning “drudgery” or “servitude”, Capek used “robot” to refer to a race of artificial humans who replace human workers in a futurist dystopia. As we integrate Artificial Intelligence into robots and other autonomous systems, what will the relationship between man and machine be? How will machines understand the human experience? How will humans work alongside machines? And how will the human race come to empathize and understand the plight of a future race of automated beings?
17:00 – 19:00
08:00 – 08:50
08:50 – 09:00
09:00 – 09:30
by VP, AI Products Group & GM, Architecture, Intel Corporation
09:30 – 10:00
by Founding Principal, Manganese
Machine learning and AI add uncertainty to product development because their level of performance can’t be guaranteed in advance. This uncertainty raises new strategic challenges in product development: How to quantify and measure the value of data? How to clearly define data science deliverables? When should an unsuccessful modeling effort lead to a product pivot?
This talk aims to provide a unifying framework to tackle these challenges. I will introduce the concept of product/data fit and explain how it relates to product/market fit. I will describe how product considerations determine prediction value and guide the choice of modeling metrics, and how the lean startup build-measure-learn methodology can be adapted to accelerate both product/market fit and product/data fit.
I will discuss case studies from healthcare and other verticals, highlighting guiding principles and common pitfalls and demonstrating how this approach can shorten time to market and help achieve financial business goals of AI driven products.
10:00 – 10:30
by Product Manager, IBM Watson
IBM leverages the power of Watson’s AI capabilities such as machine vision, natural language processing, audio processing, and digital assistants in its Internet of Things solutions to help businesses increase productivity, improve profitability and enhance decision making.
This session will cover the experiences and learnings from designing and implementing AI-based IoT solutions for customers in industries ranging from manufacturing to buildings. Subject areas discussed include designing for the human, using the right data, reducing time to value, and integrating the solution into your existing business processes.
The session is targeted at companies that want to improve their operations through Artificial Intelligence and/or Internet of Things solutions and the key takeaway for the audience will be how to get started with implementing AI.
10:30 – 11:00
AM Coffee Break
11:00 – 11:30
by CTO, Miso Robotics
Miso Robotics is pioneering the development of robotic kitchen assistants designed to adapt to existing equipment and infrastructure and learn from traditional cooking techniques, assisting food service workers with the most predictable and repetitive tasks. These artificially-intelligent machines share data on a global scale and learn from each other, enabling them to master a variety of tasks and to gain a continuously-improving understanding of how to interact effectively with their environments. The perception problem—how can a machine using a variety of sensors meaningfully understand the world around it?—the manipulation problem—how can a machine interact with its environment to achieve a desired outcome?—and the decision problem―how can a machine act to navigate a variety of scheduling constraints while interacting safely with external agents?―lie at the core of the challenge of bringing autonomous machines into the kitchen. Recent advances in computer vision using machine learning techniques combined with the availability of high-precision sensors and growing compute capacity in shrinking form factors are enabling the development of technology to solve these problems.
11:30 – 12:00
by CTO, calvIO
AI advances represent a great technological opportunity, but also possible perils. This The case outlined here involves Deep Learning Black-Boxes and their risk issues in an environment that requires compliance with legal rules and industry best practices. We examine a technological means to attempt to solve the Black-box problem for this case, referred to as “Really Useful Machine Learning” (RUMLSM). DARPA has identified such cases as being the “Third Wave of AI.”
12:00 – 12:30
GM, Product in Artificial Intelligence & Research, Microsoft
Product Manager, IBM Watson IoT
Data Science Manager, Wayfair
This is a session dedicated to women technology leaders, scientists and engineers in the data science world. Extraordinary women leaders who are pushing the boundary of the AI technology and business world will sit together to have an in-depth communication around topics like AI technologies, the future of data science, women power in technology leadership, women's career development as well as tips they'd like to share with peer women leaders and young ladies who regard them as role models.
13:00 – 14:00
14:00 – 14:30
by Senior Engineering Manager, Machine Learning, Slack
Since launching in 2013 with a mission to unify communication and make our working lives simpler, more pleasant, and more productive, Slack has taken the world by storm, quickly becoming the fastest-growing enterprise software company of all time. In this talk, I'll sketch the data-driven directions Slack's Search, Learning, & Intelligence team are exploring to build the business operating system of the future, and discuss the design process we use to prototype and ship features powered by machine intelligence.
14:30 – 15:00
by Senior Digital Data Analyst, Capital One
While the world is mostly focused on customer service part of the bot or bots solving mechanical issues, bots can significantly eliminate or reduce work for even a knowledge worker. A leader or a manager instead of digging down a report or deck or tapping on the shoulder of a junior analyst, could ask questions to a bot and get answers immediately – 24x7. This has immense cost and time savings for an organization. The bot would store the collective enterprise intelligence and be directly talking to the different databases. Leaders and managers could interact with the bots using chat, SMS, Email or Call. The talk will touch upon the need and applications of such a bot (within an enterprise), a cloud-based technical architect/,ture of the system and an early prototype demo that will showcase the possibilities of such a bot in an enterprise.
15:00 – 16:00
The brain has been an inspiration for AI since its inception. During the past 50 years, there has been enormous progress in theoretically and computationally understanding brain mechanisms and how they give rise to intelligent mental functions. However, current popular AI models, such as Deep Learning, do not include any of the major system designs that lead to human intelligence. Unlike Deep Learning, advanced brains are unexcelled in autonomously adapting in real time to changing environments that are filled with unexpected events. The computational principles that enable autonomy offer a major opportunity for designing more autonomous adaptive intelligent algorithms, machines, and robots in future AI applications. Autonomy is based on revolutionary computational paradigms, including complementary computing, which clarifies the global organization of brain architectures; hierarchical resolution of uncertainty, which clarifies why multiple processing stages are needed to overcome complementary computational deficiencies; and laminar computing, which clarifies why the cerebral cortex uses laminar circuits to support all higher biological intelligence. These paradigms have helped to explain how brains can rapidly and autonomously learn to recognize even rare events in real time; to selectively pay attention to valued objects and goals; to predict what to expect next; and to choose actions that maximize realization of valued goals. Current neural models also explain what happens in each of our brains when we consciously see, hear, feel, or know something; how all of these types of awareness are combined into coherent moments of conscious experience; and how unconscious events can influence our decisions and actions. These models also explain, from a deep computational perspective, why evolution was driven to discover conscious states, and how conscious awareness is linked to successful actions. Consciousness can hereby be understood as a natural outcome of the brain’s way of computing. The link between consciousness and action may have revolutionary implications for the design of future autonomous adaptive mobile robots. This talk will summarize some of these scientific developments, as well as neural algorithms that have been applied in large-scale engineering and technological applications.
16:00 – 17:00
What to expect
Our agendas consist of global and regional leading experts, curating talks on the latest hot topics and allowing you to understand the key take-aways from any presentation.
An exclusive event that boasts various activities for in-depth learning, experience sharing and effective networking, including keynotes, presentations, panel discussions, workshops, and much more.
A strict vendor and industry ratio control to avoid sales pitches and focus on real learnings and the exchange of relevant and effective knowledge.
A cross-industry mix of speakers and attendees to learn, network and collaborate through various interactive social sessions, including social breaks, buffet lunches, cocktail reception and Executive Dinner.
This year's summit will be held at the Boston Marriott Long Wharf. This 4-star, exclusive Boston Harbour retreat offers hospitality at its finest and a full range of luxury facilities.
Don't miss out on excellent room rates for our Summit delegates. Click the exclusive Big Data & AI Leaders Summit Reservation Link to book your stay.Book your stay
Sponsors and Media Partners
We’re always looking for brilliant sponsors to align with our global leadership Summits which are packed full of senior business leaders. With a select group of senior delegates we limit the number of sponsors for each Summits, but if your values connect with ours, please reach out to Thomas. We’d love to see you at an event soon.
Tickets and Price
The Artificial Intelligence Leaders Summit is America's foremost data technology and business intelligence conference. Our delegates are global leaders in big data, machine learning and artificial intelligence. Join them today.
Delegate numbers are limited so make sure you buy your ticket now. And if you sign up before May 5th 2018, enjoy an exclusive Early Bird discount.