Deep Learning & Deep Learning in Healthcare Summits, Boston: What to Expect

For the past three years, RE•WORK has hosted their series of evolving AI events in Boston, and are returning this May 24 - 25 for what is set to be the biggest co-located Boston event to date. For the second year and back by popular demand, this year the event will consist of the Deep Learning Summit, the Deep Learning in Healthcare Summit and the first ever Boston workshop track, bringing together 600 experts from industry and academia.

This event has been expanded due to popular demand and will see over 80 speakers coming together over the two days to share their latest advancements and breakthroughs in AI and deep learning. As the event has grown we have welcomed new attendees, speakers and sponsors each year as well as returning attendees who continue to benefit from the wealth of knowledge and expertise year on year.

Deep Learning Summit & Deep Learning in Healthcare Summit, returning companies: 25%

Who have we heard from?

At previous editions of the Deep Learning Summit, we’ve heard from the likes of Google, Facebook, Flickr, Amazon, Apple, Twitter, and countless other industry leads. Several of these experts will be returning in May to present their most current work, along with new editions such as PayPal, Mozilla, TripAdvisor and more.

Last year on the Deep Learning track, David Murgatroyd, Machine Learning Leader at Spotify spoke about agile deep learning and explained how deep learning has been called the ‘new electricity’ — transforming every industry. Innovative architectures and applications receive deserved attention. But to turn innovation into value requires integrating deep learning into practical technology products. Such products, including Spotify's, are often developed following the principles of agile.

Watch David's presentation here.

The smart AI revolution is here, and year on year it's exciting to hear the progressions made both in academia and real-world applications in industry. The Summits in Boston will bring together experts from across the board working in research, startups, large corporations and a multitude of other areas, with attendees being made up of CEOs, CTOs, Data Scientists, PhD Students, and many more. This year, we're excited to hear how Amazon are using neural networks for forecasting demand, how TripAdvisor use deep learning to improve photo selection, and how MIT Media Lab leverage deep learning to transfer knowledge from emojis.

Over on the Deep Learning in Healthcare Summit, Junshui Ma, Senior Principal Scientist at Merck spoke about how we can predict molecule activity with its structure, and whether deep neural networks are an evolutionary solution or a revolutionary one. Quantitative structure-activity relationship (QSAR) is a technique used in pharmaceutical industry to find out a molecule’s efficacy and safety from its molecule structures using computer models, instead of doing lab tests. A number of independent efforts, including Marck's, has shown that Deep Neural Networks (DNNs) can outperform existing QSAR methods. However, the improvements are frequently only marginal. Thus, using DNNs can only be claimed as an evolution in QSAR. Watch Junshui's presentation to learn more.

As the capabilities of deep learning progress, as will the impact of these technologies on the evolution of healthcare. At this year's edition of the summit, we will hear from the likes of Berg Health, GlaxoSmithKline, Accenture, Google Brain, Philips Research and many more companies and institutions at the forefront of cutting-edge progressions. The topics covered in the two days will include speech recognition, personalised medicine, diagnostics, clinical patient care, MedTech, AI assistants and many more.

'The Deep Learning summit brings together a fantastic collection of people from diverse areas of the field, from both academia and industry' Drew Volpe, First Star Ventures

'Speakers gave presentations of issues that could be broadly applied to other areas which made the varied topics (imaging, genetics, EHR, etc) very enjoyable. I liked the mix of computational and business problems presented.' Ryan Morton, Data Smart Solutions

What's new?

At all RE•WORK summits, attendees are free to watch presentations and attend panel discussions across all tracks, and after a successful introduction of a workshop track at the Deep Learning Summit in San Francisco earlier this year, we're excited to launch this in Boston. Something that makes RE•WORK really unique is the fusion of business applications and research in all aspects of AI, and the workshops will provide a hands-on experience for anyone keen to learn about new applications of deep learning. On day 1, sessions will include a practical session in creating a data product, a panel discussion covering the ROI of deep learning applications, and an open floor and networking session with experts answering general deep learning questions. Day 2 will see presentations on real-life use cases, a roundtable discussion with leading experts exploring the future of deep learning in the workplace, and a panel discussion focusing on the hot topic of AI for Good.

In San Francisco, NVIDIA, one of the workshop hosts explained how they're at 'all about helping people solve challenging problems using AI and deep learning - we help developers, data scientists and engineers.’

Previous workshop hosts include Sightline Innovation, Accenture, Consortium for Safer AI, useAIble, Solvvy, Chatbase and more.

Podcast & Interviews

As well as presentations, workshops, and 7 hours of networking with global industry experts, attendees will also receive exclusive content from the Summit. Guests will receive access to videos and slides from all presentations on the track they are registered to, as well as behind the scenes content such as video interviews, fireside chats, and a post-event summary document. Throughout the Summit, our content team speak with the most influential speakers and attendees who we feature on both the Women in AI podcast, and in panel interviews and discussions hosted by ourselves as well as leading technology journalists.