The combination of deep learning & reinforcement learning to achieve the goal of human-level intelligence

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A Brief Overview of Deep Learning from Google's Ilya Sutskever. What’s so special about deep learning? Why does it work now, and how does it differ from neural networks of old? How will it impact your industry? Hear more from Ilya at the summit.

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Karpathy and colleagues have created artificial intelligence software capable of recognizing and describing the content of photographs and videos with far greater accuracy than ever before, sometimes even mimicking human levels of understanding.

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They are a dream of researchers but perhaps a nightmare for highly skilled computer programmers: artificially intelligent machines that can build other artificially intelligent machines.

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Google DeepMind won the Innovation Lions Grand Prix for AlphaGo, a computing system that for the first time beat the best human player at Go, an ancient game that is much more complex than chess. The Artificial Intelligence system was developed in the U.K. by DeepMind, a company acquired by Google in 2014.

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Sofia explains the sorts of problems faced by each of the research teams - Multi-Agent Systems (MAS), Reinforcement Learning (RL) and Probabilistic Modelling (PM) - and the kinds of solutions and strategies PROWLER.io use to solve them.

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Deep reinforcement learning (DRL) is an exciting area of AI research, with potential applicability to a variety of problem areas. Osaro is one AI company recognised to be applying DRL in the industrial space.

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UC Berkeley researchers have developed algorithms that enable robots to learn motor tasks through trial and error using a process that more closely approximates the way humans learn, marking a major milestone in the field of artificial intelligence.

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Among his many accomplishments, Ba developed the Adam Optimizer, one of the go-to algorithms to train deep learning models. He was also one of the first students from a Canadian institution to win a Facebook PhD Fellowship.

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Stanley J. Osher has been elected to the National Academy of Engineering, for contributions to imaging, computer vision, and graphics including level-set methods and efficient compressed sensing.

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There are some estimates that five percent of all AI talent within the private sector are currently employed by Google. Perhaps no one among that rich talent pool has as deep a set of perspectives as Geoff Hinton. He has been involved in AI research since the early 1970s, which means he got involved before the field was really defined.

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Why Attend

Speakers

Extraordinary Speakers

Discover advances in deep reinforcement learning algorithms & methods from the world's leading innovators, from research pioneers to industry leaders, deploying applications of deep reinforcement learning in the real world, e.g. robotics, recommendations & manufacturing.

Tech

Discover Emerging Trends

The summit will showcase academic advancements of deep RL as well as their impact in business & industry. Where do the challenges still lie in research? How can companies leverage progress? How can we apply the notion of learning from environment to process inputs & choose complex actions?

Network

Expand Your Network

A unique opportunity to interact with engineers, research scientists, professors, and startups leading the deep reinforcement learning progression. Learn from & connect with 450+ industry innovators & researchers sharing insights, trends, recent discoveries & best practices.

Who

Who Should Attend

  • Research Scientists
  • Engineers
  • CTOs
  • Founders
  • ML Engineers
  • Software Engineers
  • Research Engineers
  • Data Scientists
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Join the discussion

  • 60 speakers
  • 450 leading technologists & innovators
  • Technical Talks & Practical Applications
  • Interactive workshops
  • 12 + hours of networking
  • Access to all the filmed presentations
  • Discover technology shaping the future
Document

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View the summit brochure and all the information you need to convince your boss that attending the summit will help future-proof your business.

Topics we cover

Neural Networks
Neural Networks
Reinforcement Learning
Reinforcement Learning
Swarm robotics
Swarm robotics
Imitation Learning
Imitation Learning
Deep Learning
Deep Learning
Meta-Learning
Meta-Learning
End-to-End Learning
End-to-End Learning
Multi-Task Learning
Multi-Task Learning

Previous attendees Include

Amazon
DeepMind
Google
UC Berkeley
Accenture
Microsoft
Capital One
osaro
facebook
openai
Imperial
Insight Robotics

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For Group Rates, Not-for-profit & Government Rates, please contact John McNicholas via john@re-work.co for more information.

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