SML: Deep Reinforcement Learning Special Edition @ Amazon
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Sydney Machine Learning is lucky enough to have Amazon as our host for this special edition Deep Reinforcement learning meetup. Come along for beer, pizza, networking and talks from Alex Long PhD Candidate in the AI group at UNSW focusing on Deep Reinforcement Learning & Alasdair Hamilton CEO of Remi.ai for two extremely interesting talks on Reinforcement Learning.
Deep Reinforcement Learning is behind the recent success of ML algorithms being able to learn how to play Atari 2600 games from raw pixel outputs & also AlphaGo, Deepminds machine learning system that overthrew Go world champions, including Lee Sedol in 2016.
This session of talks will focus both on the practical side of RL, with Alasdair’s talk focusing on where RL can be actively applied within your business & Alex’s talk taking us into a technical dive of modern Deep Reinforcement Learning techniques.
Sydney Machine Learning will also be announcing something really special with regards to Reinforcement Learning which we have been working on since August last year, so if you would like to reserve your spot and find out more, see you on the 8th ;)
Alasdair Hamiltons Talk:
The future of Artificial Intelligence is, at least partly, rooted in Reinforcement Learning. During our presentation, the team from Remi AI will take attendees on a journey through their experiences in Reinforcement Learning. Special attention will be paid to the areas in which the team have been able to apply Reinforcement Learning in a commercial setting and the four mammalian methods of learning, and how they inspire us. Remi AI has applied RL to budget and bid management, to dynamic pricing and web design, to large scale management of power requirements, inventory management, predictive maintenance. The talk will conclude with a discussion on future applications, as well as a roadmap for those looking to start out in the space, then Q&A.
Alasdair Hamilton has cemented himself as a voice of authority in A.I in Australia. Since first encountering the concepts while studying philosophy in 2013, Alasdair has built a successful A.I research firm (Remi AI) that constantly pushes the boundaries of A.I methodologies whilst also applying said methods in real businesses solving real problems. Wearing both CEO and CTO hats, Alasdair knows what is required to run a successful A.I business, bringing multiple platforms to market, in a staggeringly wide number of fields.
Alex Longs Talk:
Deep Reinforcement Learning (Deep-RL) is the combination of traditional RL algorithms with the high-dimensional function approximation methods of deep learning. This combination
allows Deep-RL to eclipse human performance on systems of previously intractable state-spaces and high branching factors, such as the game of GO, Atari arcade games, and heads up limit poker. In this talk I will focus on the intuition behind Deep-RL, how it compares (and differs) to other machine learning methods, as well as discuss some potential commercial applications.
Alex Long is a Computer Science PhD Student at the University of New South Wales (UNSW) supervised by Alan Blair. His primary research topic is Deep Reinforcement Learning, specifically the application of RL methods to the NLP domain. Prior to UNSW Alex studied an MSc in Electrical Engineering at the Institute for Cognitive Systems, within the Technische Universität München (TUM) where he published work on artificial skin for humanoid robotics.
SML: Deep Reinforcement Learning Special Edition @ Amazon