As our Global Deep Learning Summit Series draws closer, we’re casting forward to the three track event in San Francisco in January 25 & 26. The 4th annual San Francisco Deep Learning Summit will be joined by the first ever Deep Learning for Enterprise Summit as well as the fifth global Virtual Assistant Summit.
This event has sold out for the past three years, so we have increased the capacity due to high demand: register here to hear from the likes of Google Brain, OpenAI and many more cutting-edge industry leaders.
Deep learning is advancing rapidly and holds great promise for analysing unstructured data, but there are obstacles in its implementation: it’s hard to do, it requires large amounts of data, and it uses a lot of processing power. (TechCentral) Pioneers in the industry are working to overcome this, and we are excited to hear from some of the leading industry professionals, academics, startups, and businesses in the field across the three track event.
Confirmed speakers for the Deep Learning Summit include Ian Goodfellow, Staff Research Scientist working in machine learning at Google Brain and one of the world’s leading AI researchers, and Andrej Karpathy, Research Scientist at OpenAI who has been referred to as ‘a central node in AI research dissemination’.
Ian, who is known best for inventing generative adversarial networks (GANs) has also contributed to several publications as well as authoring the textbook Deep Learning. GANs are AI algorithms used in unsupervised machine learning, implemented by a system of two neural networks competing against each other in a 'zero-sum game' framework which many AI-centric companies such as Facebook rely heavily on. Yann LeCun who oversees AI research at Facebook has called them 'the coolest idea in deep learning in the last 20 years.' Ian, who will talk about how his work is pushing towards fully unsupervised machine learning, states that 'what AI cannot create, it does not understand’.
Ian spoke at the Deep Learning Summit in San Francisco this January. Watch his presentation here.
At OpenAI, Andrej is currently working on DL in computer vision as well as generative modelling and reinforcement learning. Alongside his PhD and work at OpenAI, he has worked with Fei-Fei Li (Stanford) on convolutions/recurrent neural network architectures and their applications in computer vision, natural language processing and their intersection. Andrej also designed and taught the first DL course at Stanford class with Fei-Fei on Convolutional Neural Networks for Visual Recognition. This class has grown from 150 enrolled in 2015 to 330 students in 2016, and 750 students in 2017. At the Deep Learning Summit in January, we will hear about Andrej’s most current and cutting edge work.
Deep learning is emerging as one of the most important technologies in enterprise computing, and it is estimated that by 2024 the software market will have surpassed $10.4 billion.
We are launching this enterprise track to explore the advancement of deep learning applications in industries such as healthcare, finance, retail, manufacturing and utilities where research is progressing more rapidly than previously estimated. We will hear from pioneering minds and researchers using deep learning in enterprise to optimise business efficiency in areas including: risk analysis, demand and supply optimisation, sentiment analysis, and market targeting.
As part of this Summit we will hear from CEOs, product managers, data scientists and developers as well as founders and academic researchers working in the field. Over the coming months and years, AI in enterprise will continue to expand, and these discussions and presentations will reveal the emerging research and progressions in the space.
Previous speakers include: |
Melody Guan, Deep Learning Resident, Google Brain; Richard Socher, Chief Scientist, Salesforce; Bryan Catanzaro, VP of Applied Deep Learning Research, NVIDIA; Brendan Frey, Co-Founder & CEO, Deep Genomics and many more.
A complete list of speakers will be announced soon, so register now to avoid disappointment.
‘Virtual assistants can be a blessing to your business and boost productivity immensely. They can free you up from tedious tasks such as data entry, bookkeeping or updating contact lists at a cost that won't break the bank.’
The Virtual Assistant Summit will be exploring how AI and deep learning can be applied to create chatbots and conversational interfaces to create deeper, more personaliszd one-to-one customer experiences. Whilst VAs came to life in the 60s with sci-fi movies depicting humans with robotic assistants, the reality is far more practical and these VAs are being optimised to overcome real-world problems from monotonous tasks, to apps that can assist the disabled.
Past speakers on this track include: |
Lionel Cordlesses, Innovation Project Manager, Renault; Pilar Manchon, GM of Voice & Digital Assistance, Intel; Alonso Martinez, Technical Director, Pixar Animation Studios; Anjuli Kannan, Software Engineer, Google; Deborah Harrison, Editorial Writer, Cortana and many more.
Can't make it to San Francisco? Find out more about the other events in the Global Deep Learning Summit Series:
22 November 2017, London
Leading minds in healthcare and machine intelligence will come together for an evening of networking and keynote presentations around tools & techniques set to revolutionise healthcare applications, medicine & diagnostics. Join us for a three course meal to support and showcase women in Healthcare and Machine Intelligence.
23 January 2018, San Francisco
Leading minds in machine intelligence will come together for an evening of networking and keynote presentations. Join us for a three course meal to support women in AI and Machine Intelligence.
25 January 2018, San Francisco
The Deep Learning Summit is the next revolution in artificial intelligence. The increasingly popular branch of machine learning explores advances in methods such as image analysis, speech and pattern recognition, natural language processing, and neural network research. This summit will explore how deep learning algorithms and methods are being applied to solve challenges in industries including healthcare, manufacturing, transport, security and communications.