At the heart of artificial intelligence (AI) is data. AI needs knowledge. Read the takeaways from Yoshua Bengio's Keynote "Deep Learning Frameworks" from the Deep Learning Summit, Boston 2016, to learn how Deep Learning has progressed through time starting from supervised learning, progressing to speech recognition and computer vision, until it reached human level processing.
Topics: Big Data, Deep Learning, A I, Deep Learning Summit
In January, we held the Deep Learning Summit and Virtual Assistant Summit in San Francisco, with presentations from experts at OpenAI, Google, Facebook, Stanford University, Netflix, x.ai, Yale University, Slack, Jibo, UC Berkeley and more. Read on for presentations by Ilya Sutskever, Research Director at OpenAI, and Anjuli Kannan, Software Engineer at Google.
Topics: Machine Learning, Deep Learning, Virtual Assistant Summit, A I
RE•WORK announces its 11th global Deep Learning Summit in Singapore taking place on 27-28 April 2017. RE•WORK will bring together AI pioneers from various industries to explore the latest advancements in the deep learning. Topics covered at this event will include Deep Learning Algorithms,Autonomous Vehicles,AI for Business Efficiency, Deep Learning for Enterprise, and Predictive Intelligence.
Topics: Deep Learning, Press Releases, Deep Learning in Finance Summit, FinTech
Although deep learning models are giving increasingly advanced results in diverse problems, their lack of interpretability is a major problem, especially in fields such as genomics. We spoke to Avanti Shrikumar, a PhD student in Computer Science at Stanford University, to learn more.
Topics: Big Data, Deep Learning, Data Mining, MedTech
The technologies driving forward a new era of autonomous vehicles have been accelerating exponentially in the past few years. The futuristic cars that until recently were only found in science fiction could be with with us sooner than you think, with the global connected car market size is expected to reach $180 billion by 2022. We spoke to Bryan Mistele, President and CEO of INRIX, about how breakthroughs in location technology, connectivity and big data are poised to transform urban mobility.
Topics: Machine Learning, Deep Learning, A I, Smart Transport
Today’s healthcare system was not built for a seamless integration of rapidly emerging technologies, such as machine learning innovations. In this video presentation from the 2017 Deep Learning Summit in San Francisco, Will Jack, CEO of Remedy Health, explores the difficulties of integration and deployment, and how interpretable models can better tackle tasks such as diagnosis, physician education and treatment planning.
Topics: Healthcare, Deep Learning, Diagnostics, A I
On March 23 & 24, we will be holding our first Machine Intelligence in Autonomous Vehicle Summit in San Francisco. Autonomous vehicles has been the latest obsession of every car enthusiast and manufacturer, throwing themselves into endless research and testings to create safer, smarter and more efficient transport.
Topics: Machine Learning, A I, Autonomous Vehicles, Speech Recognition
Current AI solutions, deemed “narrow AI”, are essentially task-specific - they learn to do one, well-defined task extremely well. A general AI system, on the other hand, will be capable of “learning how to learn”, much in the same way a human does. We spoke to Olga Afanasjeva, Director of the General AI Challenge, which is launching today in an effort to progress to beneficial general-purpose AI.
Topics: Machine Learning, Neural Networks, Deep Learning, A I
On 11 February we celebrated the 2nd annual International Day of Women & Girls in Science, in an effort to achieve equal access to and participation in science for women and girls. We spoke to Nandini Stocker, one of Google's leading women in conversational technologies, to explore how she came to work in this field, recent advancements in human-computer interaction, and predictions for the future of speech recognition.
Topics: International Day of Women and Girls in Science, Women in Tech, Virtual Assistants, A I
Deep learning techniques can be used to extract facial imaging biomarkers of human health status and to track the effects of cosmetic interventions. Anastasia Georgievskaya, Research Scientist at Beauty.AI will be presenting a set of tools for analysis of perception of human age and health status.
Topics: A I, Healthcare, Deep Learning in Healthcare Summit, Deep Learning