Nvidia GPU Technology Conference (GTC) 2017 Keynote- 1. Moore’s Law is finished 2. Project Holodeck – Allows collaborate on photo-realistic models in Virtual Reality (VR) 3. Demo of Deep Learning (DL) and Ray Tracing 4. Introducing the Tesla V100 – The most advanced deep learning GPU 5. Next-generation DGX-1 6. GPU accelerated cloud 7. Toyota selects Nvidia’s Drive PX platform for its autonomous platform 8. Integrated Robot Simulator ISAAC – Robot learns in VR instead of physical movements
Watch Rachel Thomas’s talk, “How to Learn Deep Learning (When You’re Not a Computer Science PhD)” from the free, live online Demystifying Data Science conference hosted by Metis on September 27, 2017. Rachel Thomas has a math Ph.D. from Duke and was selected by Forbes as one of “20 Incredible Women Advancing AI Research”. She is co-founder of fast.ai and a researcher-in-residence at the University of San Francisco Data Institute. Her background includes working as a quant in energy trading, a data scientist + backend engineer at Uber, and a full-stack software instructor at Hackbright.
Bias Traps in AI: A panel discussing how we understand bias in AI systems, highlighting the latest research insights and why issues of bias matter in concrete ways to real people. Solon Barocas, Assistant Professor of Information Science, Cornell University Arvind Narayanan, Assistant Professor of Computer Science, Princeton University Cathy O’Neil, Founder, ORCAA Deirdre Mulligan, Associate Professor, School of Information and Berkeley Center for Law & Technology, UC Berkeley John Wilbanks, Chief Commons Officer, Sage Bionetworks AI Now 2017 Public Symposium – July 10, 2017 Follow AI Now on Twitter: https://twitter.com/AINowInitiative Subscribe to our channel: https://www.youtube.com/c/ainowinitiative Visit our website: https://artificialintelligencenow.com
Kate Crawford is a leading researcher, academic and author who has spent the last decade studying the social implications of data systems, machine learning and artificial intelligence. She is a Distinguished Research Professor at New York University, a Principal Researcher at Microsoft Research New York, and a Visiting Professor at the MIT Media Lab. December 5th, 2017
Best 5 Humanoid Robots 2017, You’ll Intend to Buy – Inmoov, EZ Robot, Poppy, Plen 2, Kengoro, —————————————————————————————————— Join Amazon Prime For Amazing Offers(Free 30 Days Trial) : http://amzn.to/2HjTpKM ——————————————————————————————————- ——————————————————- You can buy on Amazon: JD Humanoid – Products – EZ-Robot Amazon: http://amzn.to/2GOTI0C ——————————————————— Do you have any idea about smart home robots? Here are the best 5 humanoid robots that you can buy right now. the futuristic modern robots are available in the market now. They are very intelligent robots. These all are so expert and very helpful to be part of your daily life. They can do lots of works even think like a human being and help you in your every task of your dailies life, you can not imagine. In a word, They are superb, Incredible. Here are the details and the links for the robots are given below. 1. JD Humanoid – EZ Robot. JD Humanoid – Products – EZ-Robot Amazon: http://amzn.to/2GOTI0C JD is a fully functional humanoid robot kit built with ez-bits and invented in Canada. This WiFi enabled humanoid robot is easy, fun and educational! JD boasts 16 degrees of freedom with metal gear heavy duty servo motors. That means he has 16 motorized joints for walking, dancing or anything that you teach him! The camera in the head of this robot provides vision recognition to track color, motion, glyphs, QR codes, faces and more. There are 18 RGB LEDs in the eyes of JD, which can be easily programmed and animated [More]
AI With The Best hosted 50+ speakers and hundreds of attendees from all over the world on a single platform on October 14-15, 2017. The platform held live talks, Insights/Questions pages, and bookings for 1-on-1s with speakers. We will discuss multiple ways in which healthcare data is acquired and machine learning methods are currently being introduced into clinical settings. This will include: 1) Modeling disease trends and other predictions, including joint predictions of multiple conditions, from electronic health record (EHR) data using Gaussian processes. 2) Predicting surgical complications and transfer learning methods for combining databases 3) Using mobile apps and integrated sensors for improving the granularity of recorded health data for chronic conditions and 4) The combination of mobile app and social network information in order to predict the spread of contagious disease. Current work in these areas will be presented and the future of machine learning contributions to the field will be discussed. http://withthebest.com/ https://twitter.com/WithTheBest https://www.facebook.com/WithTheBestConf
Speaker: Toby Walsh The AI Revolution will transform our political, social and economic systems. It will impact not just the workplace, but many other areas of our society like politics and education. There are many ethical challenges ahead, ensuring that machines are fair, transparent, trustworthy, protective of our privacy and respect many other fundamental rights. Education is likely to be one of the main tools available to prepare for this future. Toby Walsh, Scientia Professor of Artificial Intelligence at Data61, University of New South Wales will argue that a successful society will be one that embraces the opportunity that these technologies promise, but at the same time prepares and helps its citizens through this time of immense change. Join him in this session, aiming to stimulate debate and discussion about AI, education and 21st century skill needs. www.oeb.global
Self-driving technology consists of processing of sensing data, the handling of HD-maps and the decision making processes required for merging safely into dense traffic – a process we call “driving policy”. While processing sensing data is all about understanding and modeling the Present, Driving Policy is about modeling the Future. Modeling the future raises new challenges of how machine learning should be incorporated to allow on one hand advanced human-like negotiation skills required for merging into dense traffic while guaranteeing functional safety. Talk given at Bosch ConnectedWorld Conference 2017. Prof. Shashua at World Knowledge Forum: Platform for Safe & Scalable AVs – https://youtu.be/7dLQQcR9kGM Take a ride in Mobileye’s autonomous car: https://youtu.be/L1Bmc61l99A Mobileye Three Major Pillars of Technology for Autonomous Car CES 2017 – https://youtu.be/yC7Bef_Mm-s Autonomous Car Driving with Prof. Amnon Shashua – https://youtu.be/dhEgD6ZFlQE Mobileye’s Autonomous Car – What the System Sees – https://youtu.be/jKfwHsHUdVc Autonomous Car Technology – http://www.mobileye.com/our-technology/ Subscribe now to Mobileye on YouTube: https://bit.ly/2vRes7k About Mobileye: Mobileye’s advanced driver assistance systems (ADAS) technology is deployed in more than 50 million vehicles today and is integrated into hundreds of new car models from the world’s major automakers including Audi, BMW, FCA, Ford, General Motors, Honda, Hyundai, Kia, Nissan, Volkswagen, and more. Mobileye began with the vision of reducing vehicle collisions and resulting injuries and fatalities. Today, Mobileye makes one of the most advanced collision avoidance systems on the market, while working toward autonomous driving and the coming autonomous mobility-as-a-service (MaaS) revolution in road safety. Connect with Mobileye: Visit the [More]
Human Computer Integration versus Powerful Tools Umer Farooq, Jonathan Grudin, Ben Shneiderman, Pattie Maes, Xiangshi Ren CHI ’17: ACM CHI Conference on Human Factors in Computing Systems Session: Human Computer Integration versus Powerful Tools Abstract In 1960, JCR Licklider forecast three phases for how humans relate to machines: human-computer interaction, human-computer symbiosis, and ultra-intelligent machines. Have we moved from interaction to symbiosis or integration, should we focus on this or on other aspects of human augmentation via powerful tools, and how will such decisions affect us as designers, researchers, and members of society? This panel will raise uneasy and disruptive HCI notions. For example, we will debate whether integration is a necessary and desirable next phase, or whether it could undermine human self-efficacy and control and lessen the predictability of machine actions. DOI:: http://dx.doi.org/10.1145/3027063.3051137 WEB:: https://chi2017.acm.org/ Recorded at the ACM CHI Conference on Human Factors in Computing Systems in Denver, CO, USA May 6-11, 2017
For more on IDE lunch seminars, go to ide.mit.edu
Toby Walsh (Professor of Artificial Intelligence, UNSW Sydney | Future of AI, AI & Robotics), Rupert Steffner (Founder, WUNDER.ai (Customer Experience, Personal Shopping)) & Viviane Hülsmeier (Co-Funder, CoPlannery (Machine Learning in Construction)) discuss about “Perspectives and Progress of AI” at hub.berlin on November 28th 2017. hub.berlin is Europe’s interactive business festival for digital movers and makers. hub.berlin brings together key players of Europe’s leading industries, politics and 500+ startups in a unique environment to discuss, shape and experience the digital transformation. Learn more at www.hub.berlin www.bitkom.org www.bitkom.org/Themen/Digitale-Transformation-Branchen/Digital-Hubs-Themenseite/ www.unsw.edu.au https://wunder.ai/ www.coplannery.com
Stuart Russell, Professor at UC Berkeley and AI pioneer explains how it will be up to us to teach robots how to make the right decisions. The Hello Tomorrow Global Summit 2017 www.hello-tomorrow.org Credits to Web Style Productions, BETAVITA and IMMAGINARTI Digital & Video
AI powered analytics platform for water companies to prevent water wastage, predict asset failures, and minimize operating costs. Learn more about the company here — https://www.slideshare.net/500startups/500-demo-day-batch-19-pluto-ai
Discover the latest innovation and the positive impact of Artificial Intelligence technologies. The Applied AI Conference is a must-attend event for people who are working, researching, building, and investing in Applied Artificial Intelligence technologies and products. Panel: Deal with AI Susan Altman, Partner, K&L Gates LLP Eric Save, Partner, K&L Gates LLP
Discover the latest innovation and the positive impact of Artificial Intelligence technologies. The Applied AI Conference is a must-attend event for people who are working, researching, building, and investing in Applied Artificial Intelligence technologies and products. Panel: The AI-powered Transportation Renaissance Moderator: Li Jiang, Investor, GSV Asset Management Speakers: Raj Rao, CEO, Ford Smart Mobility Jan Erik Solem, CEO and Co-Founder, Mapillary Trevor Darrell, Professor, UC Berkeley – Director, Berkeley Deep Drive (BDD) Jeremy Stanley, VP of Data Science, Instacart
Panel at France is AI 2017: Education: Training future AI experts With: Nicolas Vayatis (CMLA) Sébastien Provencher (ElementAI) Natalie Cernecka (OpenClassrooms) Steve Kuyan (NYU Future Labs) Moderated by: Julie Josse (Polytechnique) Video credit: VLAM
Educator and entrepreneur Sebastian Thrun wants us to use AI to free humanity of repetitive work and unleash our creativity. In an inspiring, informative conversation with TED Curator Chris Anderson, Thrun discusses the progress of deep learning, why we shouldn’t fear runaway AI and how society will be better off if dull, tedious work is done with the help of machines. “Only one percent of interesting things have been invented yet,” Thrun says. “I believe all of us are insanely creative … [AI] will empower us to turn creativity into action.”
Short introduction to the day, to RISE SICS and reflect on our mission – To act for sustainable growth in Sweden.
GPU Technology Conference 2017 kicks off with a powerful video showing how AI is changing our world. NVIDIA CEO and founder Jensen Huang welcomes the thousands of attendees to the largest gathering of GPU developers each year.
Discover the latest innovation and the positive impact of Artificial Intelligence technologies. The Applied AI Conference is a must-attend event for people who are working, researching, building, and investing in Applied Artificial Intelligence technologies and products. Cybersecurity: AI, Friend or Foe? Moderator: Bradley Rotter, Impact Investor Speakers: Mark Weatherford, Chief Cybersecurity Strategist, vArmour Herb Kelsey, CTO, New Context Services Matt Wolff, Chief Data Scientist, Cylance
Discover the latest innovation and the positive impact of Artificial Intelligence technologies. The Applied AI Conference is a must-attend event for people who are working, researching, building, and investing in Applied Artificial Intelligence technologies and products. Fireside Chat Moderator: Benjamin Levy, Co-founder BootstrapLabs Speaker: Akli Adjaoute, Founder, President and CEO Brighterion
Presented at Cognitive Computational Neuroscience (CCN) 2017 (http://www.ccneuro.org) held September 6-8, 2017.
It takes nature and evolution more than five hundred million years to develop a powerful visual system in humans. The journey for AI and computer vision is about fifty years. In this talk, I will briefly discuss the key ideas and the cutting edge advances in the quest for visual intelligences in computers. I will particularly focus on the latest work developed in my lab for both image and video understanding, powered by big data and the deep learning (a.k.a. neural network) architecture. Fei-Fei Li, Chief Scientist, AI/ML, Google Cloud, Professor of Computer Science, Stanford University Director, Artificial Intelligence Lab
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AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and automatic speech recognition (ASR) with Amazon Lex, visual search and image recognition with Amazon Rekognition, text-to-speech (TTS) with Amazon Polly, and developer-focused machine learning with Amazon Machine Learning. For more in-depth deep learning applications, the AWS Deep Learning AMI lets you run deep learning in the cloud, at any scale. Launch instances of the AMI, pre-installed with open source deep learning engines (Apache MXNet, TensorFlow, Caffe, Theano, Torch and Keras), to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques; all backed by auto-scaling clusters of GPU-based instances. Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud. Learning Objectives • Learn about the breadth of AI services available on the AWS Cloud • Gain insight into practical use cases for Amazon Lex, Amazon Polly, and Amazon Rekognition • Understand why Amazon has selected MXNet as its deep learning framework of choice due its programmability, portability, and performance