Artificial Intelligence (AI) and Blockchain

Friday, October 13, 2017

Medical Imaging with Virtual & Augmented Reality and Artificial Intelligence AI

Elon Musk's Dreams and Worries on AI safety, self-driving Tesla and Mars colonization

The iconic entrepreneur behind SpaceX, Tesla Motors and Paypal shares his predictions and worries for artificial intelligence, renewable energy and space exploration, in conversation with DFJ General Partner Steve Jurvetson at Stanford on Oct. 7, 2015. University President John Hennessy introduces the future-focused discussion, which follows Musk's journey from his first Internet startup in the mid-nineties to his dream of a Mars colony in the next 20 years.

How AI Helped Donald Trump Win US 2016 Presidential Election |Cambridge Analytica

Molly Schweickert from Cambridge Analytica on "How digital advertising worked for the US 2016 presidential campaign"

Friday, October 6, 2017

The Age of Cryptocurrency and The End of Fiat Currency | Paul Vigna and Michael Casey

A cyber-phenomenon that became a buzzword virtually overnight, Bitcoin constantly makes headlines, fueling endless media debate over its viability. And though today it can be used to buy almost anything, few understand the controversial currency and most think it will never be mainstream. So should we even care about Bitcoin?

In THE AGE OF CRYPTOCURRENCY: How Bitcoin and Digital Money are Challenging the Global Economic Order (January 27), leading WSJ financial writers Paul Vigna and Michael J. Casey argue Bitcoin represents a monumental paradigm shift that will transform the social, political and economic landscape. Since its advent, Bitcoin has gained a reputation for instability and illicit business; naysayers fear its power to eliminate jobs and upend the concept of a nation-state. Vigna and Casey show that cryptocurrencies can also bring good. For one, they remove the middleman from the financial system, giving the power to the people and safeguarding from the devastation of a 2008-type crash. They also promote financial equality; Bitcoin has already given the world's unbanked—those marginalized billions who’ve never had a bank account—unprecedented access to the global economy.

Regardless of its long-term effects, Vigna and Casey prove we can’t ignore Bitcoin; for better or worse, it’s here to stay. A critical, accessible look at a global phenomenon, THE AGE OF CRYPTOCURRENCY demystifies virtual currency and explains its origins, its functions, its potential value and how to navigate the new global cyber-economy.

The book published to great reviews, including in The Economist and Fortune. Harvard historian Niall Ferguson raved that “you need to read The Age of Cryptocurrency today” and leading VC Marc Andreessen likewise called it a “must-read.”

ABOUT THE AUTHORS

PAUL VIGNA is a markets reporter for The Wall Street Journal, covering equities and the economy. He is a columnist and anchor for MoneyBeat. Previously a writer and editor of the MarketTalk column in DowJones Newswires, he has been a guest on the Fox Business Network, CNN, the BBC, and the John Batchelor radio show. He has been interviewed by Bitcoin magazine and appeared on the Bitcoins & Gravy podcast, and boasts a collective 20 years of journalism experience.

MICHAEL J. CASEY writes for The Wall Street Journal, covering global finance in his "Horizons" column. He is a frequent contributor to the Journal's MoneyBeat blog and co-authors the daily "BitBeat" with Paul Vigna. He is the host of the book-themed video series "WSJ Afterword" and a frequent guest on and host of "The News Hub" and "MoneyBeat." His podcast on world economic affairs is forthcoming. Casey has written for such publications as Foreign Policy, The Washington Post, and The Financial Times. He is the author of two books: Che's Afterlife: The Legacy of an Image (Vintage, 2009), one of Michiko Kakutani's "best books of 2009," and The Unfair Trade: How Our Broken Financial System Destroys the Middle Class (Crown, 2012).

NYU Professor: JP Morgan is Wrong! Blockchain is the Real Innovation!

How Practical It Is To Live On Bitcoin Without Paper Money In 2017?

With all the excitement around bitcoin, we wondered if one person could live off of this virtual currency without paper money for a week in 2017

Elon Musk: Making Life Multiplanetary With Long-Term Technical Breakthroughs

Mark Cuban has Investment in Twitter and Bitcoin, Long AI and Blockchain

Thursday, October 5, 2017

Yann LeCun: Predictive Learning | Artificial Intelligence (AI) | NIPS Co...

Deep learning has been at the root of significant progress in many application areas, such as computer perception and natural language processing. But almost all of these systems currently use supervised learning with human-curated labels. The challenge of the next several years is to let machines learn from raw, unlabeled data, such as images, videos, and text. Intelligent systems today do not possess "common sense", which humans and animals acquire by observing the world, acting in it, and understanding the physical constraints of it. I will argue that allowing a machine to learn predictive models of the world is key to significant progress in artificial intelligence, and a necessary component of model-based planning and reinforcement learning. The main technical difficulty is that the world is only partially predictable. A general formulation of unsupervised learning that deals with partial predictability will be presented. The formulation connects many well-known approaches to unsupervised learning, as well as new and exciting ones such as adversarial training.

Date: August 2017

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Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Dara Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer Engineering Department.

He received the Electrical Engineer Diploma from Ecole Superieure d'Ingenieurs en Electrotechnique et Electronique (ESIEE), Paris in 1983, and a Ph.D. in Computer Science from Universite Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories in Holmdel, NJ in 1988. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 he directed NYU's initiative in data science and became the founding director of the NYU Center for Data Science. He was named Director of AI Research at Facebook in late 2013 and retains a part-time position on the NYU faculty.

His current interests include AI, machine learning, computer perception, mobile robotics, and computational neuroscience. He has published over 180 technical papers and book chapters on these topics as well as on neural networks, handwriting recognition, image processing and compression, and on dedicated circuits and architectures for computer perception. The character recognition technology he developed at Bell Labs is used by several banks around the world to read checks and was reading between 10 and 20% of all the checks in the US in the early 2000s. His image compression technology, called DjVu, is used by hundreds of web sites and publishers and millions of users to access scanned documents on the Web. Since the late 80's he has been working on deep learning methods, particularly the convolutional network model, which is the basis of many products and services deployed by companies such as Facebook, Google, Microsoft, Baidu, IBM, NEC, AT&T and others for image and video understanding, document recognition, human-computer interaction, and speech recognition.

LeCun has been on the editorial board of IJCV, IEEE PAMI, and IEEE Trans. Neural Networks, was program chair of CVPR'06 and is chair of ICLR 2013 and 2014. He is on the science advisory board of Institute for Pure and Applied Mathematics and has advised many large and small companies about machine learning technology, including several startups he co-founded. He is the lead faculty at NYU for the Moore-Sloan Data Science Environment, a $36M initiative in collaboration with UC Berkeley and University of Washington to develop data-driven methods in the sciences. He is the recipient of the 2014 IEEE Neural Network Pioneer Award.

Wednesday, October 4, 2017

Bitcoins, ICOs and Blockchain Tech Are Not a Fad! | James Altucher

Entrepreneur, investor and host of The James Altucher Show sat with Investor Town Hall while at the Crowd Invest Summit in the LA Convention Center discussing the hot topics of the year - Blockchain Technology and Cryptocurrencies.
James Altucher is an American hedge fund manager, entrepreneur, best-selling author, venture capitalist, and podcaster. He has founded or co-founded more than[clarification needed] 20 companies, including Reset Inc. and StockPickr, and says he failed at 17 of them. He has published eleven books, and he is a frequent contributor to publications, including The Financial Times, TheStreet.com, TechCrunch, Seeking Alpha, Thought Catalog, and The Huffington Post

Yann LeCun: Career Advice for Learners in Artificial Intelligence AI and...

Facebook AI Research & New York University yann.lecun.com Yann LeCun is Director of AI Research at Facebook and Silver Professor at New York University, affiliated with the Courant Institute, the Center for Neural Science and the Center for Data Science, for which he served as founding director until 2014. He received an EE Diploma from ESIEE (Paris) in 1983, a PhD in Computer Science from Université Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU in 2003 after a short tenure at the NEC Research Institute. In late 2013, LeCun became Director of AI Research at Facebook, while remaining on the NYU Faculty part-time. He was visiting professor at Collège de France in 2016. His research interests include machine learning and artificial intelligence, with applications to computer vision, natural language understanding, robotics, and computational neuroscience. He is best known for his work in deep learning and the invention of the convolutional network method which is widely used for image, video and speech recognition. He is the recipient of the 2014 IEEE Neural Network Pioneer Award, the 2015 IEEE Pattern Analysis and Machine Intelligence Distinguished Researcher Award, the 2016 Lovie Award for Lifetime Achievement, and a honorary doctorate from IPN, Mexico.

Tony Seba: Disruption in Energy and Transportation with AI and Technologies

Stanford Instructor Tony Seba explained how major global industries such as energy and transportation will undergo a complete "disruption" by the year 2030 in an address to guests of the Pacific Council and the Korea Foundation in downtown Los Angeles on March 31, 2017.

Yann LeCun: A Path to Artificial Intelligence (AI) | Beneficial AI 2017

Yann LeCun gives an overview of AI and outlines a path toward more general and complete AI at the January 2017 Asilomar conference organized by the Future of Life Institute.

The Beneficial AI 2017 Conference:
They brought together an amazing group of AI researchers from academia and industry and thought leaders in economics, law, ethics, and philosophy for five days dedicated to beneficial AI. They hosted a two-day workshop for their grant recipients and followed that with a 2.5-day conference, in which people from various AI-related fields hashed out opportunities and challenges related to the future of AI and steps that we can take to ensure that the technology is beneficial for all of us!

Kevin Kelly: The Technium, The Superorganism of Technology

The technium is a superorganism of technology. It has its own force that it exerts. That force is part cultural (influenced by and influencing of humans), but it's also partly non-human, partly indigenous to the physics of technology itself.
Kevin Kelly is the founding executive editor of Wired magazine, and a former editor/publisher of the Whole Earth Review. He has also been a writer, photographer, conservationist, and student of Asian and digital culture.

Tuesday, October 3, 2017

Yann LeCun: Predictive Learning, The Next Frontier in A.I. |Nokia Bell Labs

Yann LeCun, director of Artificial Intelligence Research at Facebook and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University and former Bell Labs researcher presented at the Shannon Luminary Lecture series. Building from the Claude Shannon Centennial Conference lectures this series is comprised of speakers who are luminaries in a wide diversity of fields and will share their perspective on the most important technologies, science, engineering, mathematics – and even more aesthetic matters – that will transform human existence in the next decades.

LeCun spoke about his research in his presentation "Predictive Learning: The Next Frontier in A.I.". His work in convolutional neural networks has revolutionized the fields of image analysis, speech recognition, and language translation. As a recognized visionary, LeCun's research promises to bring great advances in artificial intelligence and the augmentation of human ability.