stephen wolfram
Stephen Wolfram on the future of programming and why we live in a computational universe
This article originally appeared on TechRepublic. When it came to figuring out which computer scientist should help linguists decipher inscrutable alien texts, it was Stephen Wolfram who got the call. Sure, these extraterrestrials may only have existed in the sci-fi movie Arrival, but if ET ever does drop out of orbit, Wolfram might well still be on the short list of people to contact. Download this article as a PDF (free registration required). The British-born computer scientist's life is littered with exceptional achievements -- completing a PhD in theoretical physics at Caltech at age 20, winning a MacArthur Genius Grant at 21, and creating the technical computing platform Mathematica (which is used by millions of mathematicians, scientists, and engineers worldwide), plus the Wolfram Language, and the Wolfram Alpha knowledge engine.
Possible Minds: 25 Ways of Looking at AI
John Brockman: On the Promise and Peril of AI โข Seth Lloyd: Wrong, but More Relevant Than Ever โข Judea Pearl: The Limitations of Opaque Learning Machines โข Stuart Russell: The Purpose Put Into the Machine โข George Dyson: The Third Law โข Daniel C. Dennett: What Can We Do? โข Rodney Brooks: The Inhuman Mess Our Machines Have Gotten Us Into โข Frank Wilczek: The Unity of Intelligence โข Max Tegmark: Let's Aspire to More Than Making Ourselves Obsolete โข Jaan Tallinn: Dissident Messages โข Steven Pinker: Tech Prophecy and the Underappreciated Causal Power of Ideas โข David Deutsch: Beyond Reward and Punishment โข Tom Griffiths: The Artificial Use of Human Beings โข Anca Dragan: Putting the Human into the AI Equation โข Chris Anderson: Gradient Descent โข David Kaiser: "Information" for Wiener, for Shannon, and for Us โข Neil Gershenfeld: Scaling โข W. Daniel Hillis: The First Machine Intelligences โข Venki Ramakrishnan: Will Computers Become Our Overlords?
AI and the Future of Money: Stephen Wolfram - Breaking Banks
Today, we are honored to be joined by Stephen Wolfram, a legend in Silicon Valley, and a genius in the computing space. We are talking to him about AI, and all the amazing things that are happening in Artificial Intelligence and Machine Learning, and how that will affect the future of money, finance, and the ethical discussions we need to be having to plan for it. Stephen Wolfram is the creator of Mathematica, Wolfram Alpha and the Wolfram Language; the author of A New Kind of Science; and the founder and CEO of Wolfram Research. Over the course of nearly four decades, he has been a pioneer in the development and application of computational thinking--and has been responsible for many discoveries, inventions and innovations in science, technology and business. Born in London in 1959, Wolfram was educated at Eton, Oxford and Caltech.
Is there a future for humans?
Lurking beneath the fear of artificial intelligence and automation threatening people's jobs lies a deeper, far more profound threat. Do artificial intelligence and automation imperil humanity itself? Those predicting a dystopian future include Elon Musk, Bill Gates, Stephen Hawking, and many others. For some of them, it's only a matter of time before the prophecy of Yuval Noah Harari's great book, Homo Deus: A Brief History of Tomorrow, comes to pass. The bleak vision: a world where a small group of humans control machines, which in turn control the rest of humanity.
A DARPA Perspective on Artificial Intelligence - YouTube
'BREAKTHROUGH IN QUANTUM COMPUTERS' says Google: Biometrics, Brain-Machine Interface & 2030 Agenda - Duration: 10:28. Artificial Intelligence, Made in Canada - Duration: 28:31. Stephen Wolfram on How to Tell AIs What to Do (and What to Tell Them) - Duration: 51:35. 'BREAKTHROUGH IN QUANTUM COMPUTERS' says Google: Biometrics, Brain-Machine Interface & 2030 Agenda - Duration: 10:28. 'BREAKTHROUGH IN QUANTUM COMPUTERS' says Google: Biometrics, Brain-Machine Interface & 2030 Agenda - Duration: 10:28.
Stephen Wolfram on the Singularity Xconomy
Last month, I posted a story about which Boston-area innovators subscribe to the belief that there will be a technological "singularity," as popularized by Ray Kurzweil and Vernor Vinge. The idea is that a superhuman artificial intelligence will emerge in a few decades, thereby creating an event horizon beyond which humans cannot fathom--and leading to all sorts of possibilities, such as the explicit merging of humans and computers. One local I ended up reaching out to is Stephen Wolfram, the computational guru, CEO of Wolfram Research, and creator of Mathematica, A New Kind of Science, and Wolfram Alpha. I predicted that his answer would be, shall we say, complicated. Here's what Wolfram wrote back (I would say he's a non-believer, but you be the judge; as usual he brings up a different way of looking at things): There will be more automation, and the rate of new automation will increase.
The Grand Frontier of Artificial Intelligence
In 1950, Alan Turing invented a test for determining a machine's ability to exhibit intelligent behavior. At the time, some predicted that so-called "Strong A.I.," that is, artificial intelligence that matches or exceeds human intelligence, could be achieved in a few decades. Over sixty years later, every machine that has been tasked with simulating human intelligence has failed the so-called Turing Test. And yet, scientists have become both impressed and alarmed by the tremendous leaps forward in A.I. capabilities in recent years. A.I. has been put into common use by financial institutions, and found promising applications in medical equipment, search technology, games and transportation systems.
How Stephen Wolfram's image-recognition tool performs against 5 alternatives
This week Stephen Wolfram, founder and chief executive of Wolfram Research, announced a new component of the Wolfram Language for programming called ImageIdentify. Wolfram also introduced a new website, dubbed The Wolfram Language Image Identification Project, that demonstrates the language's new capabilities. The new site lets you upload images and get inferences and definitions in response. You can provide feedback, which should help it become more accurate. You can hit buttons like "Great!," "Could be better," "Missed the point," and "What the heck?!" After you choose one, the service offers a few more guesses, and a text box where you can type in a tag.