Think that AI will help put a stop to fake news? The US military isn’t so sure.
Think that AI will help put a stop to fake news? The US military isn’t so sure.
Interest in the phenomenon of “deepfakes” has died down a little in recent months, presumably as the public comes to terms with what seems like an inevitability in 2018 — that people can and will use AI to create super-realistic fake videos and images.
Why it matters: Companies failing to quickly embrace AI to improve growth risk falling further and further behind, paring their ability to attract top talent and leading to more concentration of market power within a few "superstar" firms.
It's a Saturday morning in February, and Chloe, a curious 3-year-old in a striped shirt and leggings, is exploring the possibilities of a new toy.
On a recent work trip, I found myself in a swanky-but-still-hip office of a private tech firm.
Every day brings considerable AI news, from breakthrough capabilities to dire warnings.
Helsinki University in Finland has launched a course on artificial intelligence -- one that's completely free and open to everyone around the world.
IBM Research today unveiled its Crypto Anchor Verifier, an AI-powered counterfeit detector that verifies an item’s authenticity using your phone’s camera and blockchain technology. How it works: You pull out your phone, open an app, and take a pic of, for example, a diamond.
AI, blockchain, and just an overall rise in technologies across the planet are changing the way traditional industries are doing business. The wide world of auto insurance is no exception, with disruptive technology from insurtech propelling the industry forward.
In 1945, as American physicists were preparing to test the atomic bomb, it occurred to someone to ask if such a test could set the atmosphere on fire. This was a legitimate concern. Nitrogen, which makes up most of the atmosphere, is not energetically stable.
PDF: We made a fancy PDF of this post for printing and offline viewing. Buy it here. (Or see a preview.) Note: The reason this post took three weeks to finish is that as I dug into research on Artificial Intelligence, I could not believe what I was reading.
This summer, Elon Musk spoke to the National Governors Association and told them that “AI is a fundamental risk to the existence of human civilization.” Doomsayers have been issuing similar warnings for some time, but never before have they commanded so much visibility.
Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike.
A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011.
We are surrounded by hysteria about the future of Artificial Intelligence and Robotics. There is hysteria about how powerful they will become how quickly, and there is hysteria about what they will do to jobs.
IMAGINE the perfect environment for developing artificial intelligence (AI). The ingredients would include masses of processing power, lots of computer-science boffins, a torrent of capital—and abundant data with which to train machines to recognise and respond to patterns.
In a few seconds, I want you to stop reading this article, and follow the instructions below. Machine learning and artificial intelligence (ML and AI) have seized Tech mindshare in a way few topics have in recent memory.
Azeem Azhar is a strategist, product entrepreneur, and analyst living in London. He is the curator of the weekly newsletter Exponential View, from which the following is adapted. You can (and should!) sign up here. This is the first year I am presenting predictions for the coming year.
HOW HAS ARTIFICIAL intelligence, associated with hubris and disappointment since its earliest days, suddenly become the hottest field in technology? The term was coined in a research proposal written in 1956 which suggested that significant progress could be made in getting machines to “solve the
TWO letters can add up to a lot of money. No area of technology is hotter than AI, or artificial intelligence. Venture-capital investment in AI in the first nine months of 2017 totalled $7.6bn, according to PitchBook, a data provider; that compares with full-year figures of $5.4bn in 2016.
THERE IS SOMETHING familiar about fears that new machines will take everyone’s jobs, benefiting only a select few and upending society. Such concerns sparked furious arguments two centuries ago as industrialisation took hold in Britain.
The world’s largest technology companies hold the keys to some of the largest databases on our planet. Much like goods and coins before it, data is becoming an important currency for the modern world. The data’s value is rooted in its applications to artificial intelligence.
Welcome to robot nursery school," Pieter Abbeel says as he opens the door to the Robot Learning Lab on the seventh floor of a sleek new building on the northern edge of the UC-Berkeley campus.
COMMANDING the plot lines of Hollywood films, covers of magazines and reams of newsprint, the contest between artificial intelligence (AI) and mankind draws much attention. Doomsayers warn that AI could eradicate jobs, break laws and start wars. But such predictions concern the distant future.
DeepMind’s stunning victories over Go legend Lee Se-dol have stoked excitement over artificial intelligence’s potential more than any event in recent memory. But the Google subsidiary’s AlphaGo program is far from its only project — it’s not even the main one.
I don’t care what your job is. If you dig ditches, a robot will dig them better. If you’re a magazine writer, a robot will write your articles better.
MANY TECH FIRMS’ offices boast luxurious perks such as nap pods, massages and soda fountains that offer employees a choice of exotically flavoured sparkling water.
To you and I, that passage looks like nonsense.
On Tuesday, the White House released a chilling report on AI and the economy. It began by positing that “it is to be expected that machines will continue to reach and exceed human performance on more and more tasks,” and it warned of massive job losses.
LIE DETECTORS ARE not widely used in business, but Ping An, a Chinese insurance company, thinks it can spot dishonesty. The company lets customers apply for loans through its app.
A new report authored by over two-dozen experts on the implications of emerging technologies is sounding the alarm bells on the ways artificial intelligence could enable new forms of cybercrime, physical attacks, and political disruption over the next five to ten years.
With his company DeepMind, Londoner Demis Hassabis is leading Google’s project to build software more powerful than the human brain. But what will this mean for the future of humankind?
This is the first of a multi-part series explaining the fundamentals of deep learning by long-time tech journalist Michael Copeland. Artificial intelligence is the future. Artificial intelligence is science fiction. Artificial intelligence is already part of our everyday lives.
This week, the White House published its report on the future of artificial intelligence (AI) — a product of four workshops held between May and July 2016 in Seattle, Pittsburgh, Washington DC and New York City (see go.nature.com/2dx8rv6).
Elon Musk, Stuart Russell, Ray Kurzweil, Demis Hassabis, Sam Harris, Nick Bostrom, David Chalmers, Bart Selman, and Jaan Tallinn discuss with Max Tegmark (moderator) what likely outcomes might be if we succeed in building human-level AGI, and also what we would like to happen.The Beneficial AI 2017
Yuval Noah Harari’s first book, Sapiens, was an international sensation. The Israeli historian’s mind-bending tour through the triumph of Homo sapiens is a favorite of, among others, Bill Gates, Mark Zuckerberg, and Barack Obama.
The most powerful approach in AI, deep learning, is gaining a new capability: a sense of uncertainty. Researchers at Uber and Google are working on modifications to the two most popular deep-learning frameworks that will enable them to handle probability.
On the first Sunday afternoon of 2015, Elon Musk took to the stage at a closed-door conference at a Puerto Rican resort to discuss an intelligence explosion.
SCIENCE fiction is littered with examples of intelligent computers, from HAL 9000 in “2001: A Space Odyssey” to Eddie in “The Hitchhiker’s Guide to the Galaxy”. One thing such fictional machines have in common is a tendency to go wrong, to the detriment of the characters in the story.
There’s a well-known thought experiment in the world of artificial intelligence that poses a simple, but potentially very scary, question: what if we asked a super-intelligent AI to make paperclips?
It can, and in fact it does.
We are surrounded by hysteria about the future of artificial intelligence and robotics—hysteria about how powerful they will become, how quickly, and what they will do to jobs. I recently saw a story in MarketWatch that said robots will take half of today’s jobs in 10 to 20 years.
Part 1: Why Machine Learning Matters. The big picture of artificial intelligence and machine learning — past, present, and future. Part 2.1: Supervised Learning. Learning with an answer key. Introducing linear regression, loss functions, overfitting, and gradient descent.
DELIVERING 25 PACKAGES by lorry or van might seem straightforward enough, but it is devilishly complex. The number of possible routes adds up to around 15 septillion (trillion trillion), according to Goldman Sachs, an investment bank.
The computing industry progresses in two mostly independent cycles: financial and product cycles. There has been a lot of handwringing lately about where we are in the financial cycle. Financial markets get a lot of attention. They tend to fluctuate unpredictably and sometimes wildly.
It was hailed as the most significant test of machine intelligence since Deep Blue defeated Garry Kasparov in chess nearly 20 years ago.
Between Hollywood and your dusty stack of sci-fi novels, you’ve been given many outlandish representations of the AI of the future. But AI is already here. It’s all around us — just in humbler forms. Intelligent behavior in an autonomous agent — THIS is AI.
Whenever an artificial intelligence (AI) does something well, we’re simultaneously impressed as we are worried. AlphaGO is a great example of this: a machine learning system that is better than any human at one of the world’s most complex games.
How clever is artificial intelligence, really? And how fast is it progressing? These are questions that keep politicians, economists, and AI researchers up at night.
You’ve probably heard the news: AI is going to take your job. Wait, no: It’s going to create a new job for you. AI is going to kill us all! Wait, no it’s not. AI is already totally smarter than us at, like, all the smart things. But that probably doesn’t matter? Neural networks.
Goldman Sachs has been particularly active in the last 2 years, backing 4 unique companies applying AI in financial technology. Deals and dollars to startups using AI algorithms reached record levels in 2016.
The market for artificial intelligence (AI) technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises.
Imagine that, in 20 or 30 years, a company creates the first artificially intelligent humanoid robot. Let’s call her “Ava.” She looks like a person, talks like a person, interacts like a person. If you were to meet Ava, you could relate to her even though you know she’s a robot.
We usually think of surveillance cameras as digital eyes, watching over us or watching out for us, depending on your view. But really, they’re more like portholes: useful only when someone is looking through them.
If you’ve ever gotten product recommendations on Amazon, you’ve seen Danny Lange’s handiwork. The same goes for Uber’s AI that books you a ride.
After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever. The pace of advancement in AI is "actually speeding up," said Jeff Dean, a senior fellow at Google.
In which I discuss the trouble with trusting machines to take our jobs, curate our news feeds, drive our school buses, teach our children, and lots of boring stuff too difficult to bother doing ourselves. Oh, and quotes. Lots of quotes. Houston, we have a problem.
Today we released our second annual research report on the state of artificial intelligence.
Companies new to the space can learn a great deal from early adopters who have invested billions into AI and are now beginning to reap a range of benefits.
Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey.
Who is the man behind some of the most innovative companies in the world, including Tesla, SpaceX, Planet, D-Wave, and Synthetic Genomics? His name is Steve Jurvetson, and if you’re a tech enthusiast, then you’re intimately familiar with his daring venture capital work.
Biotechnology and the rise of AI may split humankind into a small class of ‘superhumans’ and a huge underclass of ‘useless’ people. Once the masses lose their economic and political power, inequality levels could spiral alarmingly Inequality goes back to the Stone Age.
He is an essay version of class notes from Class 17 of CS183: Startup. Errors and omissions are mine. Credit for good stuff goes to them and Peter. I have tried to be accurate. But note that this is not a transcript of the conversation.
Remember AlphaGo, the first artificial intelligence to defeat a grandmaster at Go? Well, the program just got a major upgrade, and it can now teach itself how to dominate the game without any human intervention.
If you’re like me, you’re fascinated with AI. Maybe you’d love to dig deeper and get an image recognition program running in TensorFlow or Theano? Perhaps you’re a kick-ass developer or systems architect and you know computers incredibly well but there’s just one little problem:
Speaking to attendees at a deep learning conference in London last month, there was one particularly noteworthy recurring theme: humility, or at least, the need for it.
With every paradigm shift in technology, waves of innovation follow as companies improve and then reimagine processes. Today we are in the early stages of the global artificial intelligence (AI) revolution.
Artificial Intelligence and the fourth industrial revolution has made some considerable progress over the last couple of years. Most of this current progress that is usable has been developed for industry and business purposes, as you’ll see in coming posts.
Jeff Heepke knows where to plant corn on his 4,500-acre farm in Illinois because of artificial intelligence (AI). He uses a smartphone app called Climate Basic, which divides Heepke’s farmland (and, in fact, the entire continental U.S.) into plots that are 10 meters square.
IN A former leatherworks just off Euston Road in London, a hopeful firm is starting up. BenevolentAI’s main room is large and open-plan. In it, scientists and coders sit busily on benches, plying their various trades. The firm’s star, though, has a private, temperature-controlled office.
Peter Norvig is Director of Research for Google, and an expert in both artificial intelligence (AI) and online search. Prior to his work at Google, he worked at NASA, becoming the organization’s senior computer scientist. He is a true AI Trailblazer, having literally written the textbook for AI.
Past is prologue1. In one interpretation it is that the past has predetermined the sequence which is about to unfold–and so I believe that how we have gotten to where we are in Artificial Intelligence will determine the directions we take next–so it is worth studying that past.
The concept of inhuman intelligence goes back to the deep prehistory of mankind. At first the province of gods, demons, and spirits, it transferred seamlessly into the interlinked worlds of magic and technology.
Historically, when new technologies become easier to use, they transform industries. That’s what’s happening with artificial intelligence and big data; as the barriers to implementation disappear (cost, computing power, etc.
China intends to become the world’s artificial intelligence leader in 2030, according to the manifesto it just released describing plans to create an industry of $150 billion and an environment that has AI “everywhere.
It seems like everyone wants to invest in artificial intelligence (AI). And it’s not just the tech giants: USAA is using AI to protect its users from identity theft and Under Armour has connected its health app, MyFitnessPal, to IBM Watson so users can get a more thorough read of their health.