How machine learning and artificially generated images might replace photography as we know it.
When hearing the words ‘AI’, ‘Machine Learning’ or ‘bot’ most people tend to visualize a walking, talking android robot which looks like something out of a Sci-Fi movie and immediately assume about a time far away in the future.
Last year, I participated in a discussion of The Human Use of Human Beings, Norbert Weiner’s groundbreaking book on cybernetics theory. Out of that grew what I now consider a manifesto against the growing singularity movement, which posits that artificial intelligence, or AI, will supersede and eventually displace us humans.
The notion of singularity – which includes the idea that AI will supercede humans with its exponential growth, making everything we humans have done and will do insignificant – is a religion created mostly by people who have designed and successfully deployed computation to solve problems previously considered impossibly complex for machines.
ChinAI Jeff Ding’s weekly newsletter reporting on the Chinese AI scene; on the occasion of the newsletter’s first anniversary, Ding has posted a roundup of things about the Chinese AI scene that the rest of the world doesn’t know about, or harbors incorrect beliefs about.
Today, the High-Level Expert Group on AI presents their ethics guidelines for trustworthy artificial intelligence. This follows the publication of the guidelines’ first draft in December 2018 on which more than 500 comments were received through an open consultation.
Artificial intelligence has been around for decades. Is it smart enough now to predict Alzheimer’s? (Brian Monroe/The Washington Post)
What makes artificial intelligence intelligent? Is it able to learn from errors or recognize, say, the letters of the alphabet in a set of random shapes like a human can?
These are some of the questions developers of AI ask. What began as sluggish programs on hulking machines has taken the form of code that anyone in a particular field could test out and manipulate to suit their needs.
In a startling demonstration, the machine drew on experimentation, data, and observation of humans to learn how simple implements could help it achieve a task.
Learning to use tools played a crucial role in the evolution of human intelligence. It may yet prove vital to the emergence of smarter, more capable robots, too.
New research shows that robots can figure out at least the rudiments of tool use, through a combination of experimenting and observing people.
A robot and a dancer perform during the opening ceremony of an industry fair in Hanover, Germany on 31 March 2019.
The risk that humanity faces comes not from malevolent machines but from incompetent programmers, writes Martyn Thomas.
The long read (28 March) on the threat from artificial intelligence misses the point. In a paper written in 1951, Alan Turing demolished all the arguments against AI one day surpassing human intelligence, but there is no sign that that “singularity” is on the horizon. The imminent threat is that we’ve built a digital society on software foundations that are too vulnerable to failures and cyber-attacks, as a recent report from the Huawei Cyber Security Evaluation Centre oversight board powerfully illustrated. The risk that humanity faces comes not from malevolent machines but from incompetent programmers who leave their customers vulnerable to cyber-attacks and other failures.
If we survive long enough to see truly intelligent machines, then there is no known barrier to them developing consciousness. But how could we tell?
What will machine learning look like 15-20 years from now? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Machine Learning is a very rapidly moving field, so it’s hard to make predictions about the state of the art 6 months from now, let alone 15 – 20 years. I can however, offer a series of educated guesses based on what I see happening right now.
We are still far away from AGI. Current generation machine learning systems are still very far away from something that could legitimately be called artificial “intelligence”. The systems we have right now are phenomenal at pattern recognition from lots of data (even reinforcement learning systems are mostly about memorizing and recognizing patterns that worked well during training). This is certainly a necessary step, but it is very far away from an intelligent system. In analogy to human cognition, what we have now is analogous to the subconscious processes that allow split second activation of your sympathetic nervous system when your peripheral vision detects a predator approaching or former significant other turning around a corner – in other words, pattern-based, semi-automatic decisions that our brain does “in hardware”. We don’t currently have anything I can see that would resemble intentional thought and I’m not convinced we’ll get to it from current generation systems.
Will robots become self-aware? Will they have rights? Will they be in charge? Here are five scenarios from our future dominated by AI.
SMITHSONIAN MAGAZINE | April 2018
In June of 1956, A few dozen scientists and mathematicians from all around the country gathered for a meeting on the campus of Dartmouth College. Most of them settled into the red-bricked Hanover Inn, then strolled through the famously beautiful campus to the top floor of the math department, where groups of white-shirted men were already engaged in discussions of a “strange new discipline”—so new, in fact, that it didn’t even have a name. “People didn’t agree on what it was, how to do it or even what to call it,” Grace Solomonoff, the widow of one of the scientists, recalled later. The talks—on everything from cybernetics to logic theory—went on for weeks, in an atmosphere of growing excitement.
What the scientists were talking about in their sylvan hideaway was how to build a machine that could think.
Can AI be a fair judge in court? Estonia thinks so.
GOVERNMENT USUALLY ISN’T the place to look for innovation in IT or new technologies like artificial intelligence. But Ott Velsberg might change your mind. As Estonia’s chief data officer, the 28-year-old graduate student is overseeing the tiny Baltic nation’s push to insert artificial intelligence and machine learning into services provided to its 1.3 million citizens.
“We want the government to be as lean as possible,” says the wiry, bespectacled Velsberg, an Estonian who is writing his PhD thesis at Sweden’s Umeå University on using the Internet of Things and sensor data in government services. Estonia’s government hired Velsberg last August to run a new project to introduce AI into various ministries to streamline services offered to residents.
The spectre of superintelligent machines doing us harm is not just science fiction, technologists say – so how can we ensure AI remains ‘friendly’ to its makers?
It began three and a half billion years ago in a pool of muck, when a molecule made a copy of itself and so became the ultimate ancestor of all earthly life. It began four million years ago, when brain volumes began climbing rapidly in the hominid line.
Fifty thousand years ago with the rise of Homo sapiens sapiens.
Ten thousand years ago with the invention of civilization.
Five hundred years ago with the invention of the printing press.
Fifty years ago with the invention of the computer.