If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Last spring, artificial intelligence research institute OpenAI said it had made software so good at generating text--including fake news articles--that it was too dangerous to release. That line in the sand was soon erased when two recent master's grads recreated the software and OpenAI released the original, saying awareness of the risks had grown and it hadn't seen evidence of misuse. Now the lab is back with a more powerful text generator and a new pitch: Pay us to put it to work in your business. Thursday, OpenAI launched a cloud service that a handful of companies are already using to improve search or provide feedback on answers to math problems. OpenAI was founded as a nonprofit in 2015 by Elon Musk and other Silicon Valley notables to ensure that future superhuman AI was a benign force.
A team of Uber AI researchers has developed a set of algorithms, Go-Explore, that reportedly beats any Atari 2600 game with "superhuman" scores, including ones where AI previously had trouble besting its organic rivals. The key is a system that takes care to remember promising states and returns to those states before it sets out exploring. Go-Explore saw improvement by "orders of magnitude" in some games. It was the first to beat every level in Montezuma's Revenge, and got a "near-perfect" Pitfall score -- both of these are particularly challenging for reinforcement learning systems like this. DeepMind's Agent57 reached a similar benchmark, according to the team's Jeff Clune, but through "entirely different methods."
Two 40-year old robots returned to the big screen this year: handy mechanic droid R2-D2 of the Star Wars Rebel Alliance and the terrifying Terminator. The latter has been used by many headline writers as a metaphor for the perceived risk that automation will destroy human jobs. But in 2020, we will see that the real future of work lies with R2-D2, whose strength is his ability to work alongside humans and enhance their performance. Next year will be the year of augmentation technology. Our fears about automation come down to three factors: machines will execute tasks more efficiently; machine learning will enable artificial intelligence (AI) to make complex decisions more effectively; and technology companies will sell software and algorithms to replace slow and distractible people with fast and focused machines.
Over the past year, this column has celebrated female technologists of all disciplines and from across a wide range of industries. Nearly all of them have mentioned the growing importance of Artificial Intelligence or machine learning to their work. Importantly, those same women all reinforced the need to engage more females in positions relative to AI – both to aid in its unbiased application and to optimize its use in business and society. So, as we look ahead to the trends and technologies that will likely dominate this next year and decade, it makes sense to begin by unpacking how AI might continue its march forward and the opportunities it will create for female entrepreneurs, engineers, marketers, and others. From email marketing to financial services, women tech leaders expect AI and machine learning to continue augmenting businesses' abilities to improve scale, efficiency, and – in some cases – impact.
The entire written works of mankind in all languages from the beginning of recorded history is around 50 petabytes. One petabyte is about 20 million four drawer filing cabinets filled with text. Google processes about 20 petabytes per day so in three days they would have processed everything we have written – ever. Meanwhile, data centres now annually consume as much energy as Sweden. By 2025 they'll consume a fifth of all of Earth's power.
Machine learning is everywhere, but is it actual intelligence? A computer scientist wrestles with the ethical questions demanded by the rise of AI. Published by Farrar, Straus and Giroux October 15th 2019. The idea is that unchecked robots will rise up and kill us all. But such martial bodings overlook a perhaps more threatening model: Aladdin.
The Fourth Amendment's prohibition against unreasonable searches and seizures could prevent law enforcement from applying increasingly sophisticated surveillance and predictive policing technology, including "superhuman" methods employing artificial intelligence, according to a professor at the University of California-Davis School of Law. In an essay published in the Ohio State Journal of Criminal Law, Elizabeth E. Joh argues that the recent U.S. Supreme Court decision in Carpenter v United States established a precedent for using the Fourth Amendment to limit the use of emerging technology, ranging from drones that help patrol borders to predictive-analytic software that can determine when and where the next crime will occur. In that landmark case, decided this summer, the Court ruled law enforcement cannot access citizens' cellphone location records without a search warrant. Although the decision focused on whether information held by "third parties" such as cellphone providers was subject to privacy protections guaranteed under the Constitution, Joh said it also touched on the changing "nature of policing" specifically the technologically enhanced means law enforcement can now exploit to gather information in the cyber era. In the Carpenter case, justices were asked to rule on whether FBI agents sidestepped their constitutional obligations to show "probable cause" for obtaining a search warrant to retrieve the locational data of a suspected serial robber's cellphone to prove he was near the scene of stores in the Detroit area where thefts had occurred.
Computer programs have shown superiority over humans in two-player games such as chess, Go, and heads-up, no-limit Texas hold'em poker. However, poker games usually include six players--a much trickier challenge for artificial intelligence than the two-player variant. Brown and Sandholm developed a program, dubbed Pluribus, that learned how to play six-player no-limit Texas hold'em by playing against five copies of itself (see the Perspective by Blair and Saffidine). When pitted against five elite professional poker players, or with five copies of Pluribus playing against one professional, the computer performed significantly better than humans over the course of 10,000 hands of poker. Science, this issue p. 885; see also p. 864
In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such benchmarks, including poker, have been limited to two-player games. However, poker in particular is traditionally played with more than two players. Multiplayer games present fundamental additional issues beyond those in two-player games, and multiplayer poker is a recognized AI milestone.
An article published by Hackernoon months ago was able to bring some sense to the hype about AI replacing all of our jobs. The article made the compelling argument that technological advances throughout the course of history have never resulted in massive unemployment rates. From the Industrial Revolution, to the Internet, technology actually has been responsible for creating new and better jobs for us. From steam machines liberating millions of children from working in the garment industry, to the service economy bringing about more humane jobs, innovation has been on the side of humanity all along. The article claims that the present AI revolution is not an exception.