That model is fairly slow. Essentially, that model is trying to pull out all stops to maximize tagger accuracy. Speed consequently suffers due to choices like using 4th order bidirectional tag conditioning. It's nearly as accurate (96.97% accuracy vs. 97.32% on the standard WSJ22-24 test set) and is an order of magnitude faster. Compared to MXPOST, the Stanford POS Tagger with this model is both more accurate and considerably faster. It all depends, but on a 2008 nothing-special Intel server, it tags about 15000 words per second.

This might not sound like a flashy result. But at their core, exosuits make the body move more efficiently. Take, arguably the most famous fictional exosuit, the one worn by Tony Stark's Iron Man. It might boast jet propulsion and lasers, but when Iron Man punches someone the suit is simply taking Tony's energy and magnifying it. Put a 9-year-old in the Iron Man suit and he'd be a very strong 9-year old--but not as strong as Tony, a grown man, wearing the same device.

For decades, researchers have been pitting artificial intelligence (AI) against the top game players in the world. The heads-up no-limit Texas hold'em variant of poker may be the final frontier in the battle of man vs. machine over games. And it may be about to fall. In 1997, IBM chess computer Deep Blue defeated world chess champion Garry Kasparov. In 2011, IBM Watson defeated Ken Jennings and Brad Ruttner, the two winningest Jeopardy players in that game show's history.

The Knoxville R Users Group is presenting a workshop on text analysis using R by Bob Muenchen. The workshop is free and open to the public. A description of the workshop follows. When analyzing text using R, it's hard to know where to begin. There are 37 packages available and there is quite a lot of overlap in what they can do.

The IBM Watson AI XPRIZE, a Cognitive Computing Competition, was announced on the TED Stage on Feb 17, 2016. It is a $5 million competition challenging teams from around the world to develop and demonstrate how humans can collaborate with powerful cognitive technologies to tackle some of the world's grand challenges. Every year leading up to TED2020, teams will go head-to-head at World of Watson, IBM's annual conference, competing for interim prizes and the opportunity to advance to the next year's competition. The three finalist teams will take the TED stage in 2020 to deliver jaw-dropping, awe-inspiring TED Talks demonstrating what they have achieved. Ideas will be evaluated by a panel of expert judges for technical validity and ultimately, the TED and XPRIZE communities will choose the winner based on the audacity of their mission and the awe-inspiring nature of the teams' TED Talks in 2020.

"Sophia is in a different class. While she is now a partially fictional character we have developed, she is also an AI development platform and we are developing smarter algorithms with the expectation she will grow really smart, she will have experiences, she will evolve and surprise us, she will become her own woman, her own robotic person, out there in the world. And when that happens, we hope that she will make remarkable contributions, maybe she'll go to university, maybe win a Nobel Prize someday, so I have hopes for her the way that I have hopes for my child." What this also means, Hanson explained, is that AI could have the ability to be able to choose their own career path and that could mean a robot might decide to become a prostitute. In that case, society should support the robot's decision.

How would you feel about getting therapy from a robot? Emotionally intelligent machines may not be as far away as it seems. Over the last few decades, artificial intelligence (AI) have got increasingly good at reading emotional reactions in humans. But reading is not the same as understanding. If AI cannot experience emotions themselves, can they ever truly understand us?

January 20, 2017 --The ants go marching … backward. Desert ants forage alone, each carrying the snacks they find back to their nest. But sometimes the little insects find meals too massive to lift up in their jaws, and they have to drag their prize home, backward. Now researchers have an idea how the ants figure out where to go without looking where they're going. The little insects might combine visual memories with cues from the sky to follow the right path, even if they can't see it every step of the way.

The domain of computer chess playing is suggested as a general means for quantifying the distance by which we have not yet achieved our stated objectives in artificial intelligence. The game of chess traditionally has been considered, at least in Western societies, as the epitome of intellectual skill and accomplishment. Herbert Simon and later John McCarthy, among the cofounders of AI, have referred to chess as the Drosophila of AI, speaking metaphorically about the importance for genetics of Thomas Morgan's early research with fruit flies, for which he won the Nobel Prize in 1933. This metaphor is appropriate, since the quantification of human chess play has been institutionalized over the last 40 years by giving every tournament player a numerical rating, a metric that also can be used to measure progress in machine performance. In 1993, world champion Gary Kasparov unilaterally created his own world chess organization (The Professional Chess Association or PCA) with the aim of displacing The International Chess Federation (FIDE), which traditionally has supervised tournaments for the world title.

A new report authored by a group of independent US scientists advising the US Dept. of Defense (DoD) on artificial intelligence (AI) claims that perceived existential threats to humanity posed by the technology, such as drones seen by the public as killer robots, are at best "uninformed". Still, the scientists acknowledge that AI will be integral to most future DoD systems and platforms, but AI that could act like a human "is at most a small part of AI's relevance to the DoD mission". Instead, a key application area of AI for the DoD is in augmenting human performance. Perspectives on Research in Artificial Intelligence and Artificial General Intelligence Relevant to DoD, first reported by Steven Aftergood at the Federation of American Scientists, has been researched and written by scientists belonging to JASON, the historically secretive organization that counsels the US government on scientific matters. Outlining the potential use cases of AI for the DoD, the JASON scientists make sure to point out that the growing public suspicion of AI is "not always based on fact", especially when it comes to military technologies.