SpaceX's Friday-morning mission to the International Space Station (ISS) will include a new crew member quite unlike any other. The name of the new addition is CIMON (pronounced Simon) and it's being sent to act as a mobile autonomous assistance system. Think HAL 9000 in 2001: A Space Odyssey, Moon's GERTY, and Holly in the BBC's Red Dwarf. Developed by Airbus and Germany's DLR space agency, and powered by IBM's Watson supercomputer, CIMON will be the first form of artificial intelligence (A.I.) to arrive on the space station, where it will aid the astronauts with their research work and presumably become their buddy, as well. CIMON, which stands for Crew Interactive MObile companioN, is about the size of a volleyball and has a display built in. It can see, hear, talk, and comprehend, and its A.I. smarts mean that the more it interacts with crew members, the more abilities it will develop.

WASHINGTON – Hey, did my congressman really say that? Is that really President Donald Trump on that video, or am I being duped? New technology on the internet lets anyone make videos of real people appearing to say things they've never said. Republicans and Democrats predict this high-tech way of putting words in someone's mouth will become the latest weapon in disinformation wars against the United States and other Western democracies. This technology uses facial mapping and artificial intelligence to produce videos that appear so genuine it's hard to spot the phonies.

Hey, did my congressman really say that? Is that really President Donald Trump on that video, or am I being duped? New technology on the internet lets anyone make videos of real people appearing to say things they've never said. Republicans and Democrats predict this high-tech way of putting words in someone's mouth will become the latest weapon in disinformation wars against the United States and other Western democracies. This technology uses facial mapping and artificial intelligence to produce videos that appear so genuine it's hard to spot the phonies.

Hey, did my congressman really say that? Is that really President Donald Trump on that video, or am I being duped? New technology on the internet lets anyone make videos of real people appearing to say things they've never said. Republicans and Democrats predict this high-tech way of putting words in someone's mouth will become the latest weapon in disinformation wars against the United States and other Western democracies. This technology uses facial mapping and artificial intelligence to produce videos that appear so genuine it's hard to spot the phonies.

Rubio noted that in 2009, the U.S. Embassy in Moscow complained to the Russian Foreign Ministry about a fake sex video it said was made to damage the reputation of a U.S. diplomat. The video showed the married diplomat, who was a liaison to Russian religious and human rights groups, making telephone calls on a dark street. The video then showed the diplomat in his hotel room, scenes that apparently were shot with a hidden camera. Later, the video appeared to show a man and a woman having sex in the same room with the lights off, although it was not at all clear that the man was the diplomat.

Robots are set to carry out dementia care within 20 years, NHS officials have announced. They are planning a major expansion of artificial intelligence across the health service for routine operations and treatment. The technology will also be used to'nudge' patients towards having healthier lifestyles, particularly if they have diabetes or heart conditions. Today, Jeremy Hunt will announce a £215 million investment towards what has been termed the'next generation of innovative treatments.' The Health Secretary wants academics and technology firms to come up with new ideas to improve surgery, treatment and long-term care. Health Secretary Jeremy Hunt (pictured) will announce a £215 million investment towards what has been termed the'next generation of innovative treatments' His announcement coincides with a review commissioned by the Department of Health which calls for a revolution in artificial intelligence and technology.

I've written much about the future of sales and how technology is changing everything. Here is what I regard as the facts. Source data and research reports are referenced at the end of the article along with an essential book for every leader to read. Right now, machines already do'games of intellect' better than humans: Computers have already defeated the very best people on the planet at Jeopardy and GO! Chess was conquered by the machines 20 years ago when IBM's Deep Blue computer won back in 1997. Computers are already better at share trading (faster and consistently pick more winning stocks).

Recently a strong poker-playing algorithm called DeepStack was published, which is able to find an approximate Nash equilibrium during gameplay by using heuristic values of future states predicted by deep neural networks. This paper analyzes new ways of encoding the inputs and outputs of DeepStack's deep counterfactual value networks based on traditional abstraction techniques, as well as an unabstracted encoding, which was able to increase the network's accuracy.

We revisit the classical problem of exact inference on probabilistic graphical models (PGMs). Our algorithm is based on recent \emph{worst-case optimal database join} algorithms, which can be asymptotically faster than traditional data processing methods. We present the first empirical evaluation of these algorithms via JoinInfer -- a new exact inference engine. We empirically explore the properties of the data for which our engine can be expected to outperform traditional inference engines, refining current theoretical notions. Further, JoinInfer outperforms existing state-of-the-art inference engines (ACE, IJGP and libDAI) on some standard benchmark datasets by up to a factor of 630x. Finally, we propose a promising data-driven heuristic that extends JoinInfer to automatically tailor its parameters and/or switch to the traditional inference algorithms.

The lifted dynamic junction tree algorithm (LDJT) efficiently answers filtering and prediction queries for probabilistic relational temporal models by building and then reusing a first-order cluster representation of a knowledge base for multiple queries and time steps. We extend LDJT to (i) solve the smoothing inference problem to answer hindsight queries by introducing an efficient backward pass and (ii) discuss different options to instantiate a first-order cluster representation during a backward pass. Further, our relational forward backward algorithm makes hindsight queries to the very beginning feasible. LDJT answers multiple temporal queries faster than the static lifted junction tree algorithm on an unrolled model, which performs smoothing during message passing.