We study the computational complexity of candidate control in elections with few voters, that is, we consider the parameterized complexity of candidate control in elections with respect to the number of voters as a parameter. We consider both the standard scenario of adding and deleting candidates, where one asks whether a given candidate can become a winner (or, in the destructive case, can be precluded from winning) by adding or deleting few candidates, as well as a combinatorial scenario where adding/deleting a candidate automatically means adding or deleting a whole group of candidates. Considering several fundamental voting rules, our results show that the parameterized complexity of candidate control, with the number of voters as the parameter, is much more varied than in the setting with many voters.

Last year, Swedbank in Sweden "hired" Nina, a dynamo of a company rep. Nina is adept at interacting with customers on the bank's website, answering their questions and routing them to the right human representative. She typically engages in some 45,000 conversations a month and successfully answers eight out of 10 inquiries. Not only can Nina understand and mimic human speech, she can also use data to make connections and recommendations. "Nina's brain for Swedbank is educated on all things Swedbank," says Robert Weideman, EVP and GM of the enterprise division at Nuance Communications, which created Nina.

In my last retail review, I explored how my learnings at NRF 2017 changed my view ofthe so-called omni-channel (Omni-channel may be science fiction, but a single source of truth matters). That leaves open the impact of predictive, "AI", and personalization tech on retail. CEO and Founder Alan O'Herlihy gave me a fast-paced rundown of how his company has become entrenched in five of the ten largest global retailers. How did they pull it off? Get ready for this one: instead of pursing the singularity, they focused their deep learning tech on a real world pain point: lost sales at the point of sale.

When science fiction author Isaac Asimov devised his Three Laws of Robotics he was thinking about androids. He envisioned a world where these human-like robots would act like servants and would need a set of programming rules to prevent them from causing harm. But in the 75 years since the publication of the first story to feature his ethical guidelines, there have been significant technological advancements. Sci-fi author Isaac Asimov devised his Three Laws of Robotics he was thinking about androids. The three'Laws of Robotics' were devised by sci-fi author Isaac Asimov in a short story he wrote in 1942, called'Runaround'.

We're heading for an explosive quantum computing revolution, or so we keep being told, but how soon will it come? Clearly, we are slowly learning more and more about how these sort of super-powerful systems can be realised – and the latest piece of research in the field concerns a fusion of traditional machine learning and quantum computing. Essentially, this is about trying to characterise quantum systems and verify the operation of quantum processors more effectively – and more cost-efficiently – using quantum simulators and powerful machine learning routines. In other words, it's about pushing forward faster with developing quantum computing and making it a reality, which to put it mildly, is a very tricky business with a lot of challenges to overcome. Scientists from the University of Bristol's Quantum Engineering Technology Labs (pictured above) are behind the work, and have successfully demonstrated a quantum-enhanced machine learning tech which can be used with a quantum processor to learn about the evolution of other quantum systems.

The Bank of England has paired up with artificial intelligence and blockchain specialists in a bid to keep up to date with the fast-growing financial technology sector. The central bank is testing an artificial intelligence system with Canadian startup MindBridge AI to allow it to spot abnormalities in financial transactions and "explore the benefit of machine learning technology for analysing the quality of regulatory data input." It has also partnered with San Francisco-based startup Ripple, which opened an office in London last year, to trial a blockchain-based technology that would make cross-border payments and the movement of currencies more immediate. Blockchain is the technology which underpins crypto-currencies like bitcoin. The Bank said that its aim with Ripple is to "show how this kind of synchronisation might lower settlement risk and improve the speed and efficiency of cross-border payments."

Scientists from the Oxford University along with Google's DeepMind have developed an artificial intelligence system that can lip-read better than humans. The system was trained by thousands of hours of BBC news programs, the media outlet said Friday. The system, called "Watch, Attend and Spell," can correctly lip-read 50 percent of silent speech correctly, while professional lip-readers only got 12 percent right, researchers found. Read: Google AI Firm DeepMind Develops'Streams' App to Help UK Doctors With Patients Some words that rhyme, such as like mat, bat and mat, have similar mouth shapes. However, it's context is what helps lip-reading, Joon Son Chung from the university's Department of Engineering said. The system learns "things that come together, in this case the mouth shapes and the characters and what the likely upcoming characters are," explained Joon.

A deal between Google's artificial intelligence firm DeepMind and the UK's NHS had serious "inadequacies", an academic paper has suggested. More than a million patient records were shared with DeepMind to build an app to alert doctors about patients at risk of acute kidney injury (AKI). The authors said that it was "inexcusable" patients were not told how their data would be used. Google's DeepMind said that the report contained "major errors". It told the BBC that it was commissioning its own analysis and rebuttal, which the authors said they welcomed. When the deal between London's Royal Free Hospital and DeepMind became public in February 2016, some three months after the data started to be collected, it caused controversy over the amount of patient information being shared and the lack of public consultation.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. The winner of the best video competition at HRI 2017 was this masterpiece from Professor Hiroshi Ishiguro (aka "The Man Who Made a Copy of Himself") and colleagues Dylan F. Glas, Malcolm Doering, Phoebe Liu, and Takayuki Kanda from the Advanced Telecommunications Research Institute in Kyoto: Stay tuned for the live concert tour, and read the paper at the link below. Dreamer's disembodied head can follow you without blinking.

Last month, when President Donald Trump toured a Boeing aircraft plant in North Charleston, South Carolina, he saw a familiar face in the crowd that greeted him: Patrick Caddell, a former Democratic political operative and pollster who, for forty-five years, has been prodding insurgent Presidential candidates to attack the Washington establishment. Caddell, who lives in Charleston, is perhaps best known for helping Jimmy Carter win the 1976 Presidential race. He is also remembered for having collaborated with his friend Warren Beatty on the 1998 satire "Bulworth." In that film, a kamikaze candidate abandons the usual talking points and excoriates both the major political parties and the media; voters love his unconventionality, and he becomes improbably popular. If the plot sounds familiar, there's a reason: in recent years, Caddell has offered political advice to Trump. He has not worked directly for the President, but at least as far back as 2013 he has been a contractor for one of ...