Two robotic arms that each hold a pen begin to draw with short strokes on two sheets of paper-- two eyes, a mouth and the silhouette of a face. They portray the front and profile view of Eliseo Carrera Bustillo, a 26-year-old student sitting on a stool while two cameras observe and analyse him closely. Both machines imitate the style of their creator--the French artist Patrick Tresset--and it only takes half an hour to finish the portrait and sign it. Nowadays, more and more artificial intelligence systems paint pictures, compose music, create poetry and write novels. But what difference is there between a work created by a machine and by a human?

A percentage (usually around the 70%) that can be used for the training of the model, called training set. The rest of the data will play as the validation set and it will be used to evaluate the performance of the model when it receives data that has never seen. A percentage (usually around the 70%) that can be used for the training of the model, called training set. The rest of the data will play as the validation set and it will be used to evaluate the performance of the model when it receives data that has never seen. For more complex types of model, often a small percentage (usually 5% to 10% of all the datasets) is reserved for an additional evaluation of the performance, after that the model shows good results also on the validation set.

Branded Entertainment Network (BEN), the leader in connecting global brands to consumers through the power of popular entertainment, today revealed early successes from BEN's market leading Artificial Intelligence (AI) solution. Popular brands leveraging the solution include the streaming service Philo and video/games rental operator Redbox, who have all seen increased performance from their influencer marketing campaigns. BEN is the first entertainment marketing company to leverage deep learning neural networks that are backed with over 30 years of proprietary campaign data, such as performance and ROI tracking, including 10 years of influencer marketing campaign data. BEN's neural networks uniquely combine this structured data with unstructured video and audio data. Rather than simply matching brands with influencers, BEN's AI has been trained to provide its clients with next generation predictive analytics that drive actual campaign results.

Machine learning, predictive analytics, IoT, smart cities and fintech are some of the hot topics where you need to know the latest. Get a sneak peak of upcoming DATAx with the DATAx New York festival post event report.

We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse against women on Twitter. On a technical front, we carefully curate an unbiased yet low-variance dataset of labeled tweets, analyze it to account for the variability of abuse perception, and establish baselines, preparing it for release to community research efforts. On a social impact front, this study provides the technical backbone for a media campaign aimed at raising public and deciders' awareness and elevating the standards expected from social media companies.

When it comes to the creative side of advertising, the promise of artificial intelligence--that it could create ads optimized in every possible way--has mostly been the subject of satire. Twitter gave birth to a meme about forcing bots to watch 1,000 hours of programming to write hilariously flawed (and fictional) scripts, and Burger King took the joke mainstream by making an ad campaign supposedly written by AI, which celebrated a chicken sandwich that "tastes like bird." In launching that campaign, Burger King's global head of brand management, Marcelo Pascoa, noted, "Artificial intelligence is not a substitute for a great creative idea coming from a real person." Now Lexus has put that claim to the test. The automaker and agency The&Partnership have created what they describe as the first ad both written by an AI and directed by an Oscar winner (Kevin Macdonald, who won Best Documentary for One Day in September in 2000).

Global and business leaders met in Davos last week to talk about everything from the environment to the future of business. One thing everyone privately agrees on is that the future of business is in Artificial Intelligence. Stephanie Ruhle is joined by New York Times Business Columnist Kevin Roose to discuss why business leaders don't want to talk about AI publically.Jan.

Robot vacuums have now been around long enough that you might watch one bump around a living room and think, why isn't there a robot that could mow my lawn? Turns out, it's not for lack of trying. For more than a decade, iRobot, the company behind the Roomba vacuumbot, has been working - and working - on robotic lawn mowers. Now it finally has something to show for the effort, though it's come at a cost. This Wednesday, Jan. 16, 2019 photo shows an iRobot Terra lawn mower in Bedford, Mass.

According to the IHS Markit white paper, The Top Trends of 2019: Powered by Transformative Technology, three key trends are expected to have a major effect on both commercial and consumer markets in 2019. The increasing ubiquity of video is forcing significant industry change, as a growing number of players vie for consumer attention and revenue and as businesses adapt to cope with the rising demand. In fact, online video subscriptions from over-the-top (OTT) and traditional media players alone will more than double between 2017 and 2022, by which time they will approach the one billion mark. While TV, home entertainment, social media, video games and other media sectors are at the heart of the video everywhere trend, other industries – including security, education, and healthcare – are also becoming increasingly reliant on video technology. The edge is already transforming the way networks are deployed and devices are built.

Recruiters often receive a stack of applications which are not relevant to the job profiles they are looking for and the same way job seekers too fail to find a job that will offer them the opportunity to explore their potential. Vasitum, a Delhi-based HR technology startup, has launched a platform which offers real-time candidate profile screening with the help of artificial intelligence, and eliminating the recruiters' woes. Vasitum claims that its simplified user interface (UI) makes the recruitment process and job hunting easier and faster with real-time candidate screening, which used to be very time-consuming earlier. Its streamlined application tracking system (ATS) allows recruiters to bucket each application systematically. On receiving a resume, the platform spots gaps if there is any and ask the job seekers to provide further details, it said.