Have you seen Ex Machina (2015)? A smart man creates a smart robot girl, Ava. This machine turned out to be more intelligent then its creator. Or have you seen Her (2013)? A lonely writer falls in love with Samantha, his intelligent computer operating system with accelerated learning capability.

A couple of weeks ago, the authority that oversees broadcast licensing in Germany concluded that internet streaming services should be subject to the same licensing imposed on broadcast radio and television. The focus is on Twitch.tv This will be a test case for the entire world as governments and tax authorities realize they are missing out on license fees and the ability to regulate to these services. What engrained power structure could resist? In the early 1900s there was a radio craze not unlike the personal computer revolution of the 70s and 80s. Hobbyist magazines quickly evolved into a commercial enterprise.

I've been reading about Gcam, the Google X project that was first sparked by the need for a tiny camera to fit inside Google Glass, before evolving to power the world-beating camera of the Google Pixel. Gcam embodies an atypical approach to photography in seeking to find software solutions for what have traditionally been hardware problems. Well, others have tried, but those have always seemed like inchoate gimmicks, so I guess the unprecedented thing about Gcam is that it actually works. But the most exciting thing is what it portends. I think we'll one day be able to capture images without any photographic equipment at all. Now I know this sounds preposterous, but I don't think it's any more so than the internet or human flight might have once seemed.

Weekday afternoons, millions of Americans -- many stuck in rush-hour traffic -- learn the business news of the day from Kai Ryssdal, a former Navy pilot and host of the public radio show Marketplace. "I spend almost as much time with Kai Ryssdal as I do with my own husband," joked Sally Kilbridge of Scottsdale, Ariz., who toughs out her more than two-hour-a-day commute by listening to public radio. Marketplace, which is produced in downtown Los Angeles by American Public Media, is the most popular business program broadcast in the U.S., with an average of 14.6 million listeners a week. In the last year, the 28-year-old program has seen its audience grow 16% -- benefiting from Americans' increased appetite for news. Hoping to capitalize on its success, Marketplace has launched an ambitious plan to remain a vital source for economic information as consumers' listening habits change, putting a strain the traditional broadcast model.

Once the preserve of videographers with big production budgets, drones have now dropped in price by up to 30%, and not a day go by without a new drone being announced. Just recently DJI announced the latest addition to its Phantom range, the DJI Phantom 4. So 4K video shooting and high definition aerial photography can now be all yours for around £500. So here's a look at just what you can do with a drone… not all of them are entirely serious. The trouble with starting out on your own as a freelance photographer or videographer is that you're entering an incredibly crowded market. There are a lot of good people out there, using a lot of good kit, and it's tough to stand out.

In China's quest to shed its reputation as a land of copycats, the world's second-biggest economy is pouring resources in to the hottest area in technology innovation: artificial intelligence. With the goal of nurturing world-class companies that can compete with the likes of Google and IBM in building intelligent machines, the Chinese leadership singled out AI as a key area of development in a report released during the National People's Congress in March. Soon after, the country's biggest technology companies -- Alibaba, Baidu and Tencent -- announced plans for AI laboratories and projects worth billions of dollars.

The task of determining item similarity is a crucial one in a recommender system. This constitutes the base upon which the recommender system will work to determine which items are more likely to be enjoyed by a user, resulting in more user engagement. In this paper we tackle the problem of determining song similarity based solely on song metadata (such as the performer, and song title) and on tags contributed by users. We evaluate our approach under a series of different machine learning algorithms. We conclude that tf-idf achieves better results than Word2Vec to model the dataset to feature vectors. We also conclude that k-NN models have better performance than SVMs and Linear Regression for this problem.

Work on Automatic Music Transcription (AMT) dates back more than 30 years, and has known numerous applications in the fields of music information retrieval, interactive computer systems, and automated musicological analysis (Klapuri, 2004). Due to the difficulty in producing all the information required for a complete musical score, AMT is commonly defined as the computer-assisted process of analyzing an acoustic musical signal so as to write down the musical parameters of the sounds that occur in it, which are basically the pitch, onset time, and duration of each sound to be played. Despite a large enthusiasm for AMT challenges, and several audio-to-MIDI converters available commercially, perfect polyphonic AMT systems are out of reach of today's technology (Klapuri, 2004; Benetos et al., 2013b). To overcome these limitations, a practical engineering solution was to use computational techniques from statistics and digital signal processing, allowing more complex modeling of the musical signal. In this paper, we investigate the use of different Hidden Markov Models (HMMs) in AMT, and evaluate their impacts on transcription performance. HMMs are a ubiquitous tool to model time series data, and have been widely used in various tasks of Music Information Retrieval, especially in music structure analysis by characterizing repetitive patterns (Logan and Chu, 2000) or performing harmonic analysis (Raphael and Stoddard, 2003), chord estimation (Lee and Slaney, 2008) and musicological modeling of note transitions (Ryynanen and Klapuri, 2008). For what concerns the task of AMT, the sequential structure that may be inferred from musical signals can be usefully integrated to systems with HMMs.

The importance of algorithms in our lives today cannot be overstated. They are used virtually everywhere, from financial institutions to dating sites. But some algorithms shape and control our world more than others -- and these ten are the most significant. Just a quick refresher before we get started. Though there's no formal definition, computer scientists describe algorithms as a set of rules that define a sequence of operations.

For me this question has always been the defining moment of Ridley Scott's sci-fi classic, Blade Runner. Deckard, the policeman anti-hero played by Harrison Ford, has just discovered that Rachel, the self-possessed personal assistant to the founder of the Tyrell Corporation, is in fact one of the company's advanced replicants: a robot. His question to Dr Eldon Tyrell is loaded with the certainty of bigotry -- that repeated'it'. But Deckard's uncertainty about Rachel, and the essential differences between humans and machines, is just the beginning of a process of disorientation that pursues him all the way to the film's brutal but surprising climax. That we have yet to reach the dark dystopia of Blade Runner in real life is pretty obvious -- just look around you. It is also obvious from the nonetheless intriguing robotics exhibition that opened a few weeks ago at the Science Museum in London.