Should musicians, whose job relies on the unpredictable and mysterious workings of human imagination, heed the warnings about artificial intelligence driving humans into unemployment? Apparently, the answer to that question is bit complicated. Artificial intelligence is gradually transforming into a general-purpose technology that permeates virtually every aspect of human life and society. Just like electricity (another general-purpose technology) which had an impact on music and musical instruments, AI algorithms will inevitably change the way we create and perform music. While this does not mean an end to the era of human musicians, it is fair to say that some dramatic changes are lying ahead.

Should musicians, whose job relies on the unpredictable and mysterious workings of human imagination, heed the warnings about artificial intelligence driving humans into unemployment? Apparently, the answer to that question is bit complicated. Artificial intelligence is gradually transforming into a general-purpose technology that permeates virtually every aspect of human life and society. Just like electricity (another general-purpose technology) which had an impact on music and musical instruments, AI algorithms will inevitably change the way we create and perform music. While this does not mean an end to the era of human musicians, it is fair to say that some dramatic changes are lying ahead. At the heart of recent artificial intelligence breakthroughs are machine learning algorithms, programs that find patterns in large sets of data.

It's the most anticipated smartphone in years, and its success will be important for Apple. I was one of just a few journalists to be given a chance to spend the last nine days getting to grips with the new iPhone X (written X but pronounced 10). There's quite a bit to say. This is one of the key features on the new phone and it's a winner. I've gone into more detail separately here but the essence is that the Home Button found on all previous iPhones, and the fingerprint sensor, Touch ID, have been removed. Now, a sophisticated facial recognition system means that when you look at the phone, if it recognises you, it unlocks. Other phone manufacturers have included facial recognition but this one is significantly more consistent and reliable.

My new favorite vlog to follow is that of Simone Giertz. She is a Swedish inventor, maker and a robotics enthusiast. She is your real life, modern and feminine version of Dr. Emmet Brown (from the movie Back to the Future). Even better, she builds artificial intelligence/robots to help her with the mundane daily tasks like brushing teeth or making a bowl of cereal. I doubt that these robots are truly useful, but they are funny.

Most people do not interact with Semantic Web data directly. Unless they have the expertise to understand the underlying technology, they need textual or visual interfaces to help them make sense of it. We explore the problem of generating natural language summaries for Semantic Web data. This is non-trivial, especially in an open-domain context. To address this problem, we explore the use of neural networks. Our system encodes the information from a set of triples into a vector of fixed dimensionality and generates a textual summary by conditioning the output on the encoded vector. We train and evaluate our models on two corpora of loosely aligned Wikipedia snippets and DBpedia and Wikidata triples with promising results.

Research[R] LSTM as a Dynamically Computed Element-wise Weighted Sum - reinterprets gating in LSTMs as self-attention over time (a weighted sum over the candidate states c _t); shows that dependence on h_t-1 for computing c _t is not necessary; thus gating does the heavy lifting in LSTMs, not h h mappings (openreview.net)

Should musicians, whose job relies on the unpredictable and mysterious workings of human imagination, heed the warnings about artificial intelligence driving humans into unemployment? Apparently, the answer to that question is bit complicated. Artificial intelligence is gradually transforming into a general-purpose technology that permeates virtually every aspect of human life and society. Just like electricity (another general-purpose technology) which had an impact on music and musical instruments, AI algorithms will inevitably change the way we create and perform music. While this does not mean an end to the era of human musicians, it is fair to say that some dramatic changes are lying ahead. At the heart of recent artificial intelligence breakthroughs are machine learning algorithms, programs that find patterns in large sets of data.

They're usually regarded as creatures to be feared, but new images show that wasps also engage in very delicate behaviour. The stunning images show wasps blowing water bubbles before balancing the delicate structures on their front legs. The curious behaviour is used by wasps to remove excess moisture from their nests, according to experts. They're usually regarded as creatures to be feared, but new images show that wasps also engage in very bubble blowing delicate behaviour The stunning images show wasps blowing water bubbles before balancing the delicate structures on their front legs. Wasps use this method to dry off their nests, by sucking up water and then expelling it as tiny spheres of water.

Spotify, the largest on-demand music service in the world, has a history of pushing technological boundaries and using big data, artificial intelligence and machine learning to drive success. The digital music company with more than 100 million users has been busy this year enhancing its service and tech capabilities through several acquisitions. Industry watch dogs predict the company will launch an IPO in 2018. When you have tens of millions of people listening to music every minute of the day, you have access to an extraordinary amount of intel that includes what songs get the most play time, to where listeners are tuning in from and even what device they are using to access the service. There's no doubt Spotify is a data-driven company and it uses the data in every part of the organization to drive decisions.

In celebration of it successfully learning the xor function: I'm announcing the neural network library I've been working on. This is a Haskell library. Its API is somewhat reminiscent of Tensorflow, but is currently much less complete. It's currently CPU only but I have plans to add GPU acceleration with OpenGL compute shaders (which would make it the only neural network library I know of to be able to make use of a GPU I actually own)