Episode Summary: One facet of business that nearly any industry has in common is the need to stay on top of news in their respective market, including competitor strategies or understanding changes in news related to the field. Media monitoring is a domain that machine learning (ML) is well suited for, with it's ability to coax out headlines, contextual information, and financial data from the seemingly endless stream of social, blog, and other information on the web today. Signal is a company that uses ML specifically for these purposes. In this episode, we speak with Signal's Chief Data Scientist and Co-founder Dr. Miguel Martinez, who dives into real business use cases illustrating the use of machine learning for media monitoring across industries. Brief Recognition: Dr. Miguel Martinez is chief data scientist at Signal, where he manages a team of data scientists to transform best algorithms from the fields of machine learning, information retrieval, and natural language processing into large-scale commercial products.

It's the beginning of the end for smartphone apps as we have known and tapped on them, reckons Gartner. The analyst is calling the start of a "post-apps" era, based on changes in consumer interactions that appear driven, in large part, by the rise of dominant messaging platforms designed to consume more and more of mobile users' time and attention. It reckons messaging apps will become more popular than social media apps within the next two years. In a new report, based on a survey of mobile users in the US, China and the UK, Gartner's reading of the app usage tea-leaves shows signs of messaging platforms cannibalizing other apps, with for example, usage of dedicated video apps declining four percentage points between the 2015 and 2016 editions of the survey. Usage of standalone maps apps also shrunk by three percentage points, year-over-year, according to Gartner's data.

Amazon is bringing its Alexa voice assistant to British televisions with a £40 Fire TV stick that turns almost any TV into a smart streaming box. The new Fire TV stick comes with a voice-enabled remote, giving users access to voice controls and search for movies, music and TV shows. But it will also perform Alexa's other skills, allowing users to check their commute, get a weather forecast and to answer questions and control smart home devices by speaking into the remote and showing new so called video cards with information on screen. Jorrit Van der Meulen, vice president of Amazon Devices International, said that the company's focus with the new Fire TV stick was on performance and speed, making it 30% faster than the old device, to provide a smooth, rich and voice-controlled experience in a package barely larger than a flash drive. He said: "Fire TV was the number one selling item on Amazon in the UK in 2016, and now we've made it faster and given it the best of Alexa."

Even though Samsung has established a cause for those Galaxy Note 7 flare-ups, the device's story is not over. Korean outlet Hankyung reports that the company will sell the "refurbished" phones, but with smaller, less-explodey batteries inside. It doesn't sound like the devices will be returning to US or European markets (it's tough to imagine regulators reversing course on bans after the first recall and reissue), but they could be sold in India or Vietnam instead. According to the report, Samsung has some 2.5 million Galaxy Note 7s left over after using 20,000 or so up in testing to determine the cause of the problem. The refurbished devices will have new cases, and batteries with a capacity between 3,000 and 3,200mAh (the phones initially contained a 3,500mAh battery).

Across the globe, energy systems are changing, creating unprecedented challenges for the organisations tasked with ensuring the lights stay on. In the UK, large fossil fuelled power stations are being replaced by increasing levels of widely distributed wind and solar generation. This renewable power is clean and free at the point of use but it cannot always be relied upon. To date National Grid has managed this intermittency by keeping polluting power stations online to make up the difference but Artificial Intelligence offers an alternative approach. What's needed is a smart grid which can integrate renewable energy efficiently at scale without having to keep polluting power stations online to manage intermittency.

According to Startup Nation Central, a database for Israeli tech companies, the Tel Aviv-based firm had raised $1 million prior to the acquisition and employs up to 10 people. An email sent to the company requesting comment was not immediately replied. The company has sales in China, Israel, Europe, and the US, according to the data firm. RealFace's first product, the Pickeez app, created a new way to enjoy photos, with its recognition software automatically choosing the user's best photos from every platform they're on. Besides RealFace, Apple has acquired three other Israeli companies to date.

The primary application of artificial intelligence in retail is customer service chatbots, intelligent search tools, and personalisation. Despite knowing where to put their money, only a handful of retailers in the UK have trialled AI due to it being prohibitively expensive. Most AI investment in 2017 will be targeted towards e-commerce -- though Amazon is something of an exception. Amazon intends to use AI to replace in store cashiers in its Amazon Go stores to detect products shoppers have picked up. Over the next five years a growing number of retailers will buy into AI as it becomes more affordable. Here's where some big players are putting their money: Most retailers use algorithms to suggest similar items or items bought by other customers already, but in 2016 John Lewis was one of the first retailers in the UK to implement an artificially intelligent visual search tool for its iPad app.

This repository contains the TSFRESH python package. "Time Series Feature extraction based on scalable hypothesis tests". The package contains many feature extraction methods and a robust feature selection algorithm. Data Scientists often spend most of their time either cleaning data or building features. While we cannot change the first thing, the second can be automated.

Want to receive a weekly deep dive into all things auto, transportation, & logistics tech? Click here to subscribe to our auto tech newsletter. Private companies working in auto tech are on pace to attract record levels of deals and funding in 2016, with autonomous driving startups leading the charge. As expectations around self-driving vehicles have risen, major corporations have ramped up their own initiatives, racing to deploy technology onto public roads. Using CB Insights' investment, acquisition, and partnership data, we identified 33 corporate groups involved in the development of advanced driver assistance systems and self-driving vehicles. They are a diverse group of players, ranging from automotive industry stalwarts to leading technology brands. The list is organized alphabetically (companies working on industrial autonomous vehicles were not included in this analysis).

We consider the minimization of composite objective functions composed of the expectation of quadratic functions and an arbitrary convex function. We study the stochastic dual averaging algorithm with a constant step-size, showing that it leads to a convergence rate of O(1/n) without strong convexity assumptions. This thus extends earlier results on least-squares regression with the Euclidean geometry to (a) all convex regularizers and constraints, and (b) all geome-tries represented by a Bregman divergence. This is achieved by a new proof technique that relates stochastic and deterministic recursions.