Since becoming actively involved with the artificial intelligence ecosystem in early 2015, Facebook Inc. has made numerous contributions ranging from niche software modules to entire server blueprints. The social networking giant expanded its repertoire yet again this week by open-sourcing a toolkit called Torchnet that provides building blocks for deep learning projects. As the name implies, it's designed for use with Torch, a popular AI development framework that has been adopted by several of Facebook's engineering teams. Torchnet's main selling point is a set of five programming abstractions meant to common tasks involved in implementing deep learning functionality. One module provides logic for training models and testing their accuracy, while another helps assess the results.

Starting this fall when iOS 10 and macOS Sierra are launched, there will be (optional) changes to Apple's privacy policy. The company has finally acknowledged publicly that it needs to collect at least some types of information if it wants to advance with its artificial intelligence ambitions. The change was announced by Apple SVP Craig Federighi, who said that the company will collect information in a different way to before, as it seeks to improve the ability of Siri and the iPhone to predict the information the user wants. Federighi touted this approach as differential privacy. Wired published an extensive piece about what differential privacy means and how Apple plans to implement it.

From Google to Amazon to Apple, software giants are integrating voice commands, search and a whole lot of data to makes their digital voices not just smarter, but more human. The promise of voice-activated AI is exciting, but in entirely digitizing our interactions we run the risk of losing real conversation. MIT's Sherry Turkle tackles the issue in her book, "Reclaiming Conversation." By retreating to our devices, she argues, we forget what it means to be human. And the hiring of poets and novelists to craft "characters" for these emerging AIs points to the fact that consumers clearly value the human element.

It's time for another edition of "What TNW is reading." If you're not familiar with them, take a moment and enjoy the previous edition about the US election. After having first been colonized by the Spanish, the country – in its own weird way – is part of the Kingdom of the Netherlands and one of the busiest ports in the Northern Hemisphere. One of its four official languages is English and they managed to smush them all together to create Papiamentu, the local language. Speaking all four languages fluently, Cecil is currently adding French and Russian to the mix… he's such an?????????.

We start this four-part whitepaper series with Tableau. Tableau is business intelligence software that helps people see and understand their data. You can add scientific articles relevant to data science, IoT, machine learning, deep learning, big data, dataviz, stats, operations research, AI, machine-to-machine communications, scientific programming and related topics in the comment section below.

We started with the development of Leaf briefly before Google released Tensorflow. For two weeks Leaf's hypothesis seemed unique. Although Leaf has top-notch performance and an uniquely simple yet expressive API, it will lose against Tensorflow. Leaf's current theoretical benefits[1] are less significant, than the benefits that Tensorflow provides[2] over the early, scientific frameworks like Torch, Caffe, Theano. The next generation of tools, that help developers to build machine learning applications will build on Tensorflow, or more specifically on higher-level frameworks, like Keras, who abstract over multiple AI Engines[3].

Farms of 3D printers are a potential solution to batch production, with some companies relying on numerous machines to 3D print a large group of parts at once. While they may increase output, print farms may also be labor intensive to operate. To demonstrate the overall utility of its cloud robotics platform, an Oregon startup called Tend.ai has deployed a robotic arm, artificial intelligence and cloud computing to create an automated print farm. Tend.ai has built what it suggests is a universal machine automation solution that combines a number of components into a cloud robotics platform. While the specific make and model of each piece of hardware is left up to the user, all one needs to get started with Tend.ai is a robotic arm, a webcam and a robotic gripper.

Additionally, the fraud detection and prevention programs that keep your bank account safe are also utilizing predictive analytics. The most sophisticated of these programs analyze your spending habits and compare each purchase against them. The purchases themselves also have fraudulence probability scores (a 1,000 online purchase paid to a company based in Timbuktu is more likely to be fraudulent than a 200 purchase at your local grocery store). If anything seems fishy, the bank sends you an alert to ensure your funds aren't compromised if fraud is, in fact, taking place.

After years of touting itself as the company that didn't access its users data, Apple has finally acknowledged that it really does need at least some collective understanding. The company announced at last week's developer conference that, starting with iOS 10, it will collect a range of new information as it seeks to make Siri and the iPhone better at predicting the information its owner might want at a given time. Apple is looking to thread a fine needle, gaining access to the data it needs to make its servers smarter while also protecting user privacy. It's doing so by employing a concept known as differential privacy. However, the company was initially short on details on just what data it will be collecting and how.

I'm sure I'm not going be the first or last to make the association between the software name "Quixote" and the legendary story of The Ingenious Gentleman Don Quixote of La Mancha by Miguel de Cervantes Saavedra. The main character of the story is first driven by his wild fantasies that originates from all the romantic stories he read. Essentially, the character has no connection to reality and sets out on a journey where the final result is death, not just of the character, but also a metaphorical death of chivalry. In an ONR release, Marc Steinberg, the program manager says "For years, researchers have debated how to teach robots to act in ways that are appropriate, non-intrusive, and trustworthy," There-in lies the rub. "One important question is how to explain complex concepts such as policies, values, or ethics to robots. Humans are really good at using narrative stories to make sense of the world and communicate to other people. This could one day be an effective way to interact with robots."