Facebook CEO Mark Zuckerberg attacked Republican presidential candidate Donald Trump's extreme stance on refugees and immigrants during a speech on Tuesday, criticizing "fearful voices for building walls and distancing people they view as others." The founder of the social network spoke about Facebook's goal of sharing ideas during his company's annual F8 developer conference in San Francisco, when he said "instead of building walls, we can help build bridges," by welcoming refugees and immigrants. "It takes courage to choose hope over fear," he said. "Whether we are welcoming a refugee fleeing war or an immigrant seeking opportunity." Facebook launched the FWD.us immigration reform lobbying group in 2013, which advocates for legislation that supports a more open worker visa process.

You may think you do, but a recent experiment by a Russian photographer suggests otherwise. In a project entitled, "Your face is big data," Rodchenko Art School student Egor Tsvetkov began by photographing about 100 people who happened to sit across from him on the subway at some point. He then used FindFace, a facial-recognition app that taps neural-network technology, to try to track them down on Russian social media site VK. It was ridiculously easy to find 60 to 70 percent of the subjects aged between 18 and 35 or so, he found, although for older people it was more difficult. Along the way, he learned a whole lot about the lives of complete strangers.

Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed. The science behind machine learning is interesting and application-oriented. Many startups have disrupted the FinTech ecosystem with machine learning as their key technology. There are various applications of machine learning used by the FinTech companies falling under different subcategories. Let us look at some of the applications of machine learning and companies using such applications.

The marriage of computing power and data is finally bearing fruit in the field of cognitive computing, sometimes called machine learning or, more controversially, artificial intelligence. In its most everyday form, we see it in tools such as Google Translate or Microsoft's Bing Translate, which can translate phrases and documents effortlessly across multiple languages. More futuristically, the promise of self-driving vehicles, which can complete entire road journeys without driver intervention, is already being realised. Yet the biggest revolution in work is happening at some of the most basic levels, such as reading and dissecting legal documents to extract meaning and useful information. The tedious slog of work can be transformed by computers which are able to read and parse legal phrases, and summarise them or enter relevant details into a database or spreadsheet.

The Bible is an unusual book, as it is not only the most controversial but also the best-selling book ever written. Now, a ground-breaking digital analysis has revealed how many writers have penned it. The research and innovative technology behind it stand to teach us about the origins of the Bible itself. "It's well understood that the Bible was not composed in real time but was probably written and edited later," Arie Shaus, a mathematician at Tel Aviv University told Gizmodo. "The question is, when exactly?"

Since the release of Skytree Express, we have been receiving a number of requests for example scripts, tutorials and questions about automation. This tutorial-like blog post will help answer (some of) those questions using a real-world dataset. How can we classify people into high or low income earning group? Such questions are helpful in understanding whom to send a marketing coupon to for an expensive jewelry item vs an offer for cheap gas. To answer this question, we will use the widely available income datasets.

The bots are, for sure, coming to Facebook. After nearly a year of rumors circulating about Facebook creating a bot store and several other apps releasing such a system, the company has announced its own system for users to communicate with businesses without another human on the other line. "I don't know anyone who likes calling businesses," said CEO Mark Zuckerberg. "We think there's got to be a better way to do this. Facebook released Messenger Platform Tuesday, Zuckerberg announced at the company's annual F8 developers conference. Launch partners include CNN and 1-800-Flowers. The system now lets a Messenger user get news from CNN and order flowers, for example, by chatting with a bot. "To order from 1-800-Flowers, you never have to call 1-800-Flowers again," Zuckerberg said, inspiring laughs from the audience. Additionally, Facebook released an application programming interface for live video, which means app developers can integrate Facebook's live product into their own apps or websites. For example, drone manufacturers can integrate Facebook Live into their devices to live-stream video from a drone. Not every developer at F8 or beyond the conference may choose to build a company on Facebook's chatbots, but it can be a quicker way to grow and establish a business than trying to market one's own app. "You're going to see a lot of really successful small businesses that are chatbot-based.

Facebook just released new tools that will let any business build "smart" chatbots that users can interact with and even purchase things from while using the Messenger app. But what about Facebook's own super-smart virtual assistant, M? The bot, which Facebook first introduced to the world in the Fall, got few on-stage mentions during the company's F8 developer conference on Tuesday. And the third-party chatbots that Facebook now wants outside businesses to create might seem to obviate the need for Facebook to maintain its own bot. But Facebook told Business Insider that the company has not given up on M, even if the bot is still "a long way" from being broadly released. Stan Chudnovsky, head of product for messaging at Facebook, assures Business Insider that the company does still foresee M as being its own product.

He continues, "The travel industry is no exception, and for the most part, travel brands are missing an opportunity to become an integral part of their customers' lifestyle like Amazon or Netflix. Even airlines are hiring data scientists who can employ AI techniques, such as machine-learning algorithms to provide real-time, highly-personalized offers for different customers. And it makes a lot of sense, as airlines run into many situations where one customer falls into a different profile for different purchases. For example, a traveler booking a business trip probably has vastly different preferences when it comes to price and convenience then that same traveler does when scheduling a family vacation. Instead of guessing which situation a traveler is in during a particular purchase, machine-learning algorithms can identify patterns that know which profile that particular person fits at any given time, and provide an accordingly enhanced and personalized experience."

The issue of Artificial Intelligence (AI) has been a mystery for mankind for decades. Movies, literature – you name it – robots and intelligent machines were always an issue of both: great fascination and worrisome panic. However, over the last month, the technology of artificial intelligence made a huge step from fiction towards reality. Google, Amazon, IBM – they all want now to participate in the fast growing market of the future. The advantages of AI for the so called Industry 4.0 are clear and not far to seek.