Mention artificial intelligence and many people envision a dystopian future like something out of Blade Runner or I, Robot, with an impersonal society run by giant, faceless corporations. The reality is much different, as AI is behind many of the most personal services today, like voice assistants (Alexa, Siri) and predictive entertainment platforms (Netflix, Spotify). And it's not just for large enterprise companies: Thanks to more affordable AI options, small businesses are beginning to embrace it. In fact, while only 8 percent of SMBs currently use AI, research shows an additional 32 percent intend to implement it (which amounts to a potential growth rate of 310 percent). It may seem a bit shocking that so many small businesses would want to jump on board the AI train.

A ring, glasses and earbuds are among Amazon's latest voice-controlled devices to offer "even more ways to add Alexa to your daily life". Released last week, several of the products are grouped under Amazon's Echo smart speaker range. They include differently sized Echo speakers and wearables, and depend on the company's voice-activated, artificially intelligent assistant Alexa. The broad range is intended to "make your home smarter and safer, keep family and friends connected, and bring your favourite entertainment to you, wherever you are", according to Amazon. "Amazon introduced an all-new line-up of Echo devices that give you even more ways to add Alexa to your daily life – whether at home or on-the-go," it added.

Amazon (NasdaqGS:AMZN) has made the Alexa Echo available in Brazil. The mega popular virtual assistant chatbot is now able to speak Brazilian Portuguese. "Echo Dot and Echo Show 5 are available for pre-order in Brazil today and will begin shipping to customers starting next week, while Amazon Echo will be available to customers in November,'' according to the press release. "We're excited to introduce Alexa to customers in Brazil, with a custom-built experience that honors Brazil's language and unique culture. Customers across Brazil will be able to ask for their favorite music, control their smart home, and enjoy skills from hundreds of customer-favorite Brazilian brands including Show do Milhão, Porta dos Fundos, UOL Esporte, iFood, Leite Ninho, Cinemark, and more.

AI and the Future of Work: AI is the fourth industrial revolution and 84% of companies know that they need to invest in AI to have a competitive advantage. But how do we actually use AI in our day to day processes while delivering a personalized human touch to each buyer? Learn how to integrate Intelligent Virtual Assistants into your organization to drive greater workforce productivity and job satisfaction. Build higher performing teams by automating the repetitive, routine tasks and freeing up people to do what they do best - build trusted relationships, perform the higher-value tasks that require more complex decision making and emotional intelligence to drive forward progress. A Marketer's Guide to Selfcare Using Intelligent Virtual Assistants Let's be real.

Artificial Intelligence (AI) has been the talk of the town for a while now. I remember the fiasco from chatbots that replied instantly. We have all texted Siri saying'I love you' at least once in our lives. It hasn't been long since then, but Artificial Intelligence, in a very short span, has embedded itself in our lives. The technology first emerged in the mid-1950s. Some feared it would replace the human workforce in the future, but for now, we are safe.

This year, self-driving cars started getting pretty good. Deep fakes video started getting pretty convincing. Our virtual assistants got to the point where they could understand us well enough to do some simple things, like tell us the weather or get driving directions home. When it comes to artificial intelligence, we have reached an inflection point. The technology is good enough to use. Next year promises to be a breakout year for AI, as it starts to permeate all aspects of our lives. Here are predictions for 2020 from some of the world's top AI experts. Jen Snell is VP of product marketing at Verint, where she leads a product strategy team focused on intelligent self-service, conversational AI, automation, and analytics. She is a frequent speaker and a leading contributor on topics shaping the development and design of interactive technologies. Follow her on Twitter @JenniferLSnell and on LinkedIn.

How can banks and financial institutions deliver great experiences in the fragmented digital world? Successful financial services firms have reputations and brands that convey trust. Many have embraced digital channels for reaching and engaging clients and prospects and, ultimately, for building relationships with them. But in today's world, true success focuses on the experience--the sum total of offerings, interactions, and transactions. An integrated, programmatic, and highly automated approach offers the best way to accomplish this goal. So: How do you do it?

Silas: High Performance, Explainable and V erifiable Machine Learning Hadrien Bride, Zh e H ou Griffith University, Nathan, Brisbane, Australia Jie Dong Dependable Intelligence Pty Ltd, Brisbane, Australia Jin Song Dong National University of Singapore, Singapore Ali Mirjalili Griffith University, Nathan, Brisbane, AustraliaAbstract This paper introduces a new classification tool named Silas, which is built to provide a more transparent and dependable data analytics service. A focus of Silas is on providing a formal foundation of decision trees in order to support logical analysis and verification of learned prediction models. This paper describes the distinct features of Silas: The Model Audit module formally verifies the prediction model against user specifications, the Enforcement Learning module trains prediction models that are guaranteed correct, the Model Insight and Prediction Insight modules reason about the prediction model and explain the decision-making of predictions. We also discuss implementation details ranging from programming paradigm to memory management that help achieve high-performance computation.1. Introduction Machine learning has enjoyed great success in many research areas and industries, including entertainment [1], self-driving cars [2], banking [3], medical diagnosis [4], shopping [5], and among many others. However, the wide adoption of machine learn-Preprint submitted to Elsevier October 4, 2019 arXiv:1910.01382v1 The ramifications of the black-box approach are multifold. First, it may lead to unexpected results that are only observable after the deployment of the algorithm. For instance, Amazon's Alexa offered porn to a child [6], a self-driving car had a deadly accident [7], etc. Some of these accidents result in lawsuits or even lost lives, the cost of which is immeasurable. Second, it prevents the adoption in some applications and industries where an explanation is mandatory or certain specifications must be satisfied. For example, in some countries, it is required by law to give a reason why a loan application is rejected. In recent years, eXplainable AI (XAI) has been gaining attention, and there is a surge of interest in studying how prediction models work and how to provide formal guarantees for the models. A common theme in this space is to use statistical methods to analyse prediction models.

Consider this: you buy a nice shiny new pair of headphones. When you unbox the headphones there's a manual that says'download our app to set up'. So you get the app, you create an account, you connect your headphones. You very much enjoy the sound quality. Even though the purpose of this app is to'set up' your headphones, it also provides a gateway to your behaviour.

Oracle has added AI voice commands to its Digital Assistant, offering users an alternative way to interact with its various business apps. The company on Tuesday also announced that the bot will integrate with Microsoft's work stream collaboration platform, Teams. Oracle's Digital Assistant was launched last year as an interface to its portfolio of enterprise software applications, which includes sales, marketing and human resource tools. The virtual assistant uses AI techniques such as machine learning and natural language processing and understanding to interpret user intent; it's designed to automate processes such as expense approvals and meeting re-schedules. The Digital Assistant was initially targeted at text interactions and embedded in various communication and collaboration tools such as Slack, WeChat and Facebook Messenger, as well as user websites and as a standalone mobile app.