By now, we know that Artificial Intelligence is the simulation of human behaviour by a machine/computer. In the 21st century, AI has reached almost every house, like Alexa, Siri, product recommendations to name a few. According to a study by Creative Strategies, only 2% of iPhone owners have never used Siri, and only 4% of Android owners have never leveraged the power of OK Google. When it comes to usage, 51% use voice assistants in the car, 6% in public, and 1.3% at work. While studying AI, there is one term that you are going to come across a lot, and it is Machine Learning (ML).

It is widely acknowledged that addiction relapse is highly associated with spatial-temporal factors such as some specific places or time periods. Current studies suggest that those factors can be utilized for better relapse interventions, however, there is no relapse prevention application that makes use of those factors. In this paper, we introduce a mobile app called "Addict Free", which records user profiles, tracks relapse history and summarizes recovering statistics to help users better understand their recovering situations. Also, this app builds a relapse recovering community, which allows users to ask for advice and encouragement, and share relapse prevention experience. Moreover, machine learning algorithms that ingest spatial and temporal factors are utilized to predict relapse, based on which helpful addiction diversion activities are recommended by a recovering recommendation algorithm. By interacting with users, this app targets at providing smart suggestions that aim to stop relapse, especially for alcohol and tobacco addiction users.

From Siri, the virtual assistant in Apple mobile devices, to self-driving cars, artificial intelligence (AI) is progressing rapidly, outperforming humans at some tasks. As with the majority of the changes happening globally, there will be positive and negative impacts as AI continues to shape the world we live in. Every single one of us will have to reckon with our ability to balance the human way of life and the transition to the AI cosmos. According to a report by the technology research group IDC, spending on AI is expected to reach US$46 billion by 2020 with no signs of slowing down. AI is definitely on the rise in both business and life in general. The question is, will humans eventually lose control as machines become super-intelligent?

Black Friday itself might be done and dusted but the best deals for 2019 will continue all weekend, plus Cyber Monday deals are just around the corner. That's good news for anyone late to the sales party as that means there's still a significant amount of savings to be had. You'll find those savings everywhere and anywhere, both at big box retailers like Best Buy, Walmart and Target as well as online at Amazon, NewEgg and B&H Photo. So when does Black Friday well and truly end? Admittedly, some deals were for Black Friday only and sold out within minutes or hours, but many deals started a few days before Black Friday and will continue through to Cyber Monday after Thanksgiving. There are many different kinds of deals coming up from laptops to phones to AirPods (although the latter is heading quickly out of stock). We've sadly had little in the way of a cracking Nintendo Switch Black Friday deal, and even the PS4 deals - while they have existed, and haven't been too bad - were more scarce than we expected. But, based on what we saw on Friday, there's a lot more to come. If you're thinking about a deal at the moment, or you're scared it will go cheaper on Cyber Monday, then our advice is simple: if it has a good discount attached to it, go for it! If you later find the product is cheaper elsewhere, you can always buy it again and return the original. Just make sure to check the retailer's terms and conditions for returning items. It's basically been Apple products that have been the winners - with $400 cashback on an iPhone 11, lower prices on AirPods and Apple Watches and MacBook / iPads being cheaper than ever before, it's been (and still is) the time to grab yourself a bargain. There's more in there too - Dyson has been popular for Black Friday 2019, DNA kits have been a surprise package and we've even seen great discount on power tools as well. Anyway, enough of telling you what you're getting, and onto the deals themselves - and if you want something more than what we've scavenged from the depths of the web, here are all the top Black Friday sales from around the web first: HP Laptop 15t: $979.99 $519.99 from HP This HP laptop is a phenomenal price and comes with a 15-inch display paired with a powerful 10th gen Intel Core i7 processor to power the whole thing. Perfect for fitness fanatics, the Powerbeats Pro offer an adjustable ear hook design that keeps your buds firmly in place.

Nowadays, collaborative filtering recommender systems have been widely deployed in many commercial companies to make profit. Neighbourhood-based collaborative filtering is common and effective. To date, despite its effectiveness, there has been little effort to explore their robustness and the impact of data poisoning attacks on their performance. Can the neighbourhood-based recommender systems be easily fooled? To this end, we shed light on the robustness of neighbourhood-based recommender systems and propose a novel data poisoning attack framework encoding the purpose of attack and constraint against them. We firstly illustrate how to calculate the optimal data poisoning attack, namely UNAttack. We inject a few well-designed fake users into the recommender systems such that target items will be recommended to as many normal users as possible. Extensive experiments are conducted on three real-world datasets to validate the effectiveness and the transferability of our proposed method. Besides, some interesting phenomenons can be found. For example, 1) neighbourhood-based recommender systems with Euclidean Distance-based similarity have strong robustness. 2) the fake users can be transferred to attack the state-of-the-art collaborative filtering recommender systems such as Neural Collaborative Filtering and Bayesian Personalized Ranking Matrix Factorization.

Commencing in the 1980s with the appearance of specialised isolated-word recognition (IWR) systems for military command-and-control equipment, spoken language technology has evolved from large-vocabulary continuous speech recognition (L VCSR) for dictating documents (such as Dragon's Naturally Speaking and IBM's Via V oice) released in the late 1990s, through telephone-based interactive voice response (IVR) systems to the launch of Siri (Apple's voice-enabled personal assistant for the iPhone) in 2011. Siri was quickly followed by Google Now and Microsoft's Cortana. The following years heralded a new era of smart speaker based voice assistants, starting with Amazon's 2015 release of Alexa followed later by Google Home, Apple's HomePod and Sonos One. These contemporary systems not only represent the successful culmination of over 50 years of laboratory-based speech technology research (Pieraccini, 2012), but also signify that speech technology had finally become "mainstream" (Huang, 2002) (at least, in the English-speaking world). Indeed, the market penetration of these smartphone and smart speaker based voice assistants is astounding. For example, Siri has had over 40 million monthly active users in the U.S. since July 2017, Google Assistant is available on over 225 home-control brands and more than 1,500 devices, and tens of millions of Alexa-enabled devices were sold worldwide over the 2017 Christmas holiday season (Boyd, 2018). Also, a study by Juniper Research (Smith, 2017) estimated that the number of voice assistant devices across all Figure 1: The evolution of spoken language processing applications from specialised military'command-and- control' systems of the 1980/90s to contemporary'voice-enabled personal assistants' (such as Siri and Alexa) and future'autonomous social agents', i.e. robots.

Proper nomenclature has to be followed when referring to either AI or automation. The trend of misinterpreting AI for automation and vice versa has grown uncontrollably mostly due to recent developments in voice recognition systems like Alexa, Google Assistant, and Siri. These technologies automate search processes that until now were heavily manual, and they have automated them to such an extent that this automation is beginning to be perceived as commonplace. To a non-technical person, it may even seem as if the machines are "thinking". However, this is not the case.

Ask for Alexa Echo App for the Amazon Echo or Dot, is a revolutionary must have for your home. Unlock your investment in your Alexa powered device with our fun new Ask Alexa App for the Amazon Echo or Dot App! Use our Ask for Alexa Echo App for the Amazon Echo or Dot to create your own sayings for your Amazon Alexa device, and then share them with your friends! You can also use our Ask for Amazon Alexa Echo App for the Amazon Echo or Dot to talk directly to your Alexa device, without you saying a word! Our Ask for Alexa Echo App for the Amazon Echo or Dot, allows you to say / speak funny quotes and ask funny questions to your amazon echo, amazon dot or amazon Alexa Download Ask for Alexa Echo App for the Amazon Echo or Dot, for over 950 different questions that you can ask Alexa. You'll be rolling in the aisles with some of the answers!

Ask for Amazon Alexa Echo App for the Amazon Echo or Dot, is a revolutionary must have for your home. Unlock your investment in your Alexa powered device with our fun new Ask Alexa App for the Amazon Echo or Dot App! Use our Ask for Amazon Alexa Echo App for the Amazon Echo or Dot to create your own sayings for your Amazon Alexa device, and then share them with your friends! You can also use our Ask for Amazon Alexa Echo App for the Amazon Echo or Dot to talk directly to your Alexa device, without you saying a word! Our Ask for Amazon Alexa Echo App for the Amazon Echo or Dot, allows you to say / speak funny quotes and ask funny questions to your amazon echo, amazon dot or amazon Alexa Download Ask for Amazon Alexa Echo App for the Amazon Echo or Dot, for over 950 different questions that you can ask Alexa. You'll be rolling in the aisles with some of the answers!

Artificial Intelligence Technology has many useful applications in the world and it's currently starting to appear in various applications. These include home technology, automotive, space tech, industrial, manufacturing, business systems and supply chain operations. Business systems such as ERP systems are now starting to introduce both machine learning and Artificial Intelligence technologies. Machine Learning is a scientific study of statistical models and algorithms that many computer systems now use to perform specific tasks, without using a defined instruction. They rely on established patterns of operations, doing the same sort of processes every day.