We see news about AI everywhere; sometimes, we see the excitement around AI and sometimes we see articles that talk about how AI will replace or destroy our jobs. We also see the occasional article talking about how AI will destroy humanity. In this article, I will not discuss an artificial general intelligence or an evil AI that wants to destroy humanity. I will focus on current AI, which is mostly based on the algorithms that can do predictions, and discuss how the economics of AI works and how it may affect business. I also want to mention that the content of this article is highly affected by (and this author highly recommends for further reading) Prediction Machines: The Simple Economics of Artificial Intelligence and Human Machine: Reimagining Work in the Age of AI.

Over the past few years, robotic or artificial intelligence technology has rapidly developed. As robots become smarter and gain new capabilities – thanks to advancements in machine learning, companies are increasingly jumping on the bandwagon. In fact, recent research by Narrative Science reveals 61% of businesses have implemented some form of AI. This trend is expected to continue and soon every modern company will employ some kind of artificial intelligence. The beauty of artificial intelligence is that this technology is extremely flexible and as such has many purposes.

Mobile apps have pioneered advancements in technology, the capability of software and analytics, and the use of Artificial Intelligence (AI). Apps are now more intuitive than ever before. With thousands entering the market, now is the time for companies to show how this technological partnership can help them shine. While the uses for apps vary, the vast majority of consumers rely on mobile applications to help them to complete different tasks. Whether that's keeping track of appointments or creating a monthly budget, AI's ability to learn and adapt holds the potential to create a unique user experience that changes with each individual.

In June, we found a trend in Apple's ($NASDAQ:AAPL) hiring data that indicated the company was getting serious about making its digital assistant, Siri, smarter. At the time, we saw a jump in open positions with the term "Siri" in their titles, which led us to predict that Apple was setting its sights on building a vast team of engineers and scientists to bring Siri up to par with other digital assistants from Google and Amazon. Just a few days after our story, Apple poached Google's former head of search and artificial intelligence to kick Siri's smarts into high gear. But Apple isn't done; it seems the company is continuing to build its team of artificial intelligence engineering teams to bring Siri's capabilities up to speed. Of the 167 open positions on September 24, the most common titles -- at least those that match perfectly -- are for Software Engineers, with 6 openings. Of course, software engineers could be working on anything, but almost as common are NLP Research Scientists.

The online dating app profile picture has become something of an art form, with everything from carefully lit shots to hugging tigers becoming commonplace. However, researchers have now revealed that men might be wasting their time. Experts from the University of Oxford Internet Institute commissioned by dating site eHarmony found that in fact, looking average could be the better option. Experts from the University of Oxford Internet Institute commissioned by dating site eHarmony found that in fact, looking average could be the better option for men. Researchers analysed ten years of data from the site, and found men who rate their looks as five or six out of 10 receive more messages than men who give themselves a 10 out of 10 rating.

DIRECT OPTIMIZA TION OF F-MEASURE FOR RETRIEV AL-BASED PERSONAL QUESTION ANSWERING Rasool Fakoor†, Amanjit Kainth, Siamak Shakeri, Christopher Winestock, Abdel-rahman Mohamed, Ruhi Sarikaya Amazon ABSTRACT Recent advances in spoken language technologies and the introduction of many customer facing products, have given rise to a wide customer reliance on smart personal assistants for many of their daily tasks. In this paper, we present a system to reduce users' cognitive load by extending personal assistants with long-term personal memory where users can store and retrieve by voice, arbitrary pieces of information. The problem is framed as a neural retrieval based question answering system where answers are selected from previously stored user memories. We propose to directly optimize the end-to-end retrieval performance, measured by the F1-score, using reinforcement learning, leading to better performance on our experimental test set(s). Index Terms-- Question Answering, Spoken information retrieval, Reinforcement Learning, Personal Assistants 1. INTRODUCTION Recent advances in speech recognition [1, 2], speech enhancement [3, 4], natural language understanding [5, 6], question answering [7, 8, 9], and dialogue systems [10, 11] have fueled the current surge in research and development for smart personal assistants [12] like Alexa, Siri, Google assistant, and Cortana, with many use cases around shopping, music, etc. In this paper we present a system for providing personal assistants a long term personal memory that enable users to store anything they want to remember by voice, and then later ask questions about it. An example use case is shown in Table 1. This system extends long-term memories of users and enables them to store and retrieve arbitrary pieces of information they are juggling in their minds.

Ignite At its Ignite conference in the US on Monday, Microsoft pitched Cortana as a corporate worker, as the software and cloud biz pushes companies to interact with technology via voice. Javier Soltero, the Microsoft corporate vice president who oversees Cortana, suggested that voice interaction has reached the same level of familiarity as interacting with mobile phones. Cortana developers can now build business-oriented skills, with the Cortana Skills Kit for Enterprise and if you are granted an invitation. If voice has arrived, passwords appear to be headed for the exit. The code biz revisited chairman Bill Gates's 2004 prediction that passwords are on their way out.

Strategy Analytics has just released its report on the Q2 shipments of smart speakers across the globe. The numbers revealed that over 50% of the speakers are either by Google or Amazon, with Google Home Mini grabbing the lion share with a 20% of the market. The numbers reveal that although the market is still heavily concentrated around the pioneers in the smart speaker world, users still prefer the cheaper and more compact device. That--s why Google Home Mini and Amazon Echo Dot are stomping over the third placed Amazon Echo and fifth placed Google Home. The Alibaba Tmall Genie completes the top five.

The cloud-computing industry is going through a gradual shift towards becoming an intelligent cloud. While compute, storage, and networking continue to be the revenue spinners for cloud vendors, it is machine learning that is becoming the focal point of the contemporary cloud. Here are five cloud services that are highly influenced by machine learning. Cognitive Computing aims to bring sensory capabilities to applications. It enables apps to see, listen, talk, and even make decisions. Based on natural language processing, visual recognition, face detection, emotion detection, video analytics, text to speech, speech to text, language translation, and sentiment analysis, Cognitive computing empowers developers with simple APIs.

According to the "Artificial Intelligence in Marketing Market by Offering (Hardware, Software, Services), Technology (Machine Learning, Context-Aware Computing, NLP, Computer Vision), Deployment Type, Application, End-User Industry, and Geography - Global Forecast to 2025", published by MarketsandMarkets, the market is expected to be valued at USD 6.46 Billion in 2018 and is likely to reach USD 40.09 Growth in the adoption of customer-centric marketing strategies, increase in demand for virtual assistants, and increased use of social media for advertising are the major factors driving the demand for AI-based marketing and sales solutions. Browse 67 tables and 59 figures spread through 200 pages and in-depth TOC on "Artificial Intelligence in Marketing Market - Global Forecast to 2025" Software holds a major share of the overall AI in marketing market owing to the developments in AI software and related software development kits. AI systems require different types of software, including application program interfaces, such as language, speech, vision, and sensor data, along with machine learning algorithms, to realize various applications for sales and marketing. Software platforms and solutions are available at high costs as there are limited number of experts that develop machine learning algorithms.