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Stop worrying about AI taking over the world -- it won't

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Should we be afraid of artificial intelligence? For me, this is a simple question with an even simpler, two letter answer: no. But not everyone agrees – many people, including the late physicist Stephen Hawking, have raised concerns that the rise of powerful AI systems could spell the end for humanity. Clearly, your view on whether AI will take over the world will depend on whether you think it can develop intelligent behavior surpassing that of humans – something referred to as "super intelligence". So let's take a look at how likely this is, and why there is much concern about the future of AI.


2019 Marketing Trends

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Look for smart organizations in 2019 to create a dedicated marketing role, such as director of marketing data, to establish and drive the human and machine or system connections across their company. In addition to working with technology vendors and internal teams on data integration, this new role will create processes, rules and procedures to ensure that critical data is collected and integrated into a customer data platform (CDP). Since the beginning of direct and database marketing, data has been foundational for successful marketers, enabling advanced customer segmentation, deep personalization and relevant messaging to customers and prospects. The growth of AI-based marketing tools, however, has taken data management and data integration to a level of mission-critical stature for marketing organizations. In fact, 61 percent of company executives surveyed by MemSQL indicated that machine learning and AI are their companies' most significant data initiative for 2019.


New AI computer vision system mimics how humans visualize and identify objects

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The system is an advance in a type of technology called "computer vision," which enables computers to read and identify visual images. It is an important step toward general artificial intelligence systems -- computers that learn on their own, are intuitive, make decisions based on reasoning and interact with humans in a more human-like way. Although current AI computer vision systems are increasingly powerful and capable, they are task-specific, meaning their ability to identify what they see is limited by how much they have been trained and programmed by humans. Even today's best computer vision systems cannot create a full picture of an object after seeing only certain parts of it -- and the systems can be fooled by viewing the object in an unfamiliar setting. Engineers are aiming to make computer systems with those abilities -- just like humans can understand that they are looking at a dog, even if the animal is hiding behind a chair and only the paws and tail are visible.


Microsoft to train 5 lakh Indian youths in AI

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In an attempt to skill Indian youths in Artificial Intelligence, Microsoft India has taken an initiative to train five lakh youths. The company aims to train five lakh youths in AI across the country and would set up AI labs in 10 universities. Additionally, the company plans to upskill 10,000 developers in emerging technology areas like AI, IoT, etc. Microsoft also started Intelligent Cloud Hub Program to equip research and higher education institutions with AI infrastructure, build curriculum and help both faculty and students to build their skills and expertise in cloud computing, data sciences, AI and IoT. Anant Maheshwari, President, Microsoft India shares, "We believe AI will enable Indian businesses and more for India's progress, especially in education, skilling, healthcare, and agriculture. Microsoft also believes that it is imperative to build higher awareness and capabilities on security, privacy, trust, and accountability. The power of AI is just beginning to be realized and can be a game-changer for India."


Microsoft to launch AI & IoT Insider Lab in Shanghai - Khmer Times

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SHANGHAI (Xinhua) – US tech giant Microsoft yesterday signed a memorandum of strategic cooperation to locate its new artificial intelligence (AI) and Internet of Things (IoT) Insider Lab, the first of its kind in Asian-Pacific Region, in Shanghai. The memorandum was signed between the company and Shanghai's Pudong New Area. The lab is expected to open in April. It will be Microsoft's third and largest AI & IoT Insider Lab in the world, after the company set up the first two in Seattle and Munich. The lab is set to enhance deep integration of AI and IoT, and help digital transformation across industries including manufacturing, retail, healthcare, and the public sector.


Global Artificial Intelligence (AI) Industry

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Germany Market Analysis Table 35: German Recent Past, Current & Future Analysis for Artificial Intelligence Analyzed with Annual Revenue Figures in US$ Million for Years 2015 through 2024 (includes corresponding Graph/Chart) 9.4.3 Italy Market Analysis Table 36: Italian Recent Past, Current & Future Analysis for Artificial Intelligence Analyzed with Annual Revenue Figures in US$ Million for Years 2015 through 2024 (includes corresponding Graph/Chart) 9.4.4


How Amazon, Microsoft, Google Are Using AI Against Hackers

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Amazon, Microsoft and Google are the forerunners among tech giants to leverage artificial intelligence to tackle cybersecurity threats and keep hackers at bay, who often pose as a real user to gain crucial data. Speaking to an international news agency, the chief security officers from each of the company unanimously agreed that AI and ML plays a crucial role in protecting their company'' multi-million dollar infrastructure by crunching large pool of data on a daily basis. While acknowledging that it is impossible to stop every intruder, Stephen Schmidt, Amazon CISO, maintained that the new tech remains largely beneficial for companies like that of Amazon which has to ensure online safety of millions of people across the world. Speaking about the ability of AI and ML in identifying hacker he said, "We will see an improved ability to identify threats earlier in the attack cycle and thereby reduce the total amount of damage and more quickly restore systems to a desirable state." Speaking on the large set of data that needs to be processed for monitoring unauthorised activities, Mark Risher, product management director at Google said,"The amount of data we need to look at to make sure whether this is you or an impostor keeps growing at a rate that is too large for humans to write rules one by one."


Data Lit (Music Video)

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This lyrics of this music video are actually educational and they serve as an introductory lecture on AI. This video also acts as a teaser trailer for my upcoming, free 3 month Data Science course for beginners titled "Data Lit" at School of AI (Jan 28 start date). That's what keeps me going. Sign up for the "Data Lit" course at School of AI: https://www.theschool.ai/courses/data... Want more education? Shoutout to my Wizards, this ones for you It started with hello world hello engineers And now we're, world-wide yo and this the premiere So u gotta sit down tight and let me teach you a lesson I call it intro to AI, this is my confession Lesson one starts simple gotta get that data Don't even mess with the thetas until we get that data And if we open the file, it might look like a haze, But if we keep it algorithmic we can set it ablaze Hello!


A deep learning-based method to detect cyberbullying on Twitter

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Researchers at King Saud University, in Saudi Arabia, have developed a new approach to detect cyberbullying on Twitter using deep learning called OCDD. In contrast with other deep-learning approaches, which extract features from tweets and feed them to a classifier, their method represents a tweet as a set of word vectors. In recent years, cyberbullying on social media has become a huge and widely discussed issue. Cyberbullying entails the use of online communication channels to bully other users by sending intimidating, threatening or abusive messages. This can have psychological and sometimes life-threatening consequences for the victims.


Automated Dashboard for Classification Neural Network in R

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In this article, you learn how to make Automated Dashboard for Classification Neural Network in R. First you need to install the rmarkdown package into your R library. Assuming that you installed the rmarkdown, next you create a new rmarkdown script in R. The result of the above coding are published with RPubs here.