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SaraC

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  1. The increasing adoption of machine learning technologies, such as supervised learning, deep learning, and unsupervised learning, in various end-user industries, such as marketing, fintech, retail, cybersecurity, healthcare, and automotive, is driving the growth of machine learning technology in the AI (chipsets) market. https://www.prnewswire.com/news-releases/5926-bn-artificial-intelligence-chipsets-market---global-forecast-to-2025-300602676.html
  2. Since technical analysis focuses on volume and price analysis, it seems natural that ML and AI can help here. AI can learn from the patterns used here, and it can develop success algorithms that can change from time to time depending on the situation. https://www.finextra.com/blogposting/15067/impact-of-artificial-intelligence-and-machine-learning-on-trading-and-investing
  3. “Stocks are bought on expectations, not facts.” — Gerald M. Loeb As we decide to start trading it is important to ask ourselves: what does it take to become a successful trader? Trading tactics, psychology, money management and record keeping are four factors that determine the success of a trader. https://aix.trade/2018/02/22/master-trading-indicators/
  4. This is the future — a world where AI can build AI. Evolutionary algorithms are an example of the “living and breathing AI” — intelligent algorithms that can adapt with the times and think outside the box. https://venturebeat.com/2018/02/13/evolutionary-algorithms-are-the-living-breathing-ai-of-the-future/
  5. IDC forecasts that worldwide spending on AI hardware, software and services will jump to $58 billion by 2021, up from just $12 billion in 2017. Outside Silicon Valley, companies are dipping a tentative toe into AI. Surveys show that most companies plan to evaluate how artificial intelligence can make them better. Budgets could more than triple in the next few years. https://www.investors.com/news/technology/ai-in-business-future-of-artificial-intelligence/
  6. Applied AI is defined by Georgian Partners as “specialized uses of artificial narrow intelligence … used to power some of today’s most successful technology businesses” in ways such as process automation, advanced machine learning and smarter performance objectives. https://mobilebusinessinsights.com/2018/02/applied-artificial-intelligence-is-no-longer-an-advantage-its-a-necessity/
  7. ReportsnReports.com adds Artificial Intelligence (AI) Robots Market is forecast to reach $12.36 billion by 2023 from $3.49 billion in 2018 at a CAGR of 28.78% during (2018-2023) driven by the high adoption of robots for personal use such as companionship and entertainment; and support from governments worldwide to develop modern technologies; while North America to hold the second-largest share of the market in 2018. https://www.prnewswire.com/news-releases/artificial-intelligence-ai-robots-market-to-grow-at-2878-cagr-to-2023-674026093.html
  8. The first wave of artificial intelligence was targeted at helping companies to automate data collection. The second wave is focused on extracting meaningful value from data, through assessing data patterns. http://www.digitaljournal.com/business/ai-is-the-key-to-unlocking-business-data/article/513356
  9. Technology is changing rapidly: autonomous vehicles, connected devices, digital transformation, the Internet of Things (IoT), machine learning, artificial intelligence (AI), automation. The list goes on. And it has only begun. Over the last decade, a tremendous amount of effort has gone into optimizing how algorithms train. As a result, AI has made impressive advances, supported by supervised deep learning that trains deep neural networks to perform narrow, single-domain tasks. Although with supervised learning we tell the algorithm the correct answer (the label) as it is exposed to many examples (big data), it is powerful and can create systems with superhuman capabilities. https://blogs.sas.com/content/sascom/2018/01/18/two-tech-trends-shaping-2018-beyond/?utm_source=FBPAGE&utm_medium=social-sprinklr&utm_content=1293417621
  10. AI has the potential to help businesses do many things better, faster, cheaper and with fewer errors than any manual process. When combined with advanced analytics, it can also deliver insight into what customers are doing today and what they are likely to do tomorrow – turning reams of data into actionable intelligence that can be applied to improve business processes. Customers want products and services specifically suited to their requirements that help them achieve what they want to accomplish. Implementing AI and analytics to become more customer-centric will be key to ensuring technological innovation in the industry drives results – great user experiences and happy customers. https://www.globalbankingandfinance.com/artificial-intelligence-the-next-digital-frontier-for-customer-experience-in-financial-services/
  11. Time has come when Artificial Intelligence will be more closer to you (best of all times) and will be part of every day life for almost everything. More recently, however, AI has broken away from the hypothetical and into real-world business solutions. Year 2018 will be known as year of Artificial Intelligence and Intelligence Augmentation for sure (in my personal opinion). AI usage in FinTech will augment FinTech Intelligence’s all time best. https://www.finextra.com/blogposting/14905/2018-year-of-intelligence---artificial-and-augmentation
  12. • Cryptocurrencies could go on a bull run greater than last year and pass the trillion-dollar value mark, Jamie Burke, CEO at Outlier Ventures said. • Technological advancements and new investor products could push bitcoin to $50,000 in 2018, Thomas Glucksmann of Gatecoin told CNBC. • Investors may focus on so-called "utility tokens" this year which are digital coins that can power blockchain technologies, according to one expert. https://www.cnbc.com/2018/02/07/bitcoin-price-could-hit-50000-this-year-experts-say.html
  13. AI is something that has been attracting companies for decades. Lately, the public interest in this field has grown to unprecedented levels. Numerous leading companies and tech giants are investing big on AI and its subfields like Machine Learning, Image Processing and Computer Vision. http://www.oodlestechnologies.com/blogs/5-AI-Trends-That-Will-Dominate-The-Market-In-2018
  14. How will AI change strategy? That’s the single most common question the three of us are asked from corporate executives, and it’s not trivial to answer. AI is fundamentally a prediction technology. As advances in AI make prediction cheaper, economic theory dictates that we’ll use prediction more frequently and widely, and the value of complements to prediction – like human judgment – will rise. But what does all this mean for strategy? http://bit.ly/2E21uCG
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