Duncan Stewart, the director of the very narrow field of machine learning said that - “Machine Learning is the big one, not AI.AI is a very broad field.” Deloitte predicts that there would be a significant progress in mobile device usage, augmented reality and sophisticated chips.However, the most dominant tech trend of all this will be machine learning when programs will predict things using large volume of data without having to be explicitly programmed.Deloitte predicts that the business use of machine learning would double in 2018 when compared to the previous year and again it is likely to double by 2020. This exponential growth in the use of machine learning is already worth tens of billions of dollars in size.
(Source : https://www.cnbc.com/2018/04/10/machine-learning-is-the-big-one-deloitte-expert.html )
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Charlottesville’s Champion Brewing company recently partnered with Metis Machine to brew their new ML IPA—a computer’s vision of what should essentially be the ideal IPA. Champion provided Metis with the parameters on which IPA’s are decided at the Great American Beer Festival (SRM, ABV, IBU) and the range was matched with the 10 worst selling IPA’s at a local retailer and 10 best-selling IPA’s nationally. Champion brewing company is the first one to use machine learning for generating a beer recipe.
(Source : http://www.foodandwine.com/news/champion-brewing-ipa-machine-learning )
AI can be used to swap faces in photos and videos. However, many people are making misuse of this tool by face-swapping people into pornographic videos. The team at Technical University of Munich have developed a machine learning algorithm which can identify forged videos as soon as they are posted online.XceptionNet machine learning algorithm has been trained with a large set of face swaps created from the largest database of these kinds of images available.XceptionNet outperforms other rival techniques in identifying and detecting fake videos and photos thereby enhancing the quality of the forgeries.
(Source : https://www.engadget.com/2018/04/11/machine-learning-face-swaps-xceptionnet/ )
The $60 billion company DHL employees more than 500,000 employees across the globe and is famous for its international express business.With great expertise in supply chain services, e-commerce, and global air and ocean freight forwarding services, DHL also has its trend research business that takes a look on what’s down the lane in the next 5 to 10 years in social, business, and technology like automation, IoT, augmented reality and robotics.A report released by IBM and DHL last week showed that companies invested $26 billion to $39 billion in Artificial Intelligence technology in 2017 but in 2017 only 20% of the companies said that they were adopters of AI , 31% said they were partial adopters and close to 40% said they were contemplators.However, in the logistics industry there is huge scope for leveraging AI and machine learning as there is lots of operational data.DHL is using AI, machine learning, and deep learning in various ways to become more predictive, proactive, autonomous and striving to make its services more personal rather than making them standardized. DHL is using machine learning to identify problems that can show up in a company’s supply chain, to make predictions 3 months in advance on the direction of how global trade will trend, for determining delays in air freight, and autonomous vehicles.
(Source : https://www.nextplatform.com/2018/04/18/dhl-gets-logical-and-logistical-about-machine-learning/ )
SAP and The Economist Intelligence survey finds that the impact of machine learning algorithms on business processes is increasing at a rapid pace. 48% of the companies say that they have already benefited from machine learning with increased profitability being the major benefit and they also expect 6% revenue growth in the next two years. The survey finds that the major reason companies are investing in AI and machine learning is increased revenue vs. cutting costs. Companies that are data-driven are the early adopters of AI and machine learning to drive competitive advantage.Companies that leverage machine learning for superior customer experience are likely to dominate their industries.
(Source -https://www.itbusinessedge.com/blogs/it-unmasked/sap-survey-sees-machine-learning-algorithms-having-a-business-impact.html )
According to the Machine Learning - Global Market to 2022 report , the industry is expected to see a compound annual growth rate of 43.6% which could be worth $8.8 billion through 2022.The major players who will lead the machine learning market include Amazon, Alphabet, Fair Isaac, Intel, IBM , Microsoft, Oracle, and Hewlett Packard.Below are some of the key highlights from the research report -
Michael Sullivan, BCC Research senior editor, information technology said - “The market for machine learning is growing at a significant rate and driven largely by factors such as increasing computing power, increasing availability of big data for learning and prediction, improvements in machine learning algorithms and increasing usage of the cloud for data storage.However, factors such as shortage of skilled labor and usage of machine learning by hackers we expect to restrain the market growth for machine learning.”
According to the popular job portal Indeed, the demand for AI and machine learning skills has doubled in the last 3 years and the number of job postings have increased by 119% as a share of all other job postings.
(Source - https://analyticsindiamag.com/top-countries-hiring-most-number-of-artificial-intelligence-machine-learning-experts/ )
Fraud Detection is a popular machine learning use case that has garnered the attention of various organizations.San-Francisco based payment technology company Stripe believes that it has the technology required to detect fraud.Stripe has been gaining popularity in the market for having blocked $4 billion worth fraudulent transactions. Stripe’s underlying technology does not require merchants to review each transaction and write rules but instead uses machine learning for heavy -lifting. The machine learning algorithm takes into account multiple tell-tale signs to detect fraud such as buying an item in multiple sizes, pasting credit card details instead of typing them and the number of different credit card used by people over a period of time.
(Source - https://www.computerweekly.com/blog/Eyes-on-APAC/How-machine-learning-is-used-to-detect-fraud )