Machine Learning in Communication Market : Quantitative Machine Learning in Communication Market Analysis, Current and Future Trends, 2019-2033 – Instant Tech Market News

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With bottom-up and top-down approaches, the report predicts the viewpoint of various domestic vendors in the whole market and offers the market size of the Machine Learning in Communication market. The analysts of the report have performed in-depth primary and secondary research to analyze the key players and their market share. Further, different trusted sources were roped in to gather numbers, subdivisions, revenue and shares. The research study encompasses fundamental points of the global Machine Learning in Communication market, from future prospects to the competitive scenario, extensively. The DROT and Porter's Five Forces analyses provides a deep explanation of the factors affecting the growth of Machine Learning in Communication market.


The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place

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This is a carefully curated compendium of articles & tutorials covering all things AI, Data Science & Machine Learning for the beginner to advanced practitioner. I will be periodically updating this document with popular topics from time to time. My hope is that you find something of use and/or the content will generate ideas for you to pursue.


How To: Make Your Own AI

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Please join us this evening as we discuss how to make your own AI and AI apps. Following is a brief agenda for the evening: 6:00 - 6:30 PM: Doors open for networking and pizza 6:30 - 7:00 PM: Presentation by Suren and Mohamed 7:00 - 7:30 PM: Presentation by Cody 7:30 - 8:00 PM - Q&A and Networking Forward-thinking businesses are using AI to gain greater insights, make more accurate predictions and use AI to create new and compelling products and services. Across industries, AI is having a positive impact including drug discovery in pharmaceutical to cure diseases, sepsis detection in healthcare to save lives, supply chain transportation optimization to take costs out in manufacturing, fraud detection in banking to save money, subscriber churn predictions in telecoms to retain customers and personalized policies in insurance to delight consumers. Every industry stands to benefit from AI in their business. In this meetup, we will discuss how domain experts and advanced data scientists can make their own AI by writing their own recipes and seamlessly extending H2O Driverless AI with their favorite tools from the rich ecosystem of open-source data science and machine learning libraries.


Seeing Further Down the Visual Cloud Road - IT Peer Network

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Almost three years ago, Carnegie Mellon University Prof. Dave Andersen and I announced the Intel Science and Technology Center for Visual Cloud Systems (ISTC-VCS) at the 2016 NAB Show. Along with Prof. Kayvon Fatahalian at Stanford, Dave has led the center and collaborated closely with other academic and Intel Labs researchers to push the boundaries in visual cloud systems. We set out to study and find solutions for some of the key problems with gathering, storing and analyzing video data in large scale distributed environments. With the completion of the center now drawing near, it's time to take stock of the results and to talk of work yet to be done. The center's approach has been to bring together systems researchers and computer vision, AI and graphics researchers to create prototype systems that allow investigation of these topics.


Powerful antibiotic discovered using machine learning for first time

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A powerful antibiotic that kills some of the most dangerous drug-resistant bacteria in the world has been discovered using artificial intelligence. The drug works in a different way to existing antibacterials and is the first of its kind to be found by setting AI loose on vast digital libraries of pharmaceutical compounds. Tests showed that the drug wiped out a range of antibiotic-resistant strains of bacteria, including Acinetobacter baumannii and Enterobacteriaceae, two of the three high-priority pathogens that the World Health Organization ranks as "critical" for new antibiotics to target. "In terms of antibiotic discovery, this is absolutely a first," said Regina Barzilay, a senior researcher on the project and specialist in machine learning at Massachusetts Institute of Technology (MIT). "I think this is one of the more powerful antibiotics that has been discovered to date," added James Collins, a bioengineer on the team at MIT. "It has remarkable activity against a broad range of antibiotic-resistant pathogens."


Positive impact of AI on employee experience

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Abhijeet, the HR head has deployed artificial intelligence in his organization with the objective of taking care of his employees and to stay ahead of the competition. He has a vision in improving overall efficiency of the organization that leads to employee productive growth. He also wants the AI to help him get minute details of HR processes that can capture his attention better for improving the scope of productivity wherever possible. Let's find out how AI can prove to be beneficial for his team: AI helps to facilitate data on which teams can work better together or which employees can be considered for taking them on the lead for a particular project. This will, in turn, have a massive impact on the operational efficiency and quality of work amongst your team.


Ranked: The 100 Most Spoken Languages Around the World

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Even though you're reading this article in English, there's a good chance it might not be your mother tongue. Of the billion-strong English speakers in the world, only 33% consider it their native language. The popularity of a language depends greatly on utility and geographic location. Additionally, how we measure the spread of world languages can vary greatly depending on whether you look at total speakers or native speakers. Today's detailed visualization from WordTips illustrates the 100 most spoken languages in the world, the number of native speakers for each language, and the origin tree that each language has branched out from.


NST Leader: Artificial Intelligence in court

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Not as a defendant -- it would have been a novel case had it been so -- but as an aid to help the magistrate with sentencing. Trends elsewhere suggest something more. But if a machine should one day sit at the bench presiding over a court battle between men and men, then it will be a surrender most ominous. There are at least two reasons why we should not defer to machines. It is true that AI can do many complicated things.


5 things to know about getting started with AI/ML

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Alan Gibson, VP EMEA at Alteryx explains that these technologies have real business-altering potential and that's why Gartner's Enter the Age of Analytics report predicts that by 2023, AI and deep-learning techniques will be the two most common approaches for new applications of data science. But despite the promise, few companies have been able to successfully implement and deploy this technology as part of their overall data and analytics strategy--according to Gartner, 46 percent of CIOs have developed plans to deploy AI but just 4 percent have made the concept a reality. The truth is that it will take years before many organisations realise the true potential of AI and ML, but it is never too early to lay the groundwork now for an AI-driven future. In fact, if an organisation is not already thinking about what an AI strategy looks like, its competition is likely one step ahead. There's no time to waste, so here are five important points to consider when getting started with AI and ML.