Linz (Austria) (AFP) - Can artificial intelligence turn out symphonies to match one of the greats of classical music? That was the question posed by one unusual orchestra performance in the Austrian city of Linz on Friday, in which Gustav Mahler's unfinished Symphony No.10 was played -- immediately followed by six minutes of "Mahleresque" music written by software. The project's creator says that the two are clearly distinguishable but not everyone in the audience agreed. "I couldn't really feel the difference... I believe it was really well done," Maria Jose Sanchez Varela, 34, a science and philosophy researcher from Mexico, told AFP.

New York-registered startup Gemeye is an example of just how the fourth industrial revolution has digitised traditional sectors like jewellery. The world is going digital and so is every industry, and technologies like artificial intelligence (AI), machine learning (ML) and internet of things (IoT) rapidly changing the way we live, eat, and, most importantly, shop. Ecommerce giants including Amazon and Flipkart have made shopping so easy that you can buy anything your heart desires by not even stepping out of your home. And this ecommerce breeze is slowing reaching hitherto traditional, offline sectors like high-end jewellery as well. Gemeye is helping traditional family jewellers launch their very own online stores and list their products with ecommerce giants.

There is a new race in Silicon Valley involving Artificial Intelligence and no it's not HealthTech, FinTech, Voice Commerce or involve Google, Facebook or Microsoft... this race involves the brain and more specifically brain-computer interfaces. This race also involves technology royalty, the US government, billion dollar defence companies, a big connection to PayPal and years of medical research to better understand the human brain and implant devices that could make a consumer brain-computer interface a reality. The race is called "Neural implants, merging the human brain with AI" So what exactly are neural implants? Brain implants, often referred to as neural implants, are technological devices that connect directly to a biological subject's brain – usually placed on the surface of the brain, or attached to the brain's cortex. A common purpose of modern brain implants and the focus of much current research is establishing a biomedical prosthesis circumventing areas in the brain that have become dysfunctional after a stroke or other head injuries.[1]

According to a recent survey on enterprise AIOps adoption, 67% of enterprise IT organizations in the US have experimented with artificial intelligence and machine learning for data management and incident remediation. What's more, Gartner expects AI to create more jobs than it replaces by 2020. AI is moving fast and enterprises need talent today, but not just any talent. What once was a shortage of coding and software engineering expertise has now translated into an overall shortage of skills in artificial intelligence and algorithmic engineering. Skills gaps are cited as being among the biggest hurdles to AIOps adoption and implementation, and a recent EY survey of 200 senior leaders found that 56% see talent shortages as the single biggest barrier to implementing AI into business operations in 2018.

We've entered an era in which marketers are being bombarded by volumes of data about consumer preferences. In theory, all of this information should make grouping users and creating relevant content easier, but that's not always the case. Generally, the more data added to a marketer's workflow, the more time required to make sense of the information and take action. Machine learning is a subset of artificial intelligence. The technology equips computers with the capacity to analyze and interpret data to proffer accurate predictions without the need for explicit programming.

The news is filled with stories of how artificial intelligence (AI) will reshape our lives. Over the last forty years, digital computers have transformed every business. We now take word processing, spreadsheets, databases, computer control, CRM, ERP, the internet, cloud computing, and other IT business capabilities for granted. Artificial intelligence solves a whole new set of business problems that were either extremely difficult or impossible for traditional digital computers. Businesses will use AI to create new value, increase efficiency, optimize operations, and boost customer service.

Note: This blog post was authored by Aaron Baughman with Stephen Hammer, Eythan Holladay, Eduardo Morales and Gary Reiss. Tennis play at the US Open consists of 254 matches in the men's and women's singles events totaling tens of thousands of points. During the tournament's two weeks, many matches are played in parallel, and it's virtually impossible for any tennis fan, or the editorial team at the United States Tennis Association (USTA), to capture any sizable percentage of the best points. To help solve this challenge, IBM built an AI system that clips and creates candidate highlight videos and assigns a fair excitement score, all within two minutes of the end of each match. Every highlight is ranked so that tennis fans and video editors at the USTA and its broadcast partners can see the most exciting points of the tournament, while minimizing the influence of player gestures, match analytic score, player rank, player age and crowd size.

Containerize your Apps with Docker and Kubernetes is an excellent free book from Gabriel N. Schenker In this post, I explain the significance of deploying apps with Docker and Kubernetes and also some of my thinking at the University of Oxford artificial intelligence cloud and edge impleme... course. Chapter 1: What Are Containers and Why Should I Use Them? Containers are the best way to implement a DevOps architecture. This book explains the end-to-end deployment of containers for an Azure environment – including container orchestration through Kubernetes. The book explains the software supply chain and the friction within it – and then presents containers as a means to reduce this friction and add enterprise-grade security on top of it.

Hyderabad, Sep 8: Dr Mithin Aachi, Sr Ortho & Joint Replacement Surgeon, Apollo Hospitals, Secunderabad on Sunday said that'Robot Arm' assisted navigated knee replacement and Artificial Intelligence Machine Learning, definitely would dominate in future for patient care, there would be an exponential increase in their usage in the years to come. Talking to media on the occasion of 5th edition of Arthroplasty Arthrocopy Summit, organized by Apollo Hospitals under the aegis of Telangana Orthopaedic Surgeon's Association (TOSA) and Twin Cities Orthopaedic Society (TCOS), here, Dr Aachi along with Dr N Somashekar Reddy, Sr Ortho & Joint Replacement Surgeon, Apollo Hospitals said that a Robot doesn't do surgery by itself but it helps the surgeon plan, execute and achieve a better surgical result than he (doctor) would have by human effort alone. Hence Robot surgery in less pain, better outcomes and longer survival rates of joint replacement surgery, he said. Explaining further on Robot surgery, Dr Aachi said usually for a Robot assisted surgery patient undergoes CT scan of the knee to correctly update the surgeon about the deformity and the thickness of bone cuts required and the implant sizes to be placed. This is enhanced planning which gives the surgeon an idea of the type of bone cuts required and the size of implants which will correctly match that patient on an individual level.

The annual America's safest drivable cities list has been published, let's start thinking about what the list will be like once driverless cars emerge. The annual ranking of the top cities in the United States for having the "safest" drivers has been recently published by Allstate Insurance, the chronicler of the America's Best Driver's Report. I'm sure that you want to know which cities have the best drivers and which ones have the worst. Of the 200 cities listed, the "best" or topmost five in terms of being at the top of the list were: Of the 200 cities listed, the "worst" in terms of ending at the final pole positions of 196 through 200 were: Some people glance at the list to see where their particular city has landed. Some use the list to be extra cautious when driving in the cities that are toward the latter portion of the list.