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Access to information is vital to the pace of growth of businesses and organizations and the flexibility with which they respond to imperatives. Information technology has made this access easier. While earlier, computers were merely an enabler of work which could be done manually, today, IT has moved beyond MS Office and Email. Enterprise Resource Systems, which were simple repositories of information, now brandish AI-enhanced smart decision-making capabilities based on automated data discovery, machine learning and Big Data analytics.Automation, robotics, digital interfaces and IoT convergence have considerably enhanced human and organizational capabilities. Given below is a quick look at the way various technologies have impacted the IT worker’s landscape in 2018.

New headwinds in business practice have put Artificial Intelligence at the very centre of business strategy. Industry leaders such as Google and Microsoft started the trend towards a priority AI strategy, and other major corporates followed suit quickly thereafter. Today, organisations are displaying a greater willingness to use AI and related instruments such as machine learning to automate operations, reduce administrative overhead, and systematically collate and organise data. Interpreting vast amounts of information is crucial in this age of big data, and AI has demonstrated itself to be a highly efficient work tool. AI has often been blamed for job losses and cutbacks but a number of business entities have realised the smart savings and precision that AI adds to a human workforce – acting as an enabler rather than a replacement.

Employees too, need to learn how to understand and work with AI in all its application forms as part of their skill development regimen for any job role in the organization if they desire to increase productivity.The popularity of smart sensors and emergent data analytics is projected to deliver further advancements to the factory tomorrow. Greater use of automation in processes monitored by flat knitting machine Manufacturers AI, and cutting-edge robotics, along with IoT connectivity is likely to play a major role in the schemes of Industry 4.0. Alternatively known as the Fourth Industrial Revolution, Industry 4.0 is a blueprint for a more connected world in which machines carry out routine tasks. Pioneering businesses such as Amazon, have taken tangible steps to implement this in their automated warehouses. A wide spectrum of industry sectors has been experimentally using blockchain technology to establish trust networks, inculcate transparency, and reduce conflicts and غير مجاز مي باشدts.

Notwithstanding controversies and debate, cryptocurrencies powered by blockchain remain popular in the public imagination. Increasingly, commercial businesses are shedding resistance to cryptocurrency transactions, from Bitcoin to Ethereum. Industrial applications will inevitably find new avenues, covering the prevalent financial uses along with innovative answers to energy, trade, marketing, healthcare, security and several other extant problems in the social economy.The materialization of intelligent data discovery capabilities, machine learning, and the automation of the entire analytics workflow continues to enable organizations to deal with massive amounts of information. Intelligent data discovery capabilities are singularly driving progress in how we process unstructured and dark data. This data can be used by organizations to enable them to predict market developments and provide increased depth in prognosticative decision making.

Prescriptive analytics goes beyond knowledge of facts, proceeding toward recommended actions on the basis of prior outcomes. These systems precisely recommend specific courses of action to achieve measurable objectives.As new technologies and new business practices transform economies, the lines between different industry segments are disappearing as convergence takes on a literal meaning. The amalgamation of distinct industries opens up huge opportunities for organizations to evolve, offering new product portfolios and services to their customers.

Oh dear, poor Merlyn has come under a great deal of flak after England were routed by India in the first ODI. But frankly, what can a hapless, inanimate bowling machine do if the skill of batsmen against wrist spin itself is so dubious.A bowling machine is a wonderful contraption, but its usefulness is secondary to intrinsic ability and experience in the middle. No amount of practice in the nets against a bowling machine is a substitute to the technique and intelligence required during match play.England’s batsmen have been at sixes and sevens, unable to read India’s wrist spinners — Kuldeep Yadav particularly, and Yuzvendra Chahal — and have been badly exposed.

As the T20 and ODI series has progressed, they have approached these bowlers with hope and prayer, rather than conviction: Largely because they’ve been trying to read the spinners off the pitch rather than just before or when the ball is bowled, as most successful batsmen through the ages have shown.This becomes a serious limitation against bowlers who can deliver from back-of-the-hand. Fathoming a wrist spinner is never easy. It requires a deep understanding of the skills and repertoire of the bowler who can get the ball to turn either way with virtually the same action.Master batsman Viv Richards has spoken of his struggles against B.S. Chandrashekhar in the 1970s, and the time it took for him to come to terms with the unorthodox leg spinner.Indeed, even at the height of his prowess, Richards confessed that he often read Chandra wrongly. Chandrashekhar was a freak, on his day impossible to bat against.

But if one of the greatest batsmen in the history of cricket can be troubled by wrist spin, imagine the plight of lesser mortals! And the problems grow manifold if batsmen have not been exposed enough to this kind of bowling, as is the case with the current crop of English players.Wrist spin, which seemed a dead art in the 1980s, has seen a revival in the modern era, initially through Abdul Qadir, and in his wake Shane Warne, Anil Kumble, Stuart McGill, Mushtaq Ahmed all of who enjoyed successful international careers.Inspired by these bowlers, wrist-spinners abound today. Because they can be match-winners in every format, they are in huge demand.But success is not guaranteed.This is not dependent only on the inadequacies of batsmen, but the ability of the bowlers concerned.Wrist spin is a difficult skill and unless the bowler has both guile and control, it can be expensive. Apart from strong fingers, wrist, arm and shoulders, they need a sharp mind to stay ahead of the batsman, and a big heart to take punishment.

All the successful orthodox wrist-spin bowlers mentioned above – or going back earlier in history to the likes of Charlie Grimmett, Bill O’Reilly — had superb control, were always attacking, and had the ability to outthink batsmen.Essentially, wrist-spinners must be wicket-takers. They can’t be overly erratic or defensive. They are not stock bowlers. Their usefulness is not defined by how they keep batsmen quiet, rather how quickly they dismiss him. They must be risk takers to be match-winners.The crux, of course, is that that even wrist-spinners have to keep improving to remain relevant. The time for this can be extremely short these days given the number of matches being played across formats in which they can be found out and become ineffective.Brad Hogg, who like Kuldeep Yadav bowled left-arm with the dreaded chinaman in his armoury, had a brief career simply because glove machine Manufacturers he did not evolve.

The mystery in his bowling vanished quickly and he lost his place. Similarly, Indian leg spinners Amit Mishra and Piyush Chawla.How Kuldeep and Chahal progress from here remains to be seen. Interestingly, their current form and success has not only had the English batsmen bamboozled, but also created a dilemma whether they should not be in the squad for the five-Test series against England.D12

If a hacker were to break into the database of all China glove knitting machine for sale patient and payment records, he/she is basically the owner of invaluable data that can be used or misused at will.The easiest and most popular way to make money from all of this data is to offer it back to the institution -- for a hefty price. In IT security parlance, this is called Ransomware, a vulnerability whose statistics are alarming.A recent survey by endpoint and network security solutions provider, Sophos, found that 2 of 3 Indian businesses have been the target of ransomware -- the highest percentage of any nation in the world.

And healthcare is the sector most targeted -- 76 percent have received Ransomware threats recently.One in two devices in any organization have been infected with Ransomware and other Net threats. A separate study by McAfee last week came to a similar conclusion: Health care in India experienced 211% increase in disclosed security incidents in 2017. One health record typically attracts a ransom of (Rs 350)Every couple of months, a new vulnerability becomes apparent. Worms like WannaCry and NotPetya become popular and organizations scurry to find patches. But with something like Ransomware, one cannot make any predictions on possible date and time of occurrence. In fact, Sophos claims that a substantial number companies have been victims of Ransomware attacks more than once in a span of a few months.In order to counter this problem, Sophos has found a solution which is in line with the thought process of hackers. The company, in its latest security product, Intercept X, has included a machine learning capability that continually monitors threats that their customers encounter, and becomes more intelligent.

In other words, theres a robot of sorts that learns every day about new kinds of threats, so it can predict the occurrence of one or at least decipher one as soon as it hits the network.The good news is India, along with Canada and Mexico has the highest levels of machine learning technology and one third of respondents to the survey already use predictive threat technologies such as deep learning and machine learning.So the cyber baddies are out there -- eyeing your data. But net security robocops are pushing back -- for now.As a teenager working for his dad’s construction business, Noah Ready-Campbell dreamed that robots could take over the dirty, tedious parts of his job, such as digging and leveling soil for building projects. Now the former Google engineer is turning that dream into a reality with Built Robotics, a startup that’s developing technology to allow bulldozers, excavators and other construction vehicles to operate themselves.