software testing news


What can machine learning do for testing? - Software Testing News

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With the move to DevOps and high-paced development, there is a greater and more frequent need to specify test environments to ensure that systems are working efficiently; yet the ability of enterprise to model and manage capacity accurately is immature. Performance testers are theoretically well-placed to help but they may be naturally cautious about modelling capacity since testing functions can run up significant annual costs in capacity usage alone. You'll have heard plenty about AI (artificial intelligence) and ML (machine learning) of late, and with good reason – delicate, complex and downright costly technology and tools are rapidly maturing into usable toolsets in a wide range of verticals. Analyst firms predict huge markets for AI and ML, indeed the number of enterprises implementing artificial intelligence (AI) grew 270 percent in the past four years and tripled in the past year, according to industry analyst Gartner's 2019 CIO Survey. Results showed that organisations across all industries use AI in a variety of applications but on the downside struggle with acute talent shortages.


AI can bridge software automation gaps - Software Testing News

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Today's continuous integration bottlenecks need AI for code The impact artificial intelligence could have on software development is ripe for speculation. Will AI help create prototypes in days, instead of months or years? Will it teach human developers how to code better? AI research is broad and code is flexible, so it's hard to imagine what software development will look like when intelligent programs can help us interact with code. What many developers and tech managers don't realise is that AI has made huge leaps in its usefulness for development teams in the last several years.


From helping humans to evolving firms, ML's impact on the modern age is huge - Software Testing News

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With enterprises in the race to embrace digital change, other tech companies are doing what they can to make this happen. AudioEye, a digital accessibility firm, is no exception to this. They have embraced growing changes, like machine learning, to accelerate accessibility and help organisations achieve digital inclusion standards. Sean Bradley, CoFounder at AudioEye talks of why machine learning is so vital to today's evolving tech sector. Beginning in 2015/2016, businesses started reaching out to us having found themselves on the receiving end of website accessibility claims, despite having neither a) any control over their source code or b) any understanding of where to begin in order to address the claims.


Is AI all that it's cracked up to be for today's testing? - Software Testing News

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Testing in the Third Industrial Revolution: Is AI all that it's cracked up to be for today's testing? This article seeks to make sense of the promise of AI in testing. It returns first to understand the pressure currently placed on testing by iterative software delivery, identifying some core requirements for testing in the "Third Industrial Revolution". It then considers why current testing methodologies currently fail to fulfil these objects. Only then are emerging technology from the world of AI considered. The goal is to identify how current AI technologies might remedy the challenges created by rise in automated test execution, building on the tools and techniques in place today.


AI powered heart condition detection invention launches in UK - Software Testing News

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An AI firm that is assisting in detecting and diagnosing heart conditions has announced its launch in the UK. It's thought the new product could help save the NHS billions of pounds. This condition affects around 1.2 million people in the UK alone. Public Health England estimates that around half a million live with undiagnosed AF, a disorder which left untreated, can lead to strokes, disability and even death. It's thought that strokes cost the NHS around £4 billion a year.


120 million people may need retraining to work with AI - Software Testing News

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Companies could potentially have to retrain employees to work with AI and keep up with the forecasted $97.9 billion (£79 billion) that this market is expected to reach by 2023, Forbes reports. It's predicted that as many as 120 million workers across 12 of the world's biggest economies may have to be re-educated because of the impact that AI is having on firms. This information is taken from numerous surveys and studies, according to American business magazine, Forbes. Analysing the data, it was found that just 41% of CEOs believe their staff has the skills and resources to execute the correct business strategies. Which is why so many people are opting for AI instead.


AI security tool released that thinks 92% faster than humans - Software Testing News

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A new ground-breaking cybersecurity tool has been launched that thinks like a human but works at the speed of a computer. The machine learning AI device was developed and released by cyber defense company, Darktrace. It is revolutionary in digital defense because of the way that it has been trained to make human-like decisions at such high velocity. The quickness at which cybersecurity judgments are made has been cut by 92% with the new design. Whereas it normally takes a human around 30 minutes to an hour to explore a single suspicious security report.


How to identify machine learning talent - Software Testing News

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What once was a shortage of coding and software engineering expertise has now translated into a shortage of skills in artificial intelligence and algorithmic engineering – machine learning talent. According to a recent survey on enterprise AIOps adoption, 67% of enterprise IT organisations in the US have experimented with artificial intelligence (AI) and machine learning (ML) for data management and incident remediation. What's more, global research and advisory firm, Gartner, fully expects that artificial intelligence is expected to create more jobs than it replaces by 2020 . AI is moving fast and enterprises need new talent today, not tomorrow; and not just any old talent. Here, I'm going to discuss some of the things I've learnt and some of the practical questions you can pose to uncover and secure the talent you need to help both your enterprise and potential employees succeed and excel.