Artificial intelligence (AI), machine learning (ML) and deep neural networking (DNN) are disrupting businesses and challenging traditional values in the financial industry
"Slowly but surely, AI is quietly impacting the world through numerous and varied applications. AI technology is already powering many everyday activities, from driving us to work to automatically adjusting the thermostat, and often without our knowledge. According to Gartner, 40 percent of major businesses will implement AI solutions in 2020, and more than haalf will double existing implementations in 2020. This forecast was made before the COVID-19 pandemic hit, but even with this taken into account the rise of AI will be exponential.
In some industries AI, machine learning (ML) and deep neural networking (DNN) have a greater number of applications. One of these is the financial industry, where the new technologies are already disrupting businesses and challenging traditional values..."
HSBC is using artificial intelligence technology developed in-house to help it make sure ATMs are appropriately stocked with cash
"HSBC is replacing more manual processes, with artificial intelligence (AI) being used to automate when ATMs need to be refilled.
The technology, developed by HSBC's operations and technology teams, has been trialled in Hong Kong, where the bank has 1,200 ATMs.
The iCash AI technology has reduced ATM refills, which are done by third parties, by 15% - saving $1m.
To calculate how much money is needed and where, iCash uses live ATM data and predictive machine learning algorithms that factor in seasonality, holidays, public events, location and recent withdrawal trends..."
A new report suggests that to improve AI accountability, enterprises should tackle third-party risk head-on
"A report issued by technology research firm Forrester, AI Aspirants: Caveat Emptor, highlights the growing need for third-party accountability in artificial intelligence tools.
The report found that a lack of accountability in AI can result in regulatory fines, brand damage, and lost customers, all of which can be avoided by performing third-party due diligence and adhering to emerging best practices for responsible AI development and deployment.
The risks of getting AI wrong are real and, unfortunately, they're not always directly within the enterprise's control, the report observed. "Risk assessment in the AI context is complicated by a vast supply chain of components with potentially nonlinear and untraceable effects on the output of the AI system," it stated.
Why is AIOps important to Enterprise IT? Michael Allen, VP & CTO EMEA at Dynatrace discusses AIOps, why it matters to enterprise IT and where it fits within the traditional IT landscape.
"AIOps represents hope of helping organizations automate operations, turn data into precise answers and assist stretched IT teams who are struggling to piece together often conflicting insights from countless monitoring tools and dashboards. AIOps combines AI and continuous automation to analyses and triage monitoring data faster than humans ever could, making sense of the barrage of alerts they face due to rising IT complexity.
AIOps matters as, when deployed correctly, it can help teams get out of the endless firefighting loop, enable them to eliminate false positives and identify which problems need to be prioritized to optimize the user experience - effectively allowing them to stretch their limited resources even further and focus on what matters..."
Today, we still think of artificial intelligence (AI) as the technology of tomorrow - and that makes me worry that many of us aren't paying close enough attention to the incredible leaps happening in the field. In truth, AI has already started to transform life - and marketing - as we know it
"The adoption of AI is right now bringing companies the benefits of real-time audience segmentation, personalized messaging, predictable customer value, and optimized media buys. It has ceased to be an abstract idea located at some distant point in the next decade. It is instead a tool that marketers need to equip themselves with now in order to stay effective and relevant for the near future.
With explosions taking place in the amount of customer data that can be generated each second, deep insights are obtained regarding customer intentions and behavior. Deep learning - a subset of machine learning (ML) - makes personalized marketing-at-scale a present-day reality. Every day, tons of data are gathered from leads, prospects, and customers. With data flowing in from websites, apps, CRMs, marketing automation systems, social media, and even the Internet of Things (IoT), companies now have more substantive information to leverage than ever before. Optimal marketing ROI being a top priority for any business owner, once they pair with the power of AI, an enormous value is instantly created..."
Explore the different trends and topics tech and business leaders need to know
"We've all come to terms with the fact that artificial intelligence (AI) is transforming how businesses operate and how much it can help a business in the long term. Over the past few years, this understanding has driven a spike in companies experimenting and evaluating AI technologies and who are now using it specifically in production deployments.
Of course, when organizations adopt new technologies such as AI and machine learning (ML), they gradually start to consider how new areas could be affected by the technology. This can range across multiple sectors, including production and logistics, manufacturing, IT and customer service. Once the use of AI and ML techniques becomes ingrained in how businesses function and in the different ways in which they can be used, organizations will be able to gain new knowledge which will help them to adapt to evolving needs..."
There's a difference between a shiny new thing and a thing that works. You just need to look at the annual Consumer Electronics Show (CES) in Las Vegas to see how much of the technology we create just doesn't cut it and gets tossed into the wastebin of innovation because it doesn't find a working business model
"Where does artificial intelligence stand? Recent advances in machine learning have surely created a lot of excitement-and fear-around artificial intelligence. Game-playing bots that outmatch human champions. A text-generating AI that writes articles in mere seconds. Medical imaging algorithms that detect cancer years in advance.
How much of these technological advances are actually making it to the mainstream? How much of it is unwarranted hype? How will AI affect jobs? How is machine learning changing the business model of companies?..."
The future of successful AI implementations will be MLOps
"Businesses increasingly solve complex problems with data science. Access to very large data sets, accelerated advances in ML research fields, and inexpensive computing power are driving an AI-fueled transformation across industries.
In a crowded market where consumers can have anything at any time, ML/AI applications that prevent fraud, mitigate churn, serve product suggestions in real-time, and manage predictive maintenance on infrastructure can be the critical differentiator. Yet as AI/ML projects come into the mainstream, businesses are finding just how hard it is to go from data science to business value..."
Artificial Intelligence is quickly becoming a reality for businesses of all shapes and sizes
"With the massive amounts of data, your business needs smart machines that derive valuable insights. Artificial Intelligence enables you to make sense of that data, understand the patterns and use it to your advantage.
A recent report shows that the worldwide data will grow by 61% to 175 zettabytes by 2025. It would be a result of businesses collectively generating tons of customer data. It would become next to impossible to manually process this data, understand its behaviour, and deriving analytics and insights.
But do you really need all this data? If you trust what studies show, then data is going to be the most significant factor in determining the success or failure of your business. Target has been using it for a year, and while it was controversial, they seemingly are benefitting from that data..."
Taking pause to consider whether technological progress is amplifying challenges we are trying to overcome
"2020 is forcing us to confront some hard truths about the world we live in. The COVID-19 pandemic has cast a sobering spotlight on the unsustainable path we are on.
One such truth is symbolized by the global #BlackLivesMatter movement, which has once again highlighted the embedded biases in our interconnected social fabric, forcing us all, to re-evaluate long standing notions of morality, fairness and ethics.
It is worth taking pause to consider whether the exponential technological progress is not also amplifying some of the very same challenges we are trying to overcome as a global society..."
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