Anomaly detection refers to identification of items or events that do not conform to an expected pattern or to other items in a dataset that are usually undetectable by a human expert. Such anomalies can usually be translated into problems such as structural defects, errors or frauds. Anomaly detection alone or coupled with the prediction functionality can be an effective means to catch the fraud and discover strange activity in large and complex datasets.
What about AI that benefits humans’ morality, our own capacity to behave virtuously? Designing technologies to encourage ethical behavior raises the question of which behaviors are ethical. To what degree should we focus on helping people develop a moral compass and fortitude, and to what degree should we focus on nudges and social platforms that make morality easy? What’s clear is that just as we define our technologies, they define us. AI systems could invite us to reflect privately upon the sort of person we think we are or want to be.
In the 2010s, automation got better, cheaper, and way less avoidable. It’s still mysterious, but no longer foreign. On the other hand, each of us now sees a personalized version of the world that is curated by an AI to maximize engagement with the platform. Humans and tech have always coexisted and coevolved, but this decade brought us closer together—and closer to the future—than ever. So here’s how we changed our bots this decade, how they changed us, and where our strange relationship is going as we enter the 2020s.
It is hard to imagine a Board member today in any large organisation who would be unaware of cyber threats. Of course, priorities may vary in line with economic conditions or the general health of the business, but “cyber” is on the agenda of all Boards, and consistently rated as a top risk by many. The focus of the Board has shifted towards execution, very often in exchange of significant investments in cyber security, in particular where initial maturity levels were low.
As cognitive technologies and automation force every job to be reinvented or adjusted, the future of work is rapidly developing around the idea of an ‘augmented workforce’ made more capable by technology. The future of work is defined by high-tech, smart management, and even smarter employees. Tomorrow’s successful companies are embracing automation, taking better care of their employees, and restructuring offices into healthy, open, and collaborative spaces. They’re increasingly relying on the gig economy, and leveraging the quantified self to improve wellness and motivation.
Staff turnover can be surprisingly costly, even for roles which do not require specialist qualifications. If a sizeable percentage of your workers walk out the door each year, you’re looking at significant disruption and a big bill. That’s why it makes sense to make it a priority to keep your existing team happy. Deploying robotic process automation (RPA) technology to eliminate repetitive manual processes wherever practicable is one way you can do so – and boost efficiency and productivity in the process.
The Internet of Things is still emerging which generate sufficient and attractive returns for investors. In the future, bank branches will become extinct and banking as a service (BaaS) will become the most important business model, while cloud-based services will become the main banking platform. Though an IoT project will certainly cost a lot to introduce, it will pay off in the long run. When you invest in the IoT, you invest in your future. The winners will be organizations which overcome today’s obstacles to embrace change and capitalize on initial uncertainty.
Over the past two years, we’ve seen robotic process automation (RPA) emerge as one technology for making this automation-first mindset a reality. However, introducing automation into an organization is a massive undertaking that can be difficult to effectively implement if you don't execute it correctly. Even after addressing challenges such as organizational resistance, concerns over job losses and identifying the best automation technology for a business, it can be difficult to establish an automation program that operates at full efficiency.
Just as computing dramatically altered workplaces in the 1980s, the development of artificial intelligence and robotic process automation will usher in a new period of dramatic change in 2020 and beyond. Enticed by the potential for the technologies to streamline workflows and improve customer service, organisations will be undertaking deployments in ever-increasing numbers. At the same time, the capabilities of the technologies will continue to grow at a breakneck pace. During 2020, five key trends will shape the field of AI and RPA.
It’s time to take stock and the picture is somewhat bleak. Instead of a global technological utopia, there are a number of worrying signs ranging from income inequality to the rise of popular authoritarianism. The fact is that technology and globalization have failed us. Technology alone will not save us. To solve complex challenges like inequality, climate change and the rise of authoritarianism we need to take a complex, network based approach. We need to build ecosystems of talent, technology and information. That won’t happen by itself, we have to make better choices.
During 2020, we will increasingly see a more predictive approach being offered by applications. Driven by the addition of factors such as artificial intelligence and sensors, applications will be able to better provide support and services. They’ll shift from being reactive business processes to proactive business applications. Predictive and proactive business applications will become much more widespread. Predicted trends such as these will guide that change and help organisations take advantage of opportunities as they appear. Here the top five trends to watch out for in 2020.
Today, customers can be in touch with their bank using a laptop, a tablet, a smartphone or a smart watch. The advantages of such connections are pumped up by the development of the market of the innovative IoT in banking and finance, which allows banks to collect more data about their customers’ preferences, behavior, and needs. The use of IoT technologies ensures the collection and analysis of large amounts of banking information. Banks can use the obtained data to better understand and track the behavior of their customers.
The year 2020 will hit all 4 components of IoT Model: Sensors, Networks-Communications, Analytics-Cloud, and Applications, with different degrees of impact. By 2020, the Internet of Things (IoT) is predicted to generate substantial revenues, as well as to drive substantial cost reductions. IoT and smart devices are already increasing the performance metrics of major industries. The following 10 trends explore the impact of many technologies on IoT and predict what is next for IoT.
Multi-channel design simply means that a channel is being used multiple times. The channel is only needed to be drawn once, and placed into the design process. Are you using a multi-channel design tool? What are your top benefits? Multi-channel design is something supported in multiple stages in the overall design process. Multi-channel design is a must for future design projects and there are certainly many more benefits to implementing a multi-channel design tool within your PCB design process.
When will blockchain become a true game-changer? Despite the enormous amount of research into uses for blockchain technology and the large number of pilot projects using blockchain technology, many questions still remain. Experts are seeking to see that killer app that requires blockchain tech as the enabler. 2020 may very well be that game-changing year. If not, we will certainly see tremendous progress, and some organization will release a true game-changing app based on blockchain technology in the early '20s.
The reaction to the phrase artificial intelligence was mixed. Did it really explain the technology? Was there a better way to word it? Well, no one could come up with something better–and so AI stuck. Since then, we’ve seen the coining of plenty of words in the category, which often define complex technologies and systems. The result is that it can be tough to understand what is being talked about. So to help clarify things, let’s take a look at the AI words you need to know.
The importance of visualization is a topic taught to almost every data scientist in an entry-level course at university but is mastered by very few individuals. This article focuses on the importance of visualization with data. The amount and complexity of information produced in science, engineering, business, and everyday human activity is increasing at staggering rates. Good visualizations not only present a visual interpretation of data, but do so by improving comprehension, communication, and decision making.
Why are black-box models so in-vogue? A model can be a black box for one of two reasons. The function that the model computes is far too complicated for any human to comprehend, or the model may in actual fact be simple, but its details are proprietary and not available for inspection. It’s hard to argue against the tremendous recent successes of deep learning models, but we shouldn’t conclude from this that more complex models are always better. There has been a lot of research into producing explanations for the outputs of black box models.
How Decision Trees work exactly? This is one of the most asked questions in ML/DS interviews. We generally know they work in a stepwise manner and have a tree structure where we split a node using some feature on some criterion. But how do these features get selected and how a particular threshold or value gets chosen for a feature? This post will talk about three of the main splitting criteria used in Decision trees and why they work.
Is IoT a danger of the future? There are IoT devices that we carry with us all the time and which can also be misused for various purposes. If we look at business users and some things are complicated because today in industry 4.0 we have a large number of IoT devices that can also be abused and make huge financial damage to the company.
Have you ever thought what will be in the future with your experience and skills that you are getting during your lifetime? What if people from around the world can create the skills for enterprise software or IT products/programs and publish them on the marketplace? It means any person, or a developer, or a consultant can transfer their knowledge by creating digital skills, and publish them on the marketplace (skills store), specify the pricing for the skills and sell them.
For many CIOs who are expected to lead the charge towards the digital holy grail, the exercise can be a hair-raising challenge that requires them to navigate an unchartered IT minefield, with redundant and obsolete applications that have accumulated over the years threatening to blow the entire exercise out of the water. It’s essential that before embarking on a digital transformation journey, CIOs ensure they fully understand and then streamline the organisation's application portfolio.
Blockchain technology is young and changing very rapidly; widespread commercialization is still a few years off. Nonetheless, to avoid disruptive surprises or missed opportunities, strategists, planners, and decision makers across industries and business functions should pay heed now and begin to investigate applications of the technology. Blockchain ensures that data has not been tampered with, offering a layer of time stamping that removes multiple levels of human checking and makes transactions immutable. However, it isn’t yet the cure-all that some believe it to be.’
The coming year will be exciting as ever when it comes to technology. We live in exponential times and the more various technologies converge, the more exciting the opportunities become. The Internet of Things will drive the data deluge, which will help train artificial intelligence, which will result in better applications and more personalisation. New developments in chip design will continue Moore's law and result in more powerful machine learning algorithms, while decentralised solutions will bring back control to the consumer. 2020 will be the Year of Convergence. Here are the top seven technology trends for 2020.