Clustering is a Machine Learning technique that involves the grouping of data points. Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group. In theory, data points that are in the same group should have similar properties and/or features, while data points in different groups should have highly dissimilar properties and/or features. Clustering is a method of unsupervised learning and is a common technique for statistical data analysis used in many fields.
Think of the old paradigm where a software sales person or team would shuffle into your conference room and deliver a packaged presentation, followed by a packaged demo, in hopes of finding a hot button that appealed to you and somehow satisfied your need. That won't work today and a wise software company knows that. If you want to succeed in the market today, you have to get ahead of things. You need to understand what your prospective customers want, and need, and take into consideration the industry in which they work.
While the same core technologies that dominated discussions will continue to be foundational to our collective digital transformation journey, 2020 will be defined by a fresh new class of technologies ready to graduate to the sidelines to center stage. Among them: 5G, AI, advanced data analytics, but also some that may surprise you. Without further ado, here are the 10 among them that will be the most significant in 2020, and will both dominate digital transformation discussions and inform the trajectory of successful digital transformation programs.
Online banking is just one of the online services most of us rely on. But it's a huge part of why robust cybersecurity is utterly essential for consumers and banks alike. So let's talk about cybersecurity and staying safe when it comes to digital banking, for both corporations and the average user. There are several other steps banking customers can take, today, to keep their money and their financial lives safe. Find a bank that provides customizable account and card notifications for transactions, and then take the time to set them up.
Distributed version control systems (DVCS) offer very fast, lightweight and local software change control capabilities that support many parallel code branches across large project code bases. These are compelling benefits for individual developers and development teams. At their heart, DVCS accomplish this by tracking software changes as a series of file system snapshots in local repositories instead of via management of individual file changes in a central database. The DVCS approach is ideal for individuals and small agile teams because it puts control directly in their hands without the need to transact all file changes.
How many people know what Blockchain really is about? In an attempt to make this definition as simple as possible, blockchain automates trust. It’s a software architecture that allows non-trusting parties to record transactions without requiring a trusted governing authority. In other words, it does away with middlemen. That directly affects banking, insurance, and distribution, as well as any industry that previously relied on a trusted third party. There are many benefits of blockchain technology.
Businesses around the globe are creating smart offices to improve productivity; save money on utilities; and create a happier, healthier workforce. If you're planning in on building a smart office, start by figuring out how this technology can improve your existing operating procedures. The goal of creating smart offices is to work smarter, not harder. Don't bring in IoT if it's going to make your job harder. Use it as a tool to make things flow more smoothly.
If we talk about secret weapon of FinTech, i.e. blockchain technology, how will it disrupt banking sector? Blockchain has shown a lot of potential for the banking sector and has numerous benefits. Nevertheless, there is no doubt that blockchain has taken up the banking industry by storm and the landscape of the industry is quite changed with its arrival in the market and certainly, the technology is going to progress more in the finance and banking and will be the key pillar of change in the banking sector.
As businesses and consumers grow more reliant on mobile devices, there’s a 33-percent surge in mobile malware attacks, according to the Symantec 2019 Internet Security Threat Report. The previous year’s study reports that nearly all malicious mobile payloads are delivered by third-party app markets outside of Google Play and Apple iTunes. By 2023, says Symantec, almost half of all cyberattacks will occur in the United States. Here are 5 cybersecurity essential tips for protecting your small biz.
There is simply no reason to think that AI and robots will render us redundant. It is projected that, by 2025, there will be 3.5 million manufacturing job openings in the US, and yet 2 million of them will go unfilled because there will not be enough skilled workers. In conclusion, rather than undermining humans, we are much better off thinking hard about how to upskill ourselves and learn how to work alongside machines, as we will inevitably coexist – but it won’t be a case of us surrendering to them.
AI projects are no different from business transformation projects: Pick the right problems to solve. Evaluate ideas through pilots. Convince users with consumable benefits. However, practitioners often get carried away with the solution. They miss focusing on the problem that must be addressed. At the other end, users get intimidated with the hype around AI. All of this leads to a culture of resistance to AI projects. You must also navigate the change management that AI projects demand.
Technology gives us new experiences, new abilities, and new problems. Thus we need new words to keep up with this changing world. The great technology of our time, artificial intelligence, will do the same – it will change the world and our language with it. Usually, the new words flow from necessity and are created organically. But with AI, I am going to suggest some new words that we are going to need to adjust to this new technology.
Enterprise resource planning (ERP) is a process management software used by businesses that merges various aspects of a business, such as manufacturing, financials, and reporting into one fluid system. In the past, separate software systems were needed for the mentioned business aspects to accomplish all business functions. Today, modern ERP software can bring all business processes together to keep up with all your business needs. Here’s our list of top ERP trends and how they will affect business in 2019.
In the IT world, when you ask someone, ‘what is Shadow IT?’ The answers you get are going to vary quite a bit, some in the industry refer to it as a threat, others are far more optimistic and advise organizations to embrace it. When your employees use software or hardware at work that your IT or security team is unaware of – that’s Shadow IT. In the context of digital certificates, Shadow IT can lead to unexpected expirations, operational downtime, loss of revenues and compliance penalties.
The revived idea of a universal basic income (UBI) is the cornerstone of the limited policy discussion under way. The idea is, of course, not new but has had numerous incarnations over many decades and been presented as a solution for quite different problems. The one that concerns us here is simply whether the UBI could be a solution for large-scale technological unemployment or temporary labor market dislocations that could result from accelerated technological change.
While it is true you can easily “containerize” nearly any software quite quickly, this alone will not realize the benefits of an effective container deployment. Those who are serious about containers will do well to learn from others. In this article we list nine pillars of best practices for containers. While is it clear that containers offer immense value for software deployment, adhering to best practices is essential to realize their value.
Different to a few years ago, many experts today consider the underlying blockchain technology as the largest potential to disrupt industries far beyond banking. There are indicators that blockchain projects with the primary focus on general-purpose technology and other applications are on the verge of disrupting other industries instead of being a pure store of value. With respect to the chemical industry, we want to emphasize four main blockchain features that can be combined to enable new functionality.
On one hand, artificial intelligence in cyber security is beneficial because it improves how security experts analyze, study, and understand cybercrime. It enhances the cyber security technologies that companies use to combat cybercriminals and help keep organizations and customers safe. On the other hand, artificial intelligence can be very resource intensive. It may not be practical in all applications. More importantly, it also can serve as a new weapon in the arsenal of cybercriminals who use the technology to hone and improve their cyberattacks.
When you run a business, maintaining compliance with all governmental rules and regulations including taxation, worker safety, and environmental measures is key to ongoing viability. Compliance issues often arise from changes in adherence to applicable laws, regulations, and guidelines specific to business practices. It forms the basis of many complaints about governmental interference in private business operations. However, leaders must realize the rules exist for a reason, in many cases to increase parity and promote public health and safety.
There are benefits that AI and blockchain can jointly bring. Because blockchain can act as a trustworthy source of information, it is possible to feed AI with validated and authenticated data, thereby enabling the machines to be much better at decision-making. In addition, blockchain can also be used to monitor and record any abnormalities in data that could result from bias. Avoiding these distortions would enable machine learning algorithms to evolve in efficacy and to minimise the chance for specific bias to show up again in future AI models.
At the heart of cyber resilience lies a real application of “defence in depth” principles which have been well established for decades: Acting at preventative, detective, mitigative AND reactive levels, AND across the real breadth of the enterprise – functionally and geographically. It is about the enterprise being enabled by the use of data and technology, whilst remaining protected from active threats. Instead of being treated as another box checking exercise and a quick win, cyber resilience must be embedded into the right corporate structures and used to channel a different culture from the top down around cyber security.
Generative adversarial networks (GANs) have enabled the AI industry to take huge leaps toward creativity. However GANs are opaque, which means there’s very little visibility or control on how they work. As a result, engineers find it hard to troubleshoot them, and users find it hard to trust them. To overcome these limitations, researchers have developed a technique called “GAN Dissection” that helps explore the inner workings of GANs and better understand the reasoning that results in their output. The work is one of several efforts collectively explainable AI, that can interpret AI decisions
AI is not something to be feared. It’s not an impending robot revolution. It’s not an economic tidal wave rushing to wipe out jobs and create large-scale unemployment. What it is is another technological disruption, and just like any other technological disruption of the past, it is bound to cause some shock waves. These changes, however, are not something to be feared, but embraced. We need to stop treating AI as the villain in some low-budget sci-fi horror film.
Practical studies have proven Evolutionary Deep Learning applications to be a useful method for advancing the state of the art. Nevertheless, lots of limitations are still present in employed methods, just like the use of predefined building blocks for Neural Architecture Search and non-crossover nor mutation used in Evolutionary Deep Learning. Also, it is noticeable that Evolutionary Algorithms are seen as black-box optimization methods and thus they provide little understanding of why the performance is high. Further research will decide the future of Evolutionary Algorithms in Deep Learning.