Welcome to The Digital Eye, your weekly roundup of the latest technology news.
Our team of experts has scoured the internet for the most exciting and informative articles so that you can stay up-to-date on Digital, Data, Blockchain, AI & Analytics, and Digital Transformation.
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6 Machine Learning Algorithms to Know About When Learning Data Science
Short Explanations of 6 Popular Machine Learning Algorithms
Machine Learning has become very popular over the past decade or so with many industries adopting new algorithms to automate processes and increase productivity.
Machine Learning is a branch of Artificial Intelligence (AI) and involves machines/computers learning from data and generating results without being explicitly programmed to do so. In traditional programming we provide the input data and the rules to generate an output. In machine learning we let the algorithm figure out the rules by providing the input data and the answers.
Once these algorithms have been trained we can use them to make predictions on any new data presented to them.
Within this article we will look at 6 commonly used machine learning algorithms that you need to know.
6 FinTech trends that will dominate the industry in 2022
With the world having been in a non-stop crisis mode for the last 2.5 years, it looks like innovation will continue to thrive.
2022 may have started as the year of blockchain technologies and NFTs, but since March, the crypto market has seen a major dip.
However, despite the cooling of crypto, some trends have continued to flourish throughout the middle of the year. This article will discuss the six FinTech trends we believe will boom in 2022.
In the beginning, there was Web 1.0. This was a time, starting in 1994 when content on the internet was non-interactive and read-only. Starting in 2004, Web 2.0 introduced interactivity into websites and the internet. Now, 18 years later, Web 3.0 has begun its introduction.
Fintech is far from ‘dead’
A machine-learning algorithm that includes a quantum circuit generates realistic handwritten digits and performs better than its classical counterpart.
Machine learning allows computers to recognize complex patterns such as faces and also to create new and realistic-looking examples of such patterns. Working toward improving these techniques, researchers have now given the first clear demonstration of a quantum algorithm performing well when generating these realistic examples, in this case, creating authentic-looking handwritten digits . The researchers see the result as an important step toward building quantum devices able to go beyond the capabilities of classical machine learning.
The most common use of neural networks is classification—recognizing handwritten letters, for example. But researchers increasingly aim to use algorithms on more creative tasks such as generating new and realistic artworks, pieces of music, or human faces. These so-called generative neural networks can also be used in automated editing of photos—to remove unwanted details, such as rain.
The Future Growth of AI Software Development
With the many benefits that AI software development brings, businesses and individuals can expect to see more opportunities open up for them in the near future.
As artificial intelligence (AI) continues to grow in popularity, businesses are starting to see its potential for improving their operations. AI can be used in various ways, including the development of software.
The future growth of AI software development is something that many people are talking about. As businesses become more and more reliant on technology, the need for AI software will continue to grow. In this blog post, we will discuss the future growth of AI software development and how it can benefit businesses. Stay tuned for more information.
IoT In Blockchain: Benefits, Use Cases, and Challenges
Adopting IoT and blockchain technologies is not as widespread as one would believe. That is pure because of operational challenges and technical concerns.
IoT enables connected devices across the Internet to transmit data to blockchain networks and create tamper-resistant records of transactions in the process. This article introduces us to how using blockchain enhances IoT data security and how the combination of the two works. Moreover, we will learn the top use cases of the blockchain IoT technologies and their benefits:
The Internet of Things or IoT is a network of connected devices and people — collecting and sharing data about how they are used and the environment around them — over the Internet. Sophisticated sensors, modules, and actuators are embedded into physical products.
IoT’s analytical capabilities transform the data collected into insights, positively influencing business processes and resulting in new ways of working. Statista reports there will be 29 billion IoT devices by 2030. The total IoT market value worldwide will be one billion by the same year.
In a digital world fueled by a steady influx of data, achieving organizational excellence depends on giving everyone immediate access to accurate, up-to-date information. Organizational-wide communication and collaboration are vital. Mission-critical decisions, in particular, depend on the timely sharing of lessons learned and insights from all departments.
With new technology based on artificial intelligence (AI) and machine learning(ML), it’s easier than ever to share data effectively and consistently. Significantly, technology now enables businesses to tap the knowledge stored in one person’s mind and translate it into actionable data that anyone can leverage whenever they need it. This technology takes organizational communication and collaboration to the next level — an invaluable advantage in the pursuit of excellence.