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The US-China trade war has triggered a major reshuffle of the supply chain. The global manufacturing industry is facing unprecedented challenges. In the process of transforming smart manufacturing, the biggest problem is the integration of operating technology (OT) and information technology (IT). Only by working with the smart manufacturing ecosystem can we have a chance to survive in the changes and seize future business opportunities.

The innovative development of technology and storage in 2023, including multi-cloud, will tend to be localized in 2023, cloud service providers will face more transparency requirements, heat-assisted magnetic recording (HAMR) technology will become more popular, etc.

In the new normal of future changes, whether it is the ICT industry, the supply chain, or even the industrial ecosystem, it is necessary to think about how to improve resilience to respond to environmental changes from a mid-to-long-term perspective. It will be important to improve the resilience of the supply chain from procurement to production. The key to future competitiveness.

There are continuous information security attacks against manufacturers around the world. For the manufacturing industry, it is not only necessary to consider the information security layout of the IT side, but also to strengthen the overall protection capability on the OT side to cope with the increasingly rampant cyber-attacks.

Natural language processing is a technology that enables machines to recognize, understand and use our language through complex mathematical models and algorithms. As the NLP technology becomes more mature, the machine can work 24 hours a day and the error rate is extremely low, which will drive the wider application of NLP and create more value for the market.

When you chat with friends or family members using communication software, the information may be intercepted when transmitted on the Internet, thereby exposing the chat content. If the content contains confidential information, it may endanger privacy and security. End-to-end encryption (E2EE) is a method of protecting data that prevents potential eavesdroppers from monitoring data in transit.

Non-Practicing Entities (NPEs) is a special group of the intellectual property industry. Patent litigation involving NPEs has become a common global business activity, and it is a patent issue that the technology industry needs to pay special attention to.

It's that time of year again, check out the predictions for the most promising emerging technology trends to watch for in 2022. Pay close attention to the following topics as they will be covered in details to see what is happening around the globe.

An Industrial PC, referred to as IPC, mainly refers to a personal computer that is specially used in the industrial world and can be used as a manufacturing controller.

Technology today is evolving at a rapid pace, and these changes and progress have resulted in an even greater acceleration of change. One of the greatest areas of change that has come about as a result of COVID-19 outbreak is IT technologies. IT professionals have come to realize that their role will not stay the same in the contactless world of tomorrow.

The electronics industry categorizes LED technologies according to the size of the LED chip. For example, an LED chip that is less than 150 μm is called a mini LED; an LED chip less than 50 μm is called a micro LED. As the size of LED chips becomes smaller and smaller, the structure of display panels will also change accordingly.

Radio Frequency Identification (RFID) is a technology used to identify items in a unique manner by the use of radio waves. It is unique in that it is capable of scanning hundreds of objects at the same time. Although the term of RFID is not often heard, we use it in our daily lives more than we realize, and its use continues to increase.

The variety and volume of data that is being transmitted via the internet today, as well as the velocity at which it is being transmitted is constantly increasing. These data sets are so voluminous that traditional data processing software just can’t manage them, and so they have come to be called “Big Data”. The massive volume of data necessary to address new and more complex business operations has brought about new challenges to meeting the requirements of these new developments.

Let’s explore the different types of Edge Computing and their amazing applications in a real-world scenario. Edge computing is a type of data processing in which data is distributed throughout decentralized data centers, while some information is maintained locally, at the “edge.” There’s no need to ask a remote data center for approval. Data can be deployed offline by local devices using less bandwidth usage. Is this a way to move forward when we have the benefits of Cloud Computing? Will Edge Computing be able to make a mark in the industry?

Blockchain, sometimes referred to as Distributed Ledger Technology (DLT), makes the history of any digital asset unalterable and transparent through the use of decentralization and cryptographic hashing. Blockchain is an especially promising and revolutionary technology because it helps reduce risk, stamps out fraud and brings transparency in a scalable way for myriad uses.

Machine learning is the application of artificial intelligence to imitate the way that humans learn. It is a scientific study that uses data, algorithms and statistical models to give computer systems the ability to automatically learn and improve from experience, so that they can perform specific tasks without being explicitly programmed. Data science is a broad field that includes the capturing and processing of data, analyzing it, and deriving insights from it. One area of data science is data mining which involves finding useful information in a dataset and utilizing that information to uncover hidden patterns. In this article, we will look at a few machine learning and data science start-ups that are worth keeping an eye on.

This may seem like a simple question, but that confuses many people. It is also, one of the most popular issues discussed on Quora. So, we are going to delve into this question and see if we can shed some the light on the main differences between IT and Telecommunications.

The low-code development environment allows users with less technical knowledge to build entire business applications on their own without the assistance of IT staff.

With increasingly complex IT architecture exacerbating maintenance and operation challenges, the demand for IT agility is driving the growth of the AIOps market.

Robotic behavior is often built as a computational graph, with data flowing from sensors to computational technology, all the way to actuators and back. To gain additional performance capabilities, robotic computing platforms must efficiently map these graph-like structures to CPUs, as well as to specialized hardware including FPGAs and GPUs.