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Why is this the best time for Beauty Industries to step up for Online Business?

As this Coronavirus outbreak continues to lock people down in their homes, it limits the numbers of brick and mortar shopping and makes more customers interested in eCommerce as a solution to get the items they need in this pandemic. For this, the businesses which already had their eCommerce platform, are getting more revenue, and the other businesses are leaning towards this to earn more, as most of the customers are turning to online customers. Like that, the Beauty brands who already have invested in their online presence are in a better position than the brands rely on brick and mortar retailers who are almost closed or about to run out of the business in this pandemic weather. Apparently, like the other businesses, these pandemic times can be the golden opportunity for the beauty industries to get an eCommerce platform and step up for their online business. Why? Let’s see then.

Edge Computing: The Next Level of Computing

The world is already being digital and we are using our lives most of this digital platform and services, and our workplaces too. The huge growth of remote services and implementations of updated technology in businesses is increasing the production of data and this affects the data sharing process. As the amount and speed of data sharing are incensed, it affects the efficiency of information shared to a data center, such as Cloud, also the cloud might not be able to handle all of this at a time due to an increased amount of data generated by numerous IoT connected devices. In this scenario, edge computing can be a solution for processing data in a faster, cheaper, and reliable way. So let’s be more elaborate about what is this edge computing and why it should matter to us!

How Technology Enhances Human Augmentation?

Human augmentation is mainly a field of study that focuses on the methods and technologies that enhance the productivity and capabilities of humans. Some of us may have an idea about it. Yes, technologies and the advancements of these technologies lead to the advent of human augmentations. Even for this augmentation, we can see individuals are going out and living their normal lives instead of being limited by their disabilities either physical or cognitive. Even the physically impaired individuals are welcoming these augmentations in their lives, and all of these are being possible with the combination of modern technologies.

How Blockchain and Edge Computing Support Each Other?

Both edge computing and the blockchain are part of these emerging technologies. The edge computing is an advanced and extended form of cloud computing, with collaboration to the internet of things. On the other hand, the blockchain is the main underlying technology of the currencies with the help of the internet of things. Both of these are working on the networks and share the data through the networks. Edge computing and blockchain can hold their backs in their own ways like the blockchain can provide the decentralized marketplace for edge computing whereas edge computing can provide the low latency infrastructure to the blockchain for better performance. For your convenience, I am starting with some introductory parts for both of them.

The Future of Machine Learning

In this era of artificial intelligence, machine learning is the most trending topic ever. Machine learning is a component of Artificial Intelligence Technology. This enables the machines to use its complex algorithms and allows the machines to autonomously learn from the data sets, and continuously make decisions on a specific task by improving the efficiency of the machines. It mainly focuses on computer programs, with the primary aim to make them automatically able to learn from the data and make decisions without any human interference.

Automation is Everywhere: Autonomous Driving

Automation is everywhere surrounding us. With the advancements in the technologies, the computers with its calculation power and better sensors are controlling our daily life tasks, like we use washing machine, dishwasher, refrigerator in our home, also we see the automated doors in buses and shopping malls, these all are controlled by the computers and these all are the automation in our daily life. In a broader aspect, we can think about autonomous driving as an application of automation in our lives.

Artificial Intelligence in Cybersecurity

The increasing numbers of cyber attacks and cyber threats are continuously making today’s cybersecurity tools and human cybersecurity teams impossible to cope up with this latest malware problems. Even almost 56% of researches and surveys show that cybersecurity analysts can not cope up with the increasing numbers of malware. These cyber-attacks are growing in numbers on a daily basis and making it more complex to cope up with this. And reaching these hackers is also getting impossible as they can commit the theft or do harm in someone’s personal or professional resources remotely with the help of the latest technologies.

Recent trends of Quantum Computing

Quantum computers are a new and trending form of computation that solves the problems in a faster and quicker way, which will take longer times in the case of classical computers. It uses Qubits instead of the classical bits that classical computers use. The basic difference between the qubits and the classical bits lies in their shape and the nature of the data that they encode. The quantum computer has been in the experimental stage for so many years and it is still evolving. In the last year, the Quantum Computer has got so much attention with the inventions of Google’s “Quantum Supremacy”. And the research is also showing that the total market expenditure for Quantum Computing is going to reach up to $9.1 billion annually by the year 2030.

Natural Language Processing and RPA

NLP or natural language processing is a branch of computer technology. It actually smoothens the connection between human and machine by teaching the machines to understand natural human language both verbally and written. Don’t you think that why NLP, while using ML it is able to identify the data sets and make changes to it or perform some work on it? Then come to the main point.