5 Scenarios For The Future Of Technology And Development

Talk about how future technologies, including human-computer interactions, robots, and autonomous vehicles, will impact our lives and the world around us.

Over the past two decades, digital technologies have primarily defined modern life. And a deep integration of various technologies will mark the future. Scientists expected that humans would be able to control the material universe by 2030.

Human society has undergone dramatic changes as a result of the advancements and applications of science and technology. As science and technology developed, labor productivity increased. The workers are freed from heavy physical labor. Time and space are becoming less of a constraint on our lives, affecting our living habits and lifestyles. Changes in technology have an impact on every aspect of human life. We have listed a few of them below.

1. Natural human-computer interactions

future human-computer interaction technology

The interaction between humans and computers is still in its early stages with touch, voice, and somatosensory signals. We are going to be presented with a lot of marvelous applications in the subsequent phase. For instance, by looking at your screen, the screen determines your status, optimizing and learning, and correcting as necessary to provide you with the best service. In this regard, science and technology can be seen as a living organism that inevitably develops to modify humans' "repelling reaction." Culture and business are bound to undergo profound changes due to screens everywhere. There is still a long way to go before screen media, and interactive windows are fully released from their influence.

Back then, being digital meant having a cellphone number, an email address, and maybe even a Myspace page. In today's digital world, people are able to live a full, digital life because of the interactivity they have with other people on various social media platforms. WeChat, QQ, Facebook, Twitter, LinkedIn, Instagram, and other accounts are examples of digital identities that many people have, usually more than these ones.

The virtual world on the Internet has become increasingly entwined with real life in an increasingly interconnected world. Digital identities will become increasingly commonplace in the future. As we portray ourselves through our dress, language, and behavior in real life, building and maintaining an online image will come as naturally as that. People can create their own online images, search for and share information, freely express themselves, meet others, and build relationships with anybody in the online world.

2. An era of sharing

sharing economy

People are willing to share more if they are given the chance. Today's technology and applications are far from providing enough opportunities for people, and many of those who wish to share still haven't yet been able to do so.

Generally acknowledged, this phenomenon describes the development of technology that allows entities (individuals or organizations) to jointly share the right to utilize a certain physical commodity or share/provide a specific service, which was very inefficient or impossible to achieve in the past. Such goods or services are often shared through online markets, mobile applications and location-based services, or other technology-driven platforms. In this way, all participants can achieve good economic benefits, as transaction costs and system friction are reduced. Sharing economy examples abound in the transportation sector, including Uber and Didi, two well-known companies.

3. Robots in the workforce

For safety reasons, most robots used in heavy industry were kept away from humans as much as possible. And now, whether on the battlefield or in the factory, robots are beginning to work side by side with humans. Robots are expected to play an increasingly critical role in our daily lives by 2030. Using nanomaterials that are lighter and stronger, the next generation of robots can naturally interact with humans. Built with powerful neurological chips and deep learning algorithms, they can operate independently or collaborate with humans.

From manufacturing to agriculture, retail, and service industries, robotics has begun to affect all walks of life. In the United States, a robot pharmacist has been introduced. The International Federation of Robotics reports that there are 1.1 million industrial robots in use worldwide, and robots do 80 percent of auto industry work. The use of robots is improving supply chain efficiency so that business performance is more predictable and efficient.

4. Self-driving on a large scale

future automobile self-driving technology

A lot of progress has been made in self-driving technologies. Sensors, cameras, video recorders, onboard radars, and laser rangefinders can assist autonomous vehicles in detecting their environment and following a preset course. It is projected that unmanned vehicles will be used widely by 2030.

5. New computer architecture

Gordon Moore proposed Moore's Law in 1965, which predicted that the chip's processing speed would double every 18 months. Chip engineers have been practicing this law of development for more than 50 years. Now that Moore's Law is about to end, people are attempting to extend its life through 3D stacking and FPGA chip technology, but they have limited effects. For the chip industry to continue growing quickly, we need to develop a new computer architecture.

Quantum computing exploits quantum effects such as overlap and entanglement to increase computer performance million times over today's chip. The other one is to develop a neurological chip that mimics the human brain, which will run at a faster processing speed, billions of times faster than existing computers. It will take several years for these two new types of computers to be commercialized, but there are already prototypes in use. We can expect these new architectures to transform the computer industry within 10 years completely.

Currently, scientists are working on applying quantum computers to new technical fields, such as using them to analyze gene sequences, predict stock market fluctuations, simulate the interactions between individual molecules, and expand the possibilities of machine learning. Additionally, although it is still impossible to evaluate thoroughly the ability of this kind of computer to handle problems, it is believed that an answer will be revealed in the near future.

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