4 major trends for artificial intelligence in 2021


liu, tempo Date: 2021-07-23 09:36:42 From:ozmca.com
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The US Forbes – biweekly website published a report entitled “Four Trends For Artificial Intelligence in 2021”. The author is Bernard Marr. Based on the current situation, the article predicts the four trends of artificial intelligence next year.

 

 

Before the global epidemic broke out in 2020 and the world was completely overturned, artificial intelligence, especially the branch of artificial intelligence-machine learning (ML)-had been widely disrupting almost all industries.

 

 

The new coronavirus epidemic has affected many aspects of our behavior, but it has not weakened the impact of artificial intelligence on our lives.

 

 

In fact, it has become obvious that self-learning algorithms and intelligent machines will play a major role in the current battle against this epidemic and other events that we may face in the future.

four trends of artificial intelligence

 

When it comes to selecting technologies that will change the way we live, work, and play in the near future, artificial intelligence is undoubtedly still a key trend.

 

 

To this end, we outline below what we can expect in this year of rebuilding our lives and rethinking business strategies and priorities.

 

 

1. Smarter big data analysis

 

In the current epidemic, we have witnessed the urgent need to quickly analyze and interpret data related to the spread of the virus around the world. Governments, global health institutions, academic research centers, and industry jointly develop new methods for collecting, summarizing, and using information.

 

 

Technological progress is the main reason why this epidemic (yet) did not cause as many deaths as the Spanish flu of 1918. As many as 50 million people died in that epidemic. From advances in medical technology and medical standards to advances in communication technology, they enable us to detect epidemics and implement lockdowns faster. Next year, artificial intelligence will be included in the list of technological developments that will enable us to respond more effectively to the epidemic.

 

 

The number of scientific and medical literature alone has increased significantly, with more than 28,000 papers related to the new coronavirus published before April this year.

 

 

Work is still underway to develop artificial intelligence solutions to help deal with a large backlog of other medical problems such as cancer. The treatment of these diseases has been affected by the transfer of resources to fight the new coronavirus. Next year, we are likely to see the accelerated adoption of artificial intelligence in many other medical fields, not just in response to viruses.

 

 

By developing our ability to apply machine learning problem-solving technology to these large, real-time global data sets, we will find it easier to detect the epidemic, track close contacts, achieve more accurate diagnosis, and predict the possible future evolution of the virus to develop more effective and durable vaccination.

 

 

2. Automatic detection and prevention

 

We have seen the use of drones in several jurisdictions, including the United States, to at least test whether drones may be used to monitor whether people are complying with social distancing guidelines. More advanced applications are about to emerge-such as drones that can detect fever and other symptoms of new coronary pneumonia in a crowd. These systems use computer vision technology to analyze the data obtained by the cameras on the drones and notify relevant departments or local managers of the statistics and probability of virus transmission.

 

 

Another related area of development will be the use of facial recognition technology, which is also powered by computer vision algorithms. One of the more controversial aspects of facial recognition is that it focuses on identifying patterns in individuals, rather than crowds, so the police use this technology to find people evading lockdowns and quarantine, and to track the activities of individuals with symptoms in the crowd.
3. Predict behavioral changes

 

The way we live, work and socialize has been greatly affected by the spread of the new coronavirus. Although there has been a stable and strong digital trend in many aspects of society, this year we have witnessed an upsurge.

 

 

Amazon’s sales in the second quarter of 2020 increased by 40% over the same period last year, and even companies that have so far avoided online retail are forced to re-evaluate their options.

 

 

Artificial intelligence tools and platforms are already helping companies understand how customers adapt to new realities. Institutions that have previously lagged in the adoption of digital channels in business and relationship training have gradually realized the urgency of this situation and are quickly grasping concepts such as behavior analysis and personalization.

 

 

In 2021, tools that allow organizations to acquire this technology on their own will become more and more popular, as small and medium-sized enterprises are seeking to build their own competitive advantage.

 

 

4. Eliminate the next epidemic in its infancy

 

Most artificial intelligence algorithms are aimed at prediction. The nirvana of artificial intelligence-assisted epidemiological research will be to establish a system that can accurately predict when and where future epidemics will break out.

 

 

This research has been going on for some time, in fact, some of the earliest warnings about the current epidemic are generated by artificial intelligence.

 

 

We can expect that artificial intelligence research will make further breakthroughs in the next 18 months, thereby improving our ability to detect and respond to the danger of virus outbreaks. However, to achieve this, continuous global cooperation between governments and private companies is also needed.

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