According to a study by the McKinsey Global Institute, almost all companies use at least one AI technology in their business processes. In the AI generation, the development of artificial intelligence will be closely related to us.
The emergence of AI (Artificial intelligence) has changed the world, and with its widespread application and progress, it has penetrated into our lives and all walks of life. After a whole year of challenges from the new crown pneumonia, the epidemic has clearly become a catalyst, accelerating the application of artificial intelligence technology in various fields. And how will AI develop in the coming years? The following are five trends in artificial intelligence technology in the Future:
1. Use AI to Implement Hyper-Automation
In the face of the epidemic, many companies have made hyper-automation one of the goals of their business operations starting this year, and the IT research and consulting company Gartner has listed the concept of "hyper-automation" as a key technology next year. One of the trends. The so-called "hyper-automation" means that all operations in an enterprise, including its production process, can be automated. The equipment originally operated by software (software package) is changed to a process operated by hyper-automation, which is automated through robotic processes ( Robotic process automation (RPA), artificial intelligence, machine learning, and other technologies allow machines to have the ability to judge themselves and make rapid adjustments in response to data according to different conditions and situations, thereby replicating the work that people participate in in the automation process.
2. Using AI to Solve Cybersecurity Issues
Since the emergence of the epidemic, many companies have implemented a "work from home" model, but at the same time, it has also generated hidden concerns about network security. Therefore, the use of AI to solve network security issues will be a major trend next year. Many companies work in hybrid mode or completely remotely, but the security of relevant information, passwords, and confidential documents are all tested. In the future, AI can be used to identify new attack threats, such as detecting suspicious IP addresses and Potential data leakage can also be combined with blockchain technology to ensure data security and improve remote identity verification. It also allows the company to know who and when the information has been accessed at any time.
3. Further Applications of the Smart Internet of Things (AIoT)
Also, experts predict that next year the Internet of Things (IoT) will be deeply integrated with AI technology, and the definition of IoT will evolve from the Internet of things to artificial intelligence of things (AloT; the Internet of Smart Things), through AI, machine learning, and deep learning technologies. It is expected that the equipment can move towards autonomy and will be specifically applied in the fields of manufacturing and the medical industry.
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The machine production data of the factory can be collected and analyzed by the AI system to enhance production efficiency and efficiency. It can also accurately predict the life and maintenance time of the device. On the one hand, it can improve the safety of the equipment and reduce the temporary shutdown. In the medical industry, AI helps enable data to be applied to the entire medical process, such as the use of faster image recognition to support clinical decision-making, and can even be applied to remote diagnosis, surgical assistance, etc., thereby speeding up smart medical care And the pace of telemedicine.
4. Import Artificial Intelligence Engineering Strategy
The current market lacks industrial-grade support tools, and it is not easy to transform artificial intelligence prototypes into production in disguise. According to Gartner statistics, only 53% of AI projects can be successfully implemented. Therefore, next year’s forecasting technology will also move towards the concept of AI engineering, which means that AI will be introduced into the concept of DevOps (development & operations), integrated engineering strategies with artificial intelligence, and focus on developing, verifying, and deploying various Different machine learning provides enterprises with the best real-time solutions, thereby shortening the development time and strengthening the stability and production efficiency of the AI model.
5. The Moral Controversy of AI Applications
Artificial intelligence technology brings convenience to our lives, but there are also controversial gray areas. The ethical implementation of AI technology will be another key trend in 2021. The deepfake (deep synthesis) technology introduced in the early years uses facial image synthesis technology and deep learning to produce extremely realistic composite images. Therefore, it has been concerned whether criminals will use it to produce false information. And next year, there are predictions that more and more companies will want to add facial recognition functions to internal and customer-facing applications as contactless identity verification.
However, using AI for facial recognition authentication and determining the identity, race, and gender of a person will actually involve sensitive issues such as privacy, discrimination, and monitoring. On the other hand, if companies want to use facial recognition technology, they must also go through the law. Heavy review by consultants.
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