Artificial intelligence solutions market continues to grow rapidly, bringing tens of billions of dollars in revenue. Research Corporation (IDC) 9 to a report released in January, 2023, global spending artificial intelligence systems will reach $ 97.9 billion, a striking increase over this year's expected $ 37.5 billion, which means that in the next few years the growth rate will reach 28.4%. So, 2020 will be a crucial year set the tone for the next decade of innovation in artificial intelligence and to continue the existing momentum.
Next we will introduce six new Research believes AI and Machine Learning Trends in 2020 should be of concern.
Interpretable Artificial Intelligence
With the role of artificial intelligence in organizational decision-making is growing, more and more need-driven application of artificial intelligence to explain how they make these decisions. According to Gartner, by 2025, 30% of government contracts and large enterprises will need these solutions. This means that 2020 will be the foundation for this important year for emerging markets. According to the research company said in data science and machine learning platform, they need to clearly list the accuracy conclude that the use of the property and model statistics. In a separate report, Gartner said that the EU rules and legislation and other general data protection regulations will drive demand for such interpretable artificial intelligence solutions.
Autonomous artificial intelligence
Although autonomous vehicles has been the greatest concern in the autonomous space, but the researchers and technicians in advanced artificial intelligence system continued to make progress, the application of autonomous technology is expected to become more widespread. Gartner said that artificial intelligence will become independent around 2020, one of the top technology trends of the future. This will make things such as collaborative group of drones or robots capable of moving on their own and coordination, automation was once a manual or semi-automatic task. Business use cases include advanced autonomous navigation and agriculture, where the robot can autonomously run a farm.
Artificial Intelligence Security
Gartner said that artificial intelligence will have a significant impact on network security in three key areas. First, organizations will need to ensure that they can not be protected by an artificial intelligence system to prevent such a decision-making system error or leakage underlying data set. According to the research firm said 30 percent of artificial intelligence network will use the training data poisoning, artificial intelligence model theft or harm confrontational sample of artificial intelligence systems. These organizations also need to use artificial intelligence to enhance their security capability, which is already beginning to enter the market the next generation of security products can do. At the same time, they also need to realize that bad actors to implement new network *** how to use machine learning and other artificial intelligence techniques. 
Session Artificial Intelligence
Despite efforts to introduce the conversational AI mass market began a few years ago, but by 2020, this technology will usher in a great moment. For example, next year, Gartner expects 50% will come from the search query analysis, natural language processing or speech query that will make it easier to access analysis system within the organization. In a separate report, the research firm said that 70 percent of white-collar workers will use the platform every day conversation.
Artificial Intelligence Infrastructure
With artificial intelligence affect a wide variety of workloads, artificial intelligence itself play an increasing role in the future of IT infrastructure investment, which is not surprising. According to Gartner, by 2023, artificial intelligence will become one of the main driving forces infrastructure decisions. This is important, because the artificial intelligence workloads require specialized hardware and software configurations, and can continue to manage artificial intelligence model, a special team to help drive operational decisions.
Traditional machine learning is still important
According to Gartner, even enterprises to speed up the depth learning solutions using advanced, traditional machine learning will continue to play an important role. To illustrate this point, the research firm said that by 2022, more than three-quarters of organizations will use the DNN in the case of conventional machine learning have been enough. This means that a business or organization should understand the different machine learning options available to them, as simple as possible, and make sure that the chosen technology for the problem at hand.
