The headway of Reinforcement Learning (RL)

Reinforcement Learning is a special application of deep learning technology, where the software is learning and improving from its own experiences. This is a type of dynamic programming using a system of reward and punishment, with which we can train an algorithm or an RL agent that fulfills given conditions. The agent or algorithm seeks to complete the tasks more and more correctly, to minimize its penalty and maximize the rewards. This way, the algorithm learns by interacting with its environment, and can reach an expected goal which fulfills the conditions, by itself, without any human intervention.

A useful example of the application of reinforcement learning is the operation of chatbots. With applying the technology and adding appropriate sequential conditions, we can get more resourceful chatbots. Not only could these chatbots do order booking, greeting or consultation calls, but also recognize potential customers or transfer calls to the relevant service agents.  This technology doesn’t only mean a breakthrough in the field of chatbots, it is optimal either for industrial automation or for business strategy planning.

The combination of Internet of Things (IoT) and Artificial Intelligence

We have been using the phrase Internet of Things for years now, and IoT devices can be found at more and more scopes. The phrase is basically used for the separation of physical devices, that can be connected on a network and on the network, they can communicate with each other. With the usage of IoT devices, a business can lower the expenses and can optimize its resources. Among other things, it is really useful and practical for freight monitoring or asset management, but also for adjusting the energy consumption of a building. Due to the communication between the devices, we can monitor the processes so that the process optimization becomes easier, and the company could securely plan for the future. We can see, that the IoT is capable of loads of things and offers many opportunities just by itself too, and the technology has great potentials to look for, but by leveraging IoT and AI technologies (AIoT), we can benefit even more from it. 

With the combination of the two technologies (which is called the Artificial Internet of Things), it can be possible to get real-time information and to monitor the performance of the connected devices. With this, and with the continuous information analysis, both on-site and remote machine fault detection could become easier, and industrial predictive maintenance can come true. Predictive maintenance can not only make the job of technicians easier, but can also contribute to the existence of modern and future factories.

The spread of hybrid workforce

Intelligent Process Automation (IPA) is closely related to Robotic Process Automation (RPA), which is able to complete given tasks automatically by using artificial intelligence. More and more companies invest and implement both technologies, because the application brings many benefits such as maximizing workforce efficiency and cost-effectiveness. Because of the COVID-19 pandemic, many businesses had to change for online work and coordination and at most companies they want to minimize personal contacts, and these all can influence and boost the spread of RPA and IPA. RPA and IPA software robots’ work can be managed remotely, they work process is calculable, and can replace human workforce. The more fields and scopes use RPA and cognitive artificial intelligence, the closer we get to the realization of modern workplaces and hybrid workforce. Be prepared for working with digital assistants in more and more jobs and note, that software robots will support our work process more and more often.

Improvements of cyber security

In the last few years, companies placed an important emphasis on the improvement and maintenance of cyber security, and for all this, they use the opportunities provided by AI. At the same time, the quantity of data in the clouds is growing continuously and therefore data access becomes easier, and unfortunately, data breaches and phishing attacks are more and more common. Besides these, the number of digital transactions is also growing constantly, so as the number of financial frauds and fraudulent transactions. But with the advanced application of AI, these crimes can be predicted and prevented at the right time. Artificial intelligence based cyber security systems can follow and monitor digital transactions and actions, and they are able to learn the occurring nefarious patterns. By recognizing these patterns, they can distinguish dangerous cases so the possible attacks can be foretold and prevented. In the upcoming year, we have to watch out for the improvements and widespread of cyber security systems.

Overall, many promising developments are expected of artificial intelligence in 2021 and these improvements will have a great impact on several economic sectors and workplaces, so the trends and actualities will be really worth following.

Source: techopedia, neptune.ai, Analytics Insight