Last Updated on November 27, 2022 by Faiza Murtaza
The years 2020 and 2021 have changed the way we look at our workplaces. Digital and remote work has become much more prominent while the concept of physical workplaces has started to demand a rethink. It was said that major pipelines of the economy would migrate to the digital environment and the need for Artificial Intelligence and related technology would become much more important than ever before.
As we stroll along a technological roadmap, the need as well as the demand for AI courses increases. When we look at applied AI courses, Google reviews suggest that such courses would reach the pinnacle of their popularity in the next five years.
That said, artificial intelligence has reinvented itself as a technology in the post-pandemic era. It is now used for vaccine trials as well as vaccine development and treatment of various diseases and ailments. Autonomous driving or self-driving cars that ferry only a single passenger due to covid 19 restrictions and advanced chatbot technology that caters to the grievances of customers are recent highlights of AI technology.
Let us understand such post-pandemic developments in artificial intelligence in some more detail.
How did AI fast-tracked the development of new vaccines?
Vaccine development is a very long process and takes many years to complete. There are usually three stages to vaccine development. Each stage takes no less than a year to get completed. However, with the help of artificial intelligence technology, we were able to analyse large data sets about Coronavirus from different countries of the world. With the help of artificial intelligence models, it also became possible to fast-track the process of data examination and vaccine trials from different countries of the world. In addition to this, artificial intelligence models also made the analysis of the sub-components or the proteins of the virus possible in a short span of time. The application of artificial intelligence technology in the genetic domain made it possible to create vaccines within one year of the first reported case of Coronavirus.
When we look at the technical aspects of artificial intelligence technology, we understand the relevance of the linear fold AI algorithm that proved very handy for medical teams around the globe to examine the sequence of ribonucleic acids. The linear fold algorithm made it possible to examine and predict the secondary structure of the ribonucleic acids as well as the possible mutation that it undergoes. With the help of this algorithm, we were also able to predict the human immune response that would be generated on exposure of the human body to the inactivated virus. This reduced the time span between the development of the virus and its approval by the regulating bodies.
How self-driving cars become the new normal for ferrying passengers in covid restrictions?
Although the technology of autonomous vehicles was already under development for the last five years, it found a great fit with the situation created by the Covid 19 virus. Passengers needed to be ferried from one place to another and driverless cars proved to be the perfect mode of transportation for doing this without any chance of infection from another person.
When we look at the technical aspects of driverless cars, we find that artificial intelligence has been able to conceive a reinforcement learning system within the vehicle that is able to learn from the environment so that the driving experience can be improvised in the long run. With the help of artificial intelligence, the safety aspects of the vehicle have also been addressed. It has become possible to connect the driverless car with the internet of things as well as satellite technology so that multiple safety levels can be created. The vehicle can also make a sense of the traffic up to a few kilometres and plan the ride accordingly. It is also possible to create a safety factor on the upper driving limit of the vehicle.
In addition to this, new innovations in the form of a 5G remote driving service are in the final stage of testing. Furthermore, we have also seen the commercialisation of the technology of self-driving vehicles in Singapore as well as China. The Apollo go Robo taxi service has been launched in several cities in China and trial operations have concluded successfully. This is a positive sign for conceiving a full-fledged fleet of Robo taxis in the time to come.
How has the advancement in chatbot technology led to an effective grievance redressal mechanism?
In the post-pandemic era, there has been a renewed impetus for chatbot technology. The artificial intelligence technology that operates behind a chatbot is natural language processing. With the help of Natural Language Processing, we are able to analyse the various aspects of human language like intent as well as emotions. In addition to this, natural language processing technology is able to power the most sophisticated chatbots that can be used for communication with humans through digital channels. This technology is extremely important in various industries that interact with customers through a digital interface. The business process outsourcing industry, as well as the telecommunication industry, are the most important industries where chatbot technology finds its application.
Since the Covid 19 virus, there have been constant innovations in chatbot technology as well as Natural Language Processing. The aim is to conceive the next generation of chatbots and virtual assistants that can communicate with humans by understanding sentiments, emotions and even linguistic patterns. One of the most important breakthroughs has come in the form of a novel framework for natural language generation called ERNIE-GEN. With the help of semantic modelling techniques that are used by ERNIE-GEN, it has become possible to maintain a human-like flow in dialogue engagement and question generation.
How has the field of quantum computing witnessed significant advances with AI technology?
Quantum computing has been our answer to the most complex computational tasks and the derivation of their solutions in a short span of time. This technology makes use of qubits that can simultaneously hold both values of zero and one and is a huge advancement over the erstwhile binary technology that we followed in computing operations. With the help of quantum computing technology, we have been able to process the largest amount of information possible and run various cloud processes simultaneously in real-time.
Deep learning algorithms have played a great role in the advancement of quantum computing research. The next level of quantum computing would become possible once this technology is integrated with artificial intelligence. One example of this is the launch of paddle quantum which allows researchers to train Quantum neural networks with a lot of ease.
In addition to this, we may witness further development in the field of Quantum computing as researchers line up to launch Quantum leaf. Quantum leaf provides such a type of development toolkit to researchers that can enable them to work in cloud-based Quantum computing ecosystems and also reduce the time span of quantum programming.
Conclusion
Further innovation would be seen in the form of artificial intelligence devices like artificial intelligence chips that would be designed to perform specific tasks. A large number of companies have already started to make major breakthroughs in AI technology and further innovations and developments are in the pipeline.
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