Diagnosis: Deep learning can help diagnose COVID-19 through imaging techniques like CT scans, X-rays, and MRI. Deep learning models can be trained to detect COVID-19 features in these images, which can help doctors make quick and accurate diagnoses. Drug discovery: Deep learning can help in drug discovery by predicting the effectiveness of existing drugs against COVID-19 and identifying potential new drugs that can be developed to fight the virus. Deep learning models can analyze large datasets of chemical compounds to identify those most likely effective against COVID-19. Disease tracking: Deep learning can help track the spread of COVID-19 by analyzing data from various sources like social media, news reports, and government databases.

This seems the only suitable word to assess the huge amount of data being generated due to the ensuing COVID 19 pandemic and the global lockdown caused by it. We can broadly classify the data into two categories – Deliberate and Non-Deliberate. The first category of the data is being generated by governments as part of their response plan to the pandemic while the second category of data is being automatically generated due to the global lockdown. As the governments have well-defined objectives to create and use the data they are generating to control the outbreak of COVID 19 in their respective territories, this category of data is immediately being used in their outbreak response plans such as communication campaigns, diseases prevention, social distancing, awareness campaigns, diagnosis, prognosis, and treatment with the help of AI (Artificial Intelligence) based technological innovations particularly mobile apps, dashboard, websites, etc. In addition to the urgent disease containment plans, the first category of data will also be crucial for assessing health systems, developing pandemic/epidemic/outbreak resilience plans and assessing economic impacts to improve future resilience. However, the collection and use of the second category of data is likely to guide the national and global policies for the years from transport planning, supply chain management, global warming, carbon emission, climate change, biodiversity, regional cooperation, geopolitics and much more.

The bio-tech industry is developing at an accelerated rate with the advancement of Artificial Intelligence. The hopes of creating smart cities, extending life spans, cloning, printing organs and body parts are within the horizon. Tech companies have connected themselves with governments, law enforcement, education, media and celebrities to bring forth their vision of the Fourth Industrial Revolution to the populous. Something I described in my recent book The Great Reset: How big tech elites and the worlds people can be enslaved by China CCP or AI. The issue with the Fourth Industrial Revolution or The Great Reset is lack of ethics.

Artificial Intelligence tools and applications have skillfully tried to manage the analysis, diagnosis, tracing, and development of the pandemic in ways unthinkable with manpower solely. The greatest dilemma with this pandemic was that no one knew what it was and how it would react during the beginning of the pandemic. To make matters worse, Covid 19 has been rapidly mutating since its start, and researchers around the world aren't still quite prepared to interact with such a delicate mutating variant that has claimed hundreds and thousands of lives and has essentially changed the course of history forever. This is where AI's prowess comes into play. With deep learning and the combination of researchers from all around the world, Artificial Intelligence has helped us combat the pandemic in unimaginable ways. The foremost task of AI was to collect as much data as possible about the Coronavirus.

Artificial Intelligence (AI) is a branch of computer science that helps build smart machines. AI provides data that makes these machines capable enough to match human intelligence. As a result, many industries have taken advantage of AI technologies. Machine Learning and Deep Learning are the two subsets of Artificial Intelligence. Whereas machine learning refers to computers able to think and act with less human intervention, deep learning involves computers able to use structures modeled on the human brain.

Taking many efforts, large number of predictive technical tools like artificial intelligence, Machine Learning were developed. None of them made a major difference & some were found potentially harmful to human body. Few months back, the Turing Institute, It's in UK as a national center for technology, machine learning, data science and artificial intelligence, kept out a report summing up discussions at a series of workshops and seminars it held in late last year ( in 2020). The clear consensus was that artificial intelligence and Machine Learning tools had made little, if any, impact in the fight against corona virus i.e. covid 19. Two major studies that assessed hundreds of predictive tools developed last year.

A confluence of advances in biological science and accelerating development of computing, automation, and artificial intelligence is fueling a new wave of innovation. This Bio Revolution could have significant impact on economies and our lives, from health and agriculture to consumer goods, and energy and materials. Some innovations come with profound risks rooted in the self-sustaining, self-replicating, and interconnected nature of biology that argue for a serious and sustained debate about how this revolution should proceed. Accidents can have major consequences--and, especially if used unethically or maliciously, manipulating biology could become a Pandora's box that, once opened, unleashes lasting damage to the health of humans, ecosystems, or both. The risks are particularly acute because many of the materials and tools are relatively cheap and accessible. Moreover, tackling these risks is complicated by a multiplicity of jurisdictional and cultural value systems, which makes collaboration and coordination across countries difficult. While the impact of COVID 19 was still unfolding at the time of writing in April 2020, bio innovations had been deployed to aid the response.

Owing to the COVID 19 pandemic, healthcare institutes are readily adopting artificial intelligence-based solutions for an effective outcome. It may seem that COVID 19 has initiated this adoption, but over the past few years, healthcare institutes have taken cognizance of this nascent technology. Due to its ability to analyse and process large datasets, healthcare institutes are deploying AI-models to make data-driven decisions. Big techs like IBM and Google are leveraging their respective products towards proactive data-driven healthcare advancements. For example, IBM Watson Health is a comprehensive product created to solve major health challenges using data, analytics and AI.

Artificial Intelligence and Machine learning solutions help B2C enterprises in deriving best strategy for business growth. Artificial intelligence and its subsets are driving the pace of digital transformation across global B2C enterprises. Even before the COVID 19 outbreak halted business operations, disruptive technologies such as AI, machine learning and natural language processing were getting promptly adopted across the industry. A report by the United Nations Conference on Trade and Development (UNCTAD) states that the digital economy contributed 15% to the global GDP in 2017. With COVID 19 outbreak, many factors thwarted efficient business operations.

Currently, the world is facing the most challenging time and going through economic turmoil. One of the important priorities of many companies is to recover quickly from the current scenario and be operational as quickly as possible. The coronavirus has impacted many companies and this economic hit is very fast throughout the world. Companies around the globe are looking for stabilizing their business and the recovery. According to the Organization for Economic Co-operation and Development of the reports released on 14th April, consumer expenditure has dropped more than 25% in Canada, France, and Germany in many majority economies, thus causing the slowdown between 20-25%. The Machine Learning (ML) and Artificial Intelligence (AI) can play a major role in the business recovery after and during the COVID 19 pandemic.