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3 technology trends that will accelerate the development of COVID-19 in 2021



The 2020 spending in the shadow of the pandemic has affected our needs and expectations for technology. For many people, COVID-19 has accelerated the pace of digital transformation: As employees work from home, companies need AI systems that can facilitate remote work and support their computing power.

The question is, how should companies concentrate their resources in 2021 to deal with this changing reality and upcoming new technologies? I predict the following three trends will attract widespread attention in 2021 and beyond.

1. Artificial intelligence must become practical

The advancement of artificial intelligence has reached the point where it can add significant value to almost any business. Due to the need for remote solutions, COVID-1

9 has triggered a strong sense of urgency around digital transformation. According to a report by the Boston Consulting Group, more than 80% of companies plan to accelerate their digital transformation, but only 30% of digital transformations have reached or exceeded their target value.

Many AI projects are small-less than a quarter of companies in McKinsey’s 2020 AI state report a significant bottom line impact. This is especially true in industries with physical and digital elements. For example: in the COVID-19 era, remotely operated autonomous production facilities, refineries, and even office buildings are very much needed. Despite the existence of basic technology, achieving scalability is still a problem, and digital leaders will have to overcome this obstacle in 2021. Scalability barriers include lack of a standardized approach, enterprise-wide thinking, trusted partners, data fluidity, and change management.

Part of the solution is to create a solution that will be operated by people who are not necessarily data scientists, so that more domain experts can manage the required procedures. What’s the point if Tesla invented self-driving cars that only data scientists can drive?

Technology needs to empower end users so that they can interact with and manipulate the model without having to explore the subtleties of data sets or code—in other words, AI will do the heavy lifting on the backend, but with user-friendly explanations UI empowers the end user. For example, facility management executives can manage their global building portfolio by sitting on a tablet computer at Starbucks. They can fully understand the operation, occupant’s experience and costs, and have the ability to intervene in operations that are originally autonomous.

2. Through deep learning, solutions become more autonomous

Dr. Geoffrey Hinton, a pioneer in deep learning, recently told the Massachusetts Institute of Technology Review that deep learning will be able to do “everything”, that is, copy all human intelligence. Deep neural networks have shown extraordinary ability to approximate the most relevant subset of mathematical functions and are expected to overcome inference problems.

However, I believe we must first conquer the step of complete autonomy: Dr. Manuela Veloso of Carnegie Mellon University calls it symbiotic autonomy. With symbiotic autonomy, feedback and correction mechanisms have been integrated into AI, so that information can be smoothly transmitted between humans and machines.

For example, symbiotic autonomy can replace virtual assistants on the phone for discussions to determine the best route to a destination without having to provide help like hard feedback (such as adding power to the Netflix queue). Interactions with these forms of AI will be more natural and conversational, and the program can explain why certain actions are suggested or performed.

Through deep learning, neural networks can approximate complex mathematical functions with simpler functions, and their ability to take into account more and more factors and make more informed decisions with fewer computing resources makes them autonomous. I expect to fully study the capabilities of these deep neural networks from start-up companies to top high-tech companies to universities.

This step towards a fully autonomous solution will be a critical step in the large-scale implementation of AI. Imagine an enterprise performance management system that can provide you with a pane of visibility and control in a global enterprise that can automatically run multiple facilities, workers, and supply chains. It can run and learn on its own, but you can intervene and teach when you make a mistake.

(Ethical issues in autonomous systems will come into play here, but this is the subject of another article.)

3. The promise of curing future epidemics will accelerate research in quantum computing

Quantum computers have the ability to process solutions in parallel rather than sequentially, and therefore have the computing power to process complex algorithms. Let us consider how this will affect the development and delivery of vaccines.

First, in the drug discovery process, researchers must simulate a new molecule. For today’s high-performance computers, this is a huge challenge, but this problem makes quantum computers finally stand out among them. Quantum computers can eventually map to molecular “quantum systems” and simulate binding energy and chemical transition strength before anyone even has to make drugs.

However, artificial intelligence and quantum computing can not only provide vaccines, but also provide more services. The logistics of manufacturing and delivering vaccines face huge computational challenges, which undoubtedly make them mature, requiring solutions that combine quantum computing and artificial intelligence.

Quantum machine learning is a very promising emerging field, but it needs a breakthrough to attract the attention of investors. Technological visionaries have begun to see how it will affect our future, especially in understanding nanoparticles, creating new materials through molecular and atomic maps, and glimpsing the deep structure of the human body.

The area of ​​growth that I am most excited about is the research intersection of these systems. I believe these intersections will start to combine and produce more results, rather than the sum of the individual parts. Although there is some connection between AI and quantum computing or 5G and AI, all these technologies work together to produce exponential results.

I am particularly happy to see how AI, quantum and other technologies will affect biotechnology, because this may be the secret of superhuman abilities-what could be more exciting than this?

Usman Shuja is the general manager of Honeywell (China).

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