The coronavirus pandemic has ravaged the global economy, and most companies aren’t doing too well right now. There are, however, a few sectors that have actually seen an increase. Gaming and streaming media services have definitely seen a bit more than their fare share of use with so many people being stuck indoors. Another area that is making a come-up right now is machine learning.
Dealing with COVID-19 has been quite the challenge. The virus, and all of the social and economic changes that have come along with it, has increased the pace of advancement of several different trends and technologies. The demand for Artificial intelligence has been much higher as a result.
Since March of this year, the general public has learned quite a bit about stats, figures, and probability. Before the COVID-19 pandemic, the average person were completely lost when it came to large sets of data. The virus, though, really increased the public awareness of statistical results. This makes sense, considering its important to be able to tell if your local infection curve is flattening or not. Due to this and other factors, the average person has taken the time to examine key factors in an attempt to identify the key properties of available information to make a prediction about the virus and it’s impacts. Things like charts, databases, and machine learning our now becoming more understood by the masses.
When it comes down to it, people are simple. In general, people are suspicious of technology because they don’t understand it. These simple folk, though, are now seeing that technology is the ally is obviously is rather than a threat. People all over the world are becoming a lot more familiar with the concept of deploying Artifical Intellegence to assist in a situation.
Certain startups find their niches by examining and predicting the current and future needs within the market. In these industries, the coronavirus pandemic has been somewhat of a good thing. New paths have been opened for growth and innovation. Even older-styled businesses that used to regard innovation innovation as a luxury are seeing now that its a critical tool that
is vital for survival.
It’s not just the scale of innovation and change that is increasing, but also the speed in which those things increase. Take online shopping for example. In January, online orders made up only 13% of total sales. By May, just five months later, that figure had gone up to 80%.
In the unexepected situation that we find ourselves in, machine learning and AI have really shown how valuable they are. In fact, AI has become useful for some things that you may have no thought of. So, here are three areas in which AI has made a large impact.
1. Clunky old-school businesses are having to turn to startups that can provide agile, real-time, machine learning-powered solutions. These older companies are having a hard time transitioning and adapting to the new ecommerce situation, and they need help deploying solutions that deliver optimization while also retraining its workforce.
2. AI startups are helping conventional businesses make changes and adapt to the situation, but dont fool yourself into thinking that they aren’t also struggling with the impacts of COVID-19. The usefulness of old data is one the casualties of the panedmic’s disruptions. The thing is, predictive analysis relies on existing, large datasets. Those datasets are useful in knowing how much of what item needs to be stocked, or when an area of a business is going to expiernce an increase. All that data, though, is based on pre-COVID behaviors and are becoming less and less effective as we move forward into the new normal. One of the biggest challanges is to rebuild data models at a high rate speed, all while dealing with far fewer data points.
3. Given the current environment, the speed that choices need to be made has created new vulnerabilities. Most of the time, large corporations centralize their data to assist in decision making. But at the same time, searching for capital efficiency is encouraging more and more businesses to cooperate with one another with an ever increasing amount of transparency. These are good moves, but they are moves that need to be made carefully as a breach in data would likely have more of an impact bias in the analysis process.
Big businesses are the ones making the effort to reach out, and this transition is creating many critical, large-scale partnerships. All parties, however, need to stay aware that this new environment still probably has a few more challenges up its sleeve.
