In this week’s roundup, we take a look at how STEM education is important for businesses in both hiring and training. We examine how AI (artificial intelligence) has the potential to improve in-vitro fertilization. We learn that data analysts need platforms—not just tools—to scale AI projects. Also, we look at how the coronavirus pandemic is forcing changes to the fundraising ladder for nonprofits.
by Renata Ramirez, contributing writer to SanDiego.edu
To be competitive, companies need rich and rigorous data in order to understand the actions of their customers, employees, and operations. The process of gathering and using this data is called business analytics. Companies that leverage business analytics can identify inefficiencies, solve problems, and measure success at a much faster and more accurate rate than humans can qualitatively. STEM fields are essential in business analytics, particularly statistics and data science. Businesses need people skilled in these areas in order to implement and reap the benefits of business analytics.
by David Sable, contributing writer for Forbes.com
Artificial intelligence is revolutionizing many areas within healthcare, including fertility treatments such as IVF (in-vitro fertilization). IVF technology is only about 40 years old, and the results are inconsistent and difficult to predict. Now doctors are using AI to identify which embryos are most likely to result in a pregnancy and to determine the ideal hormone levels for each woman. There are some hurdles to overcome before the technology becomes widely available. For example, the AI needs to learn at a larger scale, meaning more clinics need to use it. However, most clinics currently use different measurements for rating embryos, and more would need to adopt the AI technology to generate the “big data” that would make a significant impact on IVF.
by F. Duke Haddad, contributing writer for NonprofitPro.com
Many things regarding nonprofits’ donor outreach have been upended by the coronavirus pandemic—including the fundraising ladder of effectiveness. In the past, the ladder included steps that simply aren’t possible right now, such as personal meetings, crowded fundraising events, and door-to-door canvassing. Since personal connection is so important for effective fundraising, nonprofits need to rethink the ladder to adjust to social distancing without losing that personal touch.
by Joao-Pierre S. Ruth, contributing writer for InformationWeek.com
A recent survey by HackerEarth showed that working developers are feeling left behind as machine learning becomes increasingly necessary within enterprise companies. They see new graduates and students with the new programming skills needed for the modern world of data, which is becoming to be dominated by artificial intelligence and machine learning. Organizations should consider investing in additional education for these working developers, as 70% of them said they are unhappy with their jobs as they feel pressure from the changing needs of their companies.
by Jessica Davis, contributing writer for InformationWeek.com
Machine learning and AI are powered by open-source tools, programming languages, and libraries. But these tools are not enough to efficiently manage large-scale projects. Data analysts need a robust AI platform in order to manage and coordinate these. By using a machine-learning platform, organizations can scale their data analysis and use the results to reduce costs and improve efficiencies, making the investment well worth it.
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