This week, we highlight how artificial intelligence (AI) is the key to recession-proof fundraising and driving holiday purchases. We dive into the concept of edge computing with a curated list of helpful articles. And finally, we learn how automated machine learning (autoML) may be the key to paving your organization’s path to AI and the working relationship between autoML and data scientists.
Why Artificial Intelligence Is the Recession-Proof Way to Fundraise
by Kevin Leahy, featured on NonProfitPro.com
All signs are pointing to a potential recession for the U.S. economy. In The Great Recession of 2008, nonprofits took a big hit. But this time around is different, because of artificial intelligence. AI can actually thrive in difficult economic times. Here are three ways AI can empower your organization with recession-proof fundraising.
How AI Will Drive Holiday Purchases
by RJ Talyor, contributing writer for MarTechAdvisor.com
It’s that time of year again… time to roll out your holiday marketing campaigns! This year, AI is shaping up to be one of the biggest marketing trends this holiday season, with more marketers indicating they plan to use AI than ever before. Here’s how incorporating AI into marketing strategies will be the key to standing out, attracting new customers, and bringing in revenue.
Enterprise Guide to Edge Computing
by Cathleen Gagne, contributing writer for InformationWeek.com
Edge computing brings the processing closer to where data is created. And experts are projecting major growth in this area over the next few years: 75 percent of enterprise data will be created and processed outside a traditional centralized data center or cloud by 2025 (vs. 10 percent today). Here’s a collection of articles curated around the topic of edge computing.
Implementing Automated Machine Learning (AutoML)
by Raj Sanghvi for Forbes.com
Automated machine learning (autoML) is the process of applying tools to data to apply the machine learning process to a real-world problem. AutoML systems provide tools and customization options and it makes machine learning available to people without any real specialization. Learn how it works, and what to consider when implementing autoML.
How Automated Machine Learning Tools Pave The Way to AI
by Kassidy Kelley for SearchEnterpriseAI.TechTarget.com
Implementing machine learning and, ultimately, AI, is a complicated process. So is autoML the answer? Enterprises are applying autoML in a wide range of applications, from developing retail insights to training robots. But the real promise of autoML is the ability to collaborate with data scientists, removing a large amount of grunt work. Learn how data scientists can best work with autoML to move towards AI.
Did you see an interesting article in the last week? Share it with us! Send it to astuttle [at] lityx.com.
