Oscar Wilde once argued that life imitates art more than art imitates life. Strangely, that’s proving to be the case when it comes to AI development – but not in the way some had hoped.

A Production Problem (Solved)

When Henry Ford attempted to produce the Model T at a rapid pace and with high quality, he ran into a problem. It was difficult to organize teams of specialized workers to assemble automobiles, and with so many workers needed to scale the process, it was highly inefficient. To make matters worse, late delivery of parts caused pile-ups of workers vying for space to work and delays in production.

As the volume of the world’s big data grows at a staggering speed, so too does the need for people who know how to extract knowledge, insights, or solutions from it. Today’s data scientist must have both the technical skills to solve complex data problems and the curiosity to seek out the hidden problems data can solve.

Digital experts often compare data to oil. It’s immensely valuable, though mostly hidden. You need resources to mine it and experts to refine it. And, most importantly, it must be handled with extreme care to prevent the worst-case scenario: a massive spill.

Google’s three-day I/O’18 conference in Mountainview, Calif., last week brought together developers from around the globe for hands-on learning, discussion with experts, and a look at Google’s latest developer products. The conference also featured Google I/O Extended sessions held in technology hubs across the country, including a panel discussion that featured CloudFactory Chief Revenue Officer Mike Riegel.

CloudFactory invites tech disruptors to enter the fifth annual AIconics Awards at 2018 London Tech Week. AIconics is the world’s only independently judged artificial intelligence (AI) award program. The ceremony, to be held at Kensington Palace on June 12, celebrates the best in AI and innovation that is taking shape around the globe.

Data is today’s gold for businesses, representing huge potential value. But there’s a catch: the data must be uncovered, clean, and structured.

Our latest client success story shares how Ibotta, a cash-back rewards app, partnered with CloudFactory to improve accuracy and processing time on its important data-verification work. Retail consumers use Ibotta to submit photos of receipts for cash-back rewards from brands. With nearly 22 million downloads, it is one of the most frequently used shopping apps in the United States.

For all of AI’s promises, we still need people to do a lot of work behind the scenes to make it all possible. People collect, enrich, clean, and prepare data for AI systems to operate accurately and optimally. In fact, data scientists spend countless hours cleaning and combining datasets, a process commonly referred to as “data wrangling.”

Earlier this month, The Tech Tribune recognized CloudFactory as one of the 10 Best Tech Startups in Durham. The list of tech startups based in Durham, N.C., was the result of research on each company’s revenue potential, leadership team, brand and product traction, and competitive landscape.