Should you crowdsource your data labeling and annotation?
In the dynamic realm of AI and machine learning, the pivotal role of data labeling and annotation often intersects with
In the dynamic realm of AI and machine learning, the pivotal role of data labeling and annotation often intersects with
Along with “generative AI,” the term “collective intelligence” has been making significant rounds in the business and tech arenas. While
By now, we’re all familiar with the promises of automation: efficiency gains, relief from talent shortages, greater efficiency, and increased
Extraction technologies and automation solutions may be the best combo since “ctrl + c” & “ctrl + v” came onto
Keying in small bits of data that appear on a screen seems simple enough, but finding skilled contributors is absolutely
Behind one bit of technology stands another piece of technology that can make a process happen even more effectively. Our
“Data-driven decision making” is a term we’ve all heard by now, but what happens when the data driving business decisions is inaccurate? It’s no secret that the task of data entry is infamously inaccurate and nearly impossible to scale, but how great is the threat that “bad” data—most often the result of human error—poses to an organization?
Maybe it’s presumptuous to make predictions for the year ahead after 2020 brought us so many surprises, but one thing is certain: the Covid-19 pandemic has profoundly affected the way we do business.
At ScaleHub, we are a high-energy global team of individuals with a significant depth of expertise in document process automation and related technologies. When it came time to create our elevator pitch, we knew we needed to not only help the market understand what it is we do, but also what drives this collective passion of ours.
Crowdsourcing has been cited as the “next big thing” for everything from solving crimes to ensuring the safety of driverless cars. But for those stuck in people-centric back office enterprise challenges [think: application processing or claims management], the question of whether or not to crowdsource complex data processing tasks remains unclear.