According to Gartner’s recent analysis of the top tech trends for 2017 and beyond, the leading force driving innovation is the rise of artificial intelligence and machine learning. It’s clear that everything from autonomous driving vehicles to virtual reality, robotic medical innovation to gaming will infiltrate and augment how we live, work and play.
“AI and machine learning (ML), which include technologies such as deep learning, neural networks and natural-language processing, can also encompass more advanced systems that understand, learn, predict, adapt and potentially operate autonomously. Systems can learn and change future behavior, leading to the creation of more intelligent devices and programs. The combination of extensive parallel processing power, advanced algorithms and massive data sets to feed the algorithms has unleashed this new era.”
When you look under the hood, machine learning algorithms are only as accurate as the data that feeds them. In other words, ‘garbage in, garbage out.’ Many who are jumping into the AI game underestimate how large their datasets need to be in order to create accurate algorithms. But, what’s even more critical is how well those datasets are categorized, annotated or tagged in order to build accurate ground truth models that form the foundation for solid AI.
CloudFactory is helping some of the most innovative companies in the world create incredibly accurate ground truth training datasets for machine learning algorithms. Whether that’s in the form of annotating images, identifying classifiers, drawing bounding boxes, labeling objects or analyzing text for NLP, we’ve made it super easy to offload that work, which empowers data teams and engineers to focus on innovating the next generation of AI that very well may change the world.