The Curious Case of Data Annotation and AI
Data annotation takes time. And for in-house teams, labeling data can be the proverbial bottleneck, limiting a company's ability to quickly train and validate …
Looks at issues related to artificial intelligence technologies, including cognitive computing, deep learning, and machine learning. Considers also supervised and unsupervised learning and natural language processing.
Data annotation takes time. And for in-house teams, labeling data can be the proverbial bottleneck, limiting a company's ability to quickly train and validate …
A systematic AI approach used against fraud, waste, and abuse not only uncovers specific instances, but often provides additional
AI is becoming a technological norm to advance and modernize existing digital infrastructure, now the real question is, “what’s standing in my
Emotion recognition is being used for education, policing, and recruitment, yet the technology is considered by many experts to be unreliable and may lead to …
Combining intelligent video systems with AI to analyze and react in real-time lets companies automate and optimize workflows to increase business
The AI Ladder, along with CRISP-DM, provides a strategic approach to creating CI applications on real time
Building continuous intelligence applications on cloud-native architectures using containers and Kubernetes makes it easier to deploy, maintain, and update …
Incorporating machine learning capabilities into BI solutions will bring sophisticated analytics to more people, groups, and business
Previously, the way to identify these disorders would be through manual scoring, which is time-consuming and can lead to inaccuracies.
With AI becoming more prevalent, it’s clear that a platform that can manage the complete AI development and production life cycle will become more