One can get different answers to this question, but it is widely accepted that the most important piece of the AI and machine learning process is high-quality, secure, human-annotated training data. There are different ways to collect and structure data, with different firms having their own approach.

To close out Women’s History Month, we wanted to highlight some of the powerful women who make up DataForce and their extraordinary contributions to the world of AI.

2021 may have been DataForce’s best year yet.

We've outlined six factors to consider for chatbot deployment.

Learn about the different types of chatbots, how they're being used, and life sciences organization applications.

Here are seven ways that smart AI can help improve the efficiency of your organization, support business growth, and reduce costs.

Companies can make sure their data is ready for AI by creating a unified data warehouse, making company data accessible to all.

Natural language processing and other artificial intelligence applications can help detect adverse events and reduce manual revision of extracted records.

How can you improve your search relevance? Maybe it needs a human touch in addition to the technological factors..

Thanks to artificial intelligence (AI), companies are able to provide a higher level of customer care and support -- and to provide this quality at scale.

Annotation refers to the labeling of any kind of data. When you add labels to your smart phone contacts, you’re annotating data. Labeling makes it easier to retrieve your “favorites” or ignore calls from less-than-favorites.

Chatbots are created for a purpose. Whether it is to entertain the user or to carry out some tasks, it interacts with the user. To build a chatbot, simple hard-coded rules can be written or NLP models can be made use of. In either case, data is the key to success.