Many companies are building machine learning algorithms and despite the challenges this presents, those that are successful have not totally eliminated the human variation. This interesting information came to us from DATAVERSITY in their article, “Machine Learning and ‘Human-In-the-Loop’ Computing.”
The practice is called ‘human-in-the-loop’ computing. It starts with a machine learning model takes a first pass on the data, or every video, image or document that needs labeling. That model also assigns a confidence score, or how sure the algorithm is that it’s making the right judgment. If the confidence score is below a certain value, it sends the data to a human annotator to make a judgment. When the machine isn’t sure what the answer is, it relies on a human, then adds that human judgment to its model.
Semantic technology, artificial intelligence, and machine learning continue to evolve and be used in a variety of applications. It has never been more important to have someone with the expertise and knowledge handling your content, developing your taxonomies, and making your information findable.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
