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Amid the boom of AI in application building, companies face a significant data-labeling problem, especially when it comes to labeling images or other media content they want to train deep learning ...

The shift to remote work and dispersed global operations at life science firms has forever altered the regulatory market. We’ve seen an increase in the speed with which the industry is adapting to new ...

How should meat grown from cultured animal cells be labeled? In a joint FDA/USDA webinar, officials said they would work together to come up with joint principles to govern the labeling of products ...

Data labeling software is crucial in developing artificial intelligence (AI) systems. It is designed to label and annotate data in a consistent and standardized manner, just like in a commonly known ...

Traditional labeling-development techniques can put a drain on manufacturers’ resources — and that’s before a decision is made on which information is needed and will fit on the label. Electronic ...

One of the more tedious aspects of machine learning is providing a set of labels to teach the machine learning model what it needs to know. Snorkel AI wants to make it easier for subject matter ...

Organizing data labeling for machine learning is not a one sitting job, yet a single error by a data labeler may cost you a fortune. Now, you probably wonder how do I ...

As machine learning has grown, one of the major bottlenecks remains labeling things so the machine learning application understands the data it’s working with. Datasaur, a member of the Y Combinator ...

Accurate labeling of penicillin allergies is essential, but unconfirmed penicillin allergies may have negative effects on individual and public health, according to experts. A trend toward ...