An interview with Dr. Jean-Claude Junqua It seems like articles about Chat GPT, Bard, and Generative AI (Gen AI) appear almost daily. We caught up with Sigma’s Executive Senior Advisor, Dr. Jean-Claude Junqua, to discuss what goes into the development of these technologies and the future of generative AI. What are some of the use […]
With businesses looking for more and more data to enable machine learning, many are turning to synthetic data to fill in the gaps.
There are many different types of learning that you may encounter as a practitioner in the field of machine learning — here are some of the most important.
Any given machine learning workflow defines which phases are implemented, and how, during a ML project.
Conversational AI is the synthetic language and brainpower that makes human interactions with machines more effective and natural.
Data preparation is a critical step in ensuring data is clean, usable, and properly interpreted for use in machine learning.
Human in the loop machine learning refers to models that reinforce the information produced by ML with constant human influence.
In machine learning, data labeling is the process of adding labels to raw data in order to provide context for a machine learning model.