摘要： If your business is focused on data-driven, fact-based decisions, your business users may be leveraging an analytics solution to gather, find, and analyze data. Business goals include improving results and productivity and getting the best results out of your data, as well as gaining meaningful insight into data. But, you certainly want to accomplish all those goals without frustrating business users or forcing them to adopt tools that do not add value to their day-to-day workflow and tasks.
摘要： Customized protein design is now possible because of artificial intelligence (AI), which can be used to address both medicinal and environmental issues. A team at the University of Bayreuth has effectively used a computer-based natural language processing model for protein research under Prof. Dr. Birte Höcker.
摘要： Analog deep learning, a new branch of artificial intelligence, promises quicker processing with less energy use. The amount of time, effort, and money needed to train ever more complex neural network models is soaring as researchers push the limits of machine learning.
摘要： Numerous examples of machine learning show that machine learning (ML) can be extremely useful in a variety of crucial applications, including data mining, natural language processing, picture recognition, and expert systems. In all of these areas and more, ML offers viable solutions, and it is destined to be a cornerstone of our post-apocalyptic civilization.
摘要： With the massive growth of machine learning (ML)-backed services, the term MLops has become a regular part of the conversation — and with good reason.
摘要： In addition to the well-known security challenges faced by devops teams, organizations also need to consider a new source of security challenges: machine learning (ML).
