The field of Artificial Intelligence encompasses all possible approaches to simulating intelligence. Machine learning, one branch of AI, uses data and experience to train algorithms automatically. Deep learning, a sub-field of machine learning, in turn uses algorithms (called neural networks) to simulate the learning process.
If I were to ask, “Do LSPs play a role in in-country review?” you would probably reply with another question, “Why are you asking this?” Translation buyers that choose an in-country review usually have local offices branches or representatives in specific countries to whom they can entrust this task. And these buyers are typically large organizations. So, how can LSPs contribute to an efficient in-country review?
This is the first of the 3-part series “The Robot Spoke” by Dr. Patrice Caire, AI & Social Robotics Consulting Scientist. The Robot Spoke: But What
As an LSP or a manager of an in-house localization department, how will you translate this “secret” into everyday practice? In this article, we summarize 5 strategies to help you keep up with the basic principles of quality management and hit the ground running toward high performance.
After analyzing the advantages of moving your translation business to the cloud and offering a general roadmap to implement a cloud platform, now we want to discuss the importance of centralizing and organizing data in a cloud-based translation management system.
Nowadays, cloud migration is at the top of every CEO’s agenda. And if it isn’t, it should be: The growth and the diversification of your business require a digital transformation that is not limited to the simple use of state-of-the-art technologies, such as neural machine translation (NMT). This necessary digital transformation should also be built around solutions for the highest productivity, the best operational efficiency, cost reduction, and greater flexibility.
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