Natural Language Processing (NLP) is an area of artificial intelligence that focuses on helping computers understand human language, interpret it, and generate human-like language. For example, machine translation is one of NLP disciplines, as it focuses on interpreting what happens in a language to transfer the message to another language.
Artificial intelligence (AI) and machine learning (ML) models are transforming the way we live and work. From powering our search engines and social media feeds to recommending products and diagnosing diseases, AI and ML are becoming increasingly essential to our everyday lives. But how do these powerful models work? At
Artificial intelligence (AI) is fast becoming a daily tool in our daily lives, not only transforming the way we live and work, but also how we humans interface with machines and with each other. We are offering this AI Training Data Guide because as AI continues to advance, it’s crucial
Machine translation (MT) has been a popular branch of NLP and, by extension of AI in general. It has come a long way in recent years thanks to the advent of neural machine translation and since 2023, GenAI or LLM translation. Nevertheless, it still has some way to go, particularly
Machine translation (MT) systems, particularly Neural Machine Translation and LLM translation, have made enormous progress in recent years, allowing for seamless communication between different languages. However, to truly capture the essence and nuances of language, it is essential to include idiomatic expressions in the training process. Idioms are an essential
As we continue to embrace globalization and digitization, machine translation systems (MT) are playing an increasingly pivotal role in our interconnected world. By breaking down language barriers, these sophisticated tools foster cross-cultural understanding and facilitate seamless communication. However, as is the case with any technology, MT systems aren’t without their
Planning to gather or build parallel corpora for an array of languages and dialects such as Traditional Chinese, Hong Kong Chinese, Taiwanese Chinese, Thai, Burmese, Laotian, and Vietnamese is a task that is fraught with numerous challenges. Scarcity of resources combined with the linguistic and cultural nuances unique to these
Apple Translate, like other machine translation systems, relies on a large amount of high-quality, parallel corpora for ML that is designed to train and improve its translation models. This data consists of the same text in two or more languages, aligned so that the system can learn correspondences between linguistic
We’ve fully entered the era of artificial intelligence (AI) and data has emerged as the fuel that drives innovation and transformative change in all industries. The quality of data plays a pivotal role in shaping the accuracy, reliability, and effectiveness of AI systems. This blog entry explores the multifaceted importance
Large Language Models (LLMs) in artificial intelligence have undergone extensive training with data created by humans, equating to some 20.000 years of human reading on an 8-10 day. This vast amount of knowledge allows LLMs to display human-like personas that sound quite convincing in their responses. This is often referred
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