Tag: artificial intelligence (AI)

Centific and VMware are two tech giants using GenAI to revolutionize the way businesses connect with audiences around the world. This 14-year partnership — rooted in a shared commitment to ongoing innovation, cost-effectiveness, and continuous quality improvement — has resulted in a nearly unmatched capability to research the potential for AI to transform the localization industry.

OpenAI today announced its Data Partnerships program, which seeks to partner with businesses and organizations around the world

Supported By Lilt Spence Green explains how his experience as a research scientist at Google Translate over a decade ago sparked a grand idea: use AI to make all products and services available in all the world’s languages. Cut to modern day, and his company LILT is hard at work towards that vision. Green spoke with MultiLingual about what’s next for LILT and where he sees the localization industry going.

The French Fintech company Lingua Custodia, a specialist in Natural Language Processing  (NLP) applied to Finance since 2011, releases its new Document Analyser, a...

South Korea’s 14-million-user global language data platform revamps “Flitto Arcade,” its language data collection service, to expand its ventures into the Middle East by...

The Easiest, Most Affordable, and Most Secure Way to Make Meetings and Events Language Inclusive Los Altos, Calif. | October 4, 2023 -- Wordly, the...

In the past few years, the translation industry has undergone substantial changes, primarily driven by the progress made in artificial intelligence (AI) and machine learning. A noteworthy domain that is reshaping the industry is generative AI, a branch of AI that uses advanced deep learning models to create fresh content like essays, images, and even voices. With expertise in generative AI prompt design and engineering, translators can augment their work by leveraging these innovative AI technologies, improving efficiency and accuracy in their many translation tasks.

As neural machine translation (MT) has matured, software developers and users alike are looking for new innovative ways to produce better machine translations. For all the broken promises of “human quality” — except in the easiest of texts — MT has always lacked the ability for users to easily improve and orchestrate the quality they receive. It’s pretty much always been a “you get what you get” experience for most MT users.

The state-of-the-art large language model (LLM) leads to increasingly accurate translations, supporting global expansion while saving time and money for businesses  SAN FRANCISCO – September...