Slator Pro Guide: Finding Growth in Adjacent Services
25-page Slator Pro Guide: Finding Growth in Adjacent Services for LSPs helps identify new opportunities for growth. Includes analysis of barriers to entry, synergies, and risks.
NLP
Over 300 Language Experts Made the ‘Most Cited Scientists List’
Public database ranks scientists based on number of citations. Over 300 language experts among the most quoted.
How the Brain Processes Language, With MIT Neuroscientist Ev Fedorenko
MIT neuroscientist Ev Fedorenko on the origin of language, the relationship between language and thought, and how language processing differs between humans and computers.
Here Are the Language Highlights from the Popular ‘State of AI Report 2022’
Snapshot of the most interesting language technology highlights from the latest edition of the State of AI Report compiled by a group of venture capitalists and researchers.
Cohere Co-founder Nick Frosst on Building the NLP Platform of the Future
Nick Frosst on his journey to co-founding Cohere, which aims to become the default platform for NLP development; and what he thinks of the latest breakthroughs in generative AI.
Slator Pro Guide: Finding Growth in Adjacent Services
Pro Guide for LSPs to identify growth opportunities in adjacent services. Profiles 15 adjacent services, analyzing barriers to entry, risks, and synergies.
Unpacking Multilingual Data Management and Anonymization
Anonymization is on a trajectory to enable widespread monetization of multilingual data. Pangeanic CEO Manuel Herranz and CTO Amando Estela tell us how.
Researchers Experiment With Machine Translation to Simplify Medical Language
When researchers experimented with machine translation to simplify medical content for patients, the results were mixed but promising.
Can Machine Translation Facilitate Better Global Meetings in a Common Language?
Computer researchers at the University of Maryland experiment with machine translation to show how global meetings can be optimized.
Yasmin Moslem on Using Large Language Models to Custom Train Machine Translation
Adapt Center’s Yasmin Moslem on how to deploy large language models to generate domain-specific training text for machine translation — and why it matters for LSPs.
Can ‘Huge Amounts’ of Synthetic In-Domain Data Improve Machine Translation?
Machine translation researchers at Ireland’s Adapt Center propose a new approach to domain-specific MT training using back-translation for data augmentation.
Automation Leader UiPath Bolts On Text Mining Startup Re:infer
UiPath acquires AI startup Re:infer, adding communications mining expertise to robotic process automation capabilities.
Here Are 5 NLP Terms That Now Occur Naturally in Localization
NLP technologies drive the evolution of localization, turning jargon into common terms used to manage today’s ops and tomorrow’s strategic plans. Here are five NLP terms.
Here’s What Happened at the ‘New Trends in Translation and Technology’ Conference
NeTTT conference brings together academia, industry, and EU institutions, highlights new trends in translation and technology.
Research on Automatic Correction of Human Translation Wins Award
Natural language processing scientists from Lilt train model on human translation errors. The goal, to automate the correction of human translations.
Lingua Custodia Lab Publishes Their Latest Research on NLP
Lingua Custodia Lab team present their NLP research article “Approach to integrating terminology constraints into neural translation models” which has been selected for publication.
Meta Doubles Down on Direct Speech-to-Speech Translation
Meta eliminates text generation in speech to speech translation; shares code and research with the public.
Large Language Models May Leak Personal Data, Studies Show
Large pretrained language models (PLMs) memorize lots of personal data. Researchers examine data privacy risks associated with PLMs, propose solutions.
Reader Polls: New Ways to Post-Edit Machine Translation
Could a mouse-less, keyboard-less future be in the cards for translators? Slator readers weigh in on this and other developments in language technology.
Amazon Unveils Long-Term Goal in Natural Language Processing
Amazon presents three ways it hopes to extend current natural language processing R&D beyond just a small subset of the world's 7,000+ languages.
Low Resource, High Potential — NeuralSpace CEO Felix Laumann on Democratizing NLP
NeuralSpace CEO, Felix Laumann, joins the pod to discuss how they overcome the lack of research, data, and tools when training NLP models in low-resource languages.
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