Can Large Language Models Do Simultaneous Machine Translation?
Monash University researchers show that large language models can do real-time machine translation and propose new ways for model fine-tuning.
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MT
After Gizmodo Fires Spanish Writers, Google Now Ranks Raw Machine Translation
G/O Media fires Gizmodo’s entire staff of Spanish writers and begins publishing raw machine-translated versions of English articles that are now being indexed by Google Search.
Apostroph’s Experts Talk About the AI Journey and The Power of Custom Models
Apostroph’s apoLAB engineers explain the potential of custom language models for simplifying workflows and discuss better machine learning strategies and data security.
Is the Bear Market in Language Service Providers Justified?
Q3 2023 is a time of contrasts, with highs on the technology and professional sides of the language services industry, and lows on the financial side for publicly traded LSPs.
Research Shows How to Replicate ‘Translator Style’ in Literary Machine Translation
Boğaziçi University researchers reveal the potential of customizing MT systems to replicate a translator's style, leading to literary translations that mirror the translator's unique style.
Researchers Call for Clear Policies around Machine Translation Use in Higher Education
A paper discussing the use of digital tools in academia addresses machine translation as both a problematic and beneficial tool, proposing increased awareness and clear policies for its use.
This University Project Supports Post-Editing Training in Translator Education
The Post-Edit Me! project supports educators in developing innovative post-editing training practices, fostering enhanced post-editing skills for the future of the industry.
The Institutional Acceptance of Machine Translation is Growing
MT gets institutionalized; AI is artificial but AI fatigue and FOMOAI are real; interpreters are supported in their right to strike; translator training is revisited, tech expertise is not a priority.
Imminent Report: Collective Intelligence Is Found in Cultural and Linguistic Diversity
The Imminent Report 2023 is a compendium of “Word Wide Wisdom,” captured in thought-provoking articles from authors as diverse as astrophysicists and language technologists.
Here’s What Happened at ATA’s Expert-in-the-Loop and AI Conference
Speakers at the ATA MT and AI virtual conference coincided in a message urging attendees to embrace the changes AI brings to the way translators and interpreters work.
Domain Adaptation On-The-Fly: Boosting In-Context Machine Translation with Coherence
Researchers from John Hopkins University explore the role of domain and local coherence in in-context machine translation revealing improvements in quality.
Why Large Language Models Hallucinate When Machine Translating ‘in the Wild’
A group of researchers found that large language models produce hallucinations when machine translating ‘in the wild’ that are different from traditional models.
How Does Large Language Model BLOOM Perform for Machine Translation?
Researchers test BLOOM’s capabilities for producing good quality machine translation. They find that training the large language model makes a big difference for all language pairs.
How Google Wants to Improve Evaluation of Low-Resource Dialect Machine Translation
Google launches a new dataset and benchmark to address the lack of region-awareness in machine translation (MT) systems and support under-resourced dialects.
How Large Language Models Can Get Better at Machine Translation of Rare Words
Meta AI researchers experimented with dictionary data prompting on known LLMs in order to improve MT. Results look promising for rare words and domain transfer.
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