Amazon releases MT-GenEval, a realistic dataset for evaluating gender bias in machine translation, to better understand how MT models perform on gender translation accuracy.
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.
Researchers revisit controlled language as a means of improving MT quality. A new methodology based on stylistic quality is said to eliminate repeated fine tuning.
Researchers from Meta suggest training-data curation as a means to reduce added toxicity in machine translation. Toxicity categories include profanity, insults, hate speech, bullying, etc.
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.
When researchers experimented with machine translation to simplify medical content for patients, the results were mixed but promising.
UiPath acquires AI startup Re:infer, adding communications mining expertise to robotic process automation capabilities.
Translation programs should incorporate ethics in their curricula, studies show. Besides translation and technical competencies, ethical decision-making proves to be a valuable skill.
Research reveals that examining non-English scientific papers would benefit more domains, particularly those of biodiversity and global conservation.
As machine translation gets better, the problem of bias — especially gender bias — remains a source of embarrassment for the industry. Why MT bias matters and how major players are trying to fix it.
Meta AI wants to make large language models more accessible to researchers with the release of OPT-175B; advocates R&D transparency and a “research mindset.”
What does Google’s 540-billion parameter language model, PaLM, mean for machine learning and the language industry? Experts weigh in.
Part of the billions of dollars going into the Metaverse will undoubtedly go into these two areas of machine translation. Meta AI reveals its MT roadmap and the people working on it.
Indian language human+AI translation platform, Devnagri, raises USD 600,000 to help businesses reach one billion Indians in their own regional language. CEO reveals what’s next after text translation.
Where translators make the difference in mission-critical cases around subtitling, politics, brand marketing, language technology, and more.
Researchers tracked CO2 emissions from training German, French, and English machine translation engines, and found this language pair to be most carbon-intensive.
Unpacking DeepL’s turbo growth; and Welocalize AI Innovation VP, Olga Beregovaya, joins the Pod to discuss the evolution of NLP, the state of AI, and global content transformation.
The new CEO assumes the leadership role following a proven track record of growing businesses and bringing teams to a new level of operation
Google publishes translation dataset of biographies from Wikipedia in hopes of reducing gender bias in Google Translate output.
Custom.MT has completed training and evaluation of its 150th trained MT engine and aggregated several vital statistics in a report.
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