Language Industry (Artificial) Intelligence — Slator Answers
Just 1.4% of large language model PaLM’s natural language exposure is “unintentional consumption” of bilingual signals — which seems to be enough to contribute to the model’s translation abilities.
Initially launched in a few select countries, Google has plans for its “creative, helpful collaborator” to support — and translate between — 40 languages, up from the current three.
Google releases the PaLM 2 large language model. Technical report accompanying the launch finds that the LLM outperforms Google Translate in machine translation across all locales.
Subject to “guardrails” and innovative watermarks, available only to authorized partners, to prevent misuse; the system delivers speech-to-speech translation with lip matching.
Clients asking about services around ChatGPT; ChatGPT impact on language industry; Google encouraging MT for app user interface; startups where readers would invest USD 1K.
As the race in all things language AI heats up, Google discloses more details about its Universal Speech Model that the search giant claims supports over 1,000 languages.
Google launches a new dataset and benchmark to address the lack of region-awareness in machine translation (MT) systems and support under-resourced dialects.
Gamers around the world see localization as “important”, particularly for players in Asia-Pacific and Brazil, according to a Google survey.
Google demonstrates the capability of LLMs to create synthetic datasets that can be used to train semantic similarity metrics for evaluating MT quality.
TransPerfect 2022 results, Cohere’s multibillion-dollar valuation, NHS’ interpreting spend, Iyuno expands into Turkey, EU’s million-page contract, Google’s new AI chatbot.
Google Translate adds a number of new accessibility features, better contextual machine translation, and 33 additional languages on mobile for offline use.
Google’s Head of Translation AI, Mallika Iyer, on serving enterprise customers with Translation Hub, her passion for solving user problems, and making content more accessible.
In just three months, universities and tech companies released over two dozen papers on speech-to-speech translation (S2ST), highlighting continuing trends, new directions in research.
YouTube announces that Google’s machine dubbing product, Aloud, is available to its healthcare partners in India, making “dubbing as easy as one, two, three.”
NeuralGarage raises USD 1.45m, Papercup wins big with Bloomberg, large language models and their use in machine translation, and public sector RFPs for translation services.
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