Language Industry (Artificial) Intelligence — Slator Answers
Discover what’s new in the field of large language models, from ground-breaking research in academia to Big Tech’s latest releases.
As large language models are put into production across the USD 28bn language industry, CEOs expect to start recruiting for new roles: from Prompt Engineer to Source Language AI Copy Editor.
Slator launches new AI feature, Google’s Bard is super cautious on translation, K-pop star uses Youtube’s multi-audio track, and M&A in media localization.
Research shows that incorporating preparatory steps and self-generated knowledge into the translation process of LLMs enables them to emulate human translation strategies.
Researchers from John Hopkins University explore the role of domain and local coherence in in-context machine translation revealing improvements in quality.
UC Berkeley’s Steven Piantadosi on the transformative impact of LLMs on our understanding of language and how it challenges Noam Chomsky’s theories.
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.
The 140-page flagship Slator 2023 Language Industry Market Report features comprehensive market-size and buyer-segment analyses, sales and marketing insights, language tech, and more.
Jonckers sold to private equity firm, Welocalize and Lionbridge announce new C-level hires, financial update for RWS, and ZOO raises USD 15.5m for Japan acquisition.
Fireflies.ai CEO Krish Ramineni on finding their product-market fit and leveraging large language models for transcription, summarization, and translation.
Microsoft proposes a path forward for document-based machine translation, breaking free from the sentence-level translation paradigm.
Welocalize on how the language service industry is uniquely positioned to help corporations navigate the impending disruption.
AI is changing jobs even if most are not ready to make a career change, government attempt to control language is unpopular, and GPT hype is not over, though some of us are over it.
Adam Bittlingmayer, Varshul Gupta, and Mihai Vlad on LLMs and machine translation, client perspectives, state-of-the-art research, and GPT’s impact on the language industry.
Machine translation researchers look at how to manipulate ChatGPT translation quality with different prompt strategies.
As the language industry races to assess the business impact of large language models, we examine who were the top and worst performing listed language service providers since ChatGPT.
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