Since ChatGPT’s launch in November 2022, media outlets have been churning out article after article about how generative artificial intelligence (AI) is coming for our jobs. Nearly every week, a new piece comes out in publications like The Atlantic or Business Insider about how ChatGPT will “destabilize” the job market, making certain workers redundant.
oday, machine translation (MT) is so pervasive that — for many young or early-career localization professionals, at least — it’s hard to imagine a time without it. But such a time did exist. Those with a decade or two of language industry experience under their belt have, no doubt, witnessed firsthand MT’s evolution into the nearly omnipresent entity that it is today.
As of November 2022, everybody in the language industry is talking about ChatGPT. It is an undeniable trend firmly occupying the minds of many. New implementation scenarios and use cases for ChatGPT emerge daily, and GPT-4 has just been released. But will it stay as hyped in the next five years, or will it become as normal as Machine Translation (MT) for us?
Language technology providers are scrambling to jump on the speech-to-text bandwagon which means users can view machine-generated live subtitles (translated from the original) as well as multilingual captions (monolingual transcripts available for different languages)of speeches in their preferred language.
Cologne-based DeepL has announced the beta launch of DeepL Write, an AI-powered authoring tool intended to improve texts by fixing errors and making suggestions for word replacements while keeping an eye on style, grammar and formatting.
Machine interpreting (MI) is a hot topic right now as technology providers boast their latest advances in this field. It is likely that the advent of MI will revolutionize the interpreting industry as we know it, similarly to how machine translation (MT) upended the translation industry and ushered in a new era for all stakeholders involved. So, now is the perfect opportunity to take a deep dive into the world of machine interpreting.
Now that markets are down, some have been looking at web3 projects with incredulity, believing it was all just hype and that there’s no need to care about any of it anymore. That would be very wrong. Yes, we are indeed experiencing a crypto winter, and myriad projects promoting blockchain, crypto, or NFTs are long gone.
Continuous improvement in machine translation (MT) technology means that MT engines are expected to get ever more effective. One of the areas where this is already happening is fuzzy matches for MT.
It is a given nowadays that when organizations expand internationally or consolidate their existing global presence, they need to invest in localization. This does not simply mean linguistic resources but also technological investments that contribute to translation productivity among other efficiencies.