Glyph Language Services’ Post

👉 A new study shows that a significant amount of multilingual web content is machine-translated, especially in low-resource languages, which can affect the quality of AI models trained on such data. 👉 The study found that texts translated into many languages were of lower quality than texts available in only one or a few languages - an indication that machine translation was used. 👉 The authors of the study recommend filtering out machine translation from training data and further investigating the impact of machine-translated content on the performance of AI models. 👇 Read more #ai #artificialintelligence https://lnkd.in/gCY5aZuk

Excellent summary of current discourse around AI translation ✨

There’s no denying that many translators are skeptical of AI solutions. AI promising to speed up our work but instead leading to poor outcomes, doubling our workload, and reducing pay. And let’s be honest, they’re NOT WRONG. Without a clear strategy, terminology supervision, or quality input, AI and MT engines can indeed produce disastrous results. But here’s the thing: change is inevitable, whether we like it or not. Some of us will continue to serve direct clients who require fully human translations. However, it's unrealistic to believe that we, as a collective, can resist this shift in our industry. What we can do is adapt—and wisely. In fact, I recently came across a great example of how AI can be a helpful tool. One translator was struggling to translate a joke from Polish to English and reached out to a Facebook group for ideas. She was stuck, unable to find the right words to make the English version as funny as the original. Then, someone decided to ask AI. And it came up with a few clever ideas that we could choose from. So, why not use AI as an idea book, or as a search tool (Again! With a dose of caution, as with any tool)? It can be a great source of inspiration when we need it most. In our client interactions, let’s emphasize the importance of intelligent AI use. We should be proactive about terminology management, demand glossaries, and never accept a project without first reviewing the MT output. After all, using a general LLM to translate specialized content, like medical texts, is a recipe for disaster. But with an MT engine trained on domain-specific content and a term base curated by experts, the results CAN BE remarkable.

I see continued discussion among translators, almost all of whom depend on agencies for work, of how to incorporate AI into their translation workflow. AI can surely be useful, but those translators who jump on the AI bandwagon won't have any clients to give them work, since the agencies they are dependent on will only be ordering MT post-editing. The income from post-editing is so low that, if accepted, it would require a translator to drastically downsize their income expectations and lifestyle. Just using AI is not the answer. Acquiring direct clients will buy _some_ time, but that is not possible for most translators, the great portion of which have become accustomed to sitting in front of their computers and waiting for work from agencies. That's not the way it works with direct clients.

One of the best quotes I’ve seen about AI is that, “AI won’t replace you; a person using AI will.” This article about translators is a perfect example. You’d think AI might replace translators, given that we already have apps on our phones that can translate real time. But it isn’t. “Companies continue to hire human translators and interpreters because they understand that AI cannot replace the expertise and judgment that these professionals bring to the table.” It’s another real world example of workers using AI to enhance their productivity, rather than being replaced by it. #artificialintelligence #translators #productivity https://n.pr/3xzSSo2

"When AI seems too magical, sometimes it is*."   Currently there is a lot of debate surrounding AI and how it's already affecting various sectors and jobs.   The language services industry is one of those sectors where especially big players are keen to exploit "potential" benefits of AI to the detriment of human translators!   A couple of interesting online articles I came across last week, relating to Amazon phasing out their Just Walk Out technology from their grocery stores (these stores were advertised as cashierless but they relied on 1000 workers described as human babysitters in India watching the customers shop) made me draw some comparisons to how new AI powered models are being used in the LSI (links to the articles are in comments).   At the end of March, I attended CIOL Translator's Day in London during which a talk on deployment of AI from project management to post-editing in their work processes was delivered by a representative from RWS. I kind of thought to myself "Hang on, aren't we supposed to be the ones doing the post-editing tasks?".   The ways in which AI can be deployed for post-editing jobs is open to debate but where majority of LSPs are now opting for MTPE for most translation tasks, is use of AI in this area mean that even the MTPE jobs are now at stake for human translators or is this another case of pseudo AI or AI washing where companies exploit the hype and fuzzy definitions around AI to exaggerate the capabilities of their technology?   Apparently, Amazon is now moving away from the “just walk out” technology and rolling out “smart shopping carts” which are the scanners in shopping trollies that have been around for years! Surprised?   Looks like Jeff Bezo’s (the second wealthiest person in the world, worth about $205bn) ambition of replacing humans with algorithms in this area, therefore saving hundreds of thousands of dollars per store every year that would have normally been recorded as profit failed miserably.   Maybe not comparable to Amazon and Bezos in terms of the magnitude of wealth creation but is it a coincidence that most of the AI hype in the translation industry is driven by big LSPs like RWS whose boss is being paid a handsome sum of £605k a year and probably dreaming of completely replacing us with algorithms one day in the future? There is only one thing that's clear to me among all this cloud is that human translators will always be here to save the day!   * Parmy Olson #ai #artificialintelligence #pseudoai #aiwashing #machinetranslation #mtpe #freelancetranslator #litranslators

Rise and shine, readers! Discover how AI is revolutionizing translation, reducing demand for human translators—efficiency soaring, job security waning. Stay informed, stay ahead. 🌅🚀 #AI #translation #futureofwork Slide1: AI's Leap in Translation 🤖✨ Slide2: Human Translators' Dilemma 😕💬 Slide3: The Balance of Tech & Talent ⚖️🧠 Slide4: What's Next for Linguists? 🔮🗣️ Slide5: Join the Discussion! 🗨️💡 🔗 Stay updated: [Link to article] 🌐 See the impact: [Image link]

Earlier this year, DeepL, the global leader in Language AI, unveiled its latest offering for businesses: DeepL Write Pro. This new release—DeepL's first service powered by its own large language model (LLM)—helps knowledge workers write various types of business content. "Words matter, and language can be the competitive edge that moves the needle for global businesses," says Jaroslaw (Jarek) Kutylowski, DeepL's founder and CEO. "DeepL Write Pro is our first product powered by our own LLMs, and is the culmination of years of research and innovation that has set us apart from other tech giants.” Check out the full article here 👉 https://lnkd.in/ecqVvTi4 #Translation #AI #Innovation

If you liked the concept of #DeepAdaptiveAITranslation (see our newsletter last week https://hubs.la/Q02NQ5DZ0), here is the extra information on how Vector Databases power the next generation of AI Translation for automatic post-editing. https://hubs.la/Q02NQ0D_0

🌐 Is Artificial Intelligence Really Ready to Replace Human Translators? 🧠 Dive into the debate sparked by AI advancements in the language industry. Here are some of the intriguing insights from a recent article: 🔍 Ever-shifting languages: From 'deepfake' to 'groomzilla', how dictionaries struggle to keep pace with evolving language trends driven by global events and cultural shifts. 💬 Dazzled by ChatGPT: Explore how impressive AI outputs are challenging conventional translation methods and the impact of large language models. 🤖 Embracing tech in translation: A historical look at how translators have integrated technology, from the Rosetta Stone to neural MT and current CAT tools. 🔮 GenAI and translation: Unpacking the capabilities and limitations of ChatGPT in translation tasks, and the debate surrounding its reliability compared to traditional MT. 💡 Customer benefits: Understanding the role of AI like ChatGPT in the language industry, its current drawbacks, and the importance of human expertise in critical translation tasks. In a world where the language is always in motion, can machines truly grasp the intricacies of human communication? Join the conversation on the future of translation with AI revolutionizing the landscape. #LanguageTech #AIvsHumans https://lnkd.in/eHrD3QQi