GPT-4 Launch Promises Surprising New Use Cases
OpenAI releases its much anticipated GPT-4 large language model. Here’s a short primer on its language, problem-solving, and multimodal capabilities for real-world applications.
News and analysis of the latest developments in machine translation, computer-aided-translation, natural language processing, and other language-related areas in artificial intelligence.
OpenAI releases its much anticipated GPT-4 large language model. Here’s a short primer on its language, problem-solving, and multimodal capabilities for real-world applications.
The European Union’s Translation Centre gives guidance on daily post-editing output in a new multi-million Euro tender for translation services.
Developers can apply for early access to the new service to automatically translate store listings, product descriptions, and in-app text into seven languages.
Microsoft introduces a GPT-based metric to evaluate translation quality and highlights the state-of-the-art capabilities of large language models (LLMs) in this task.
AWS researchers create a way to train an automatic dubbing system based on bi-directional language data. Using phonemes instead of words resulted in better aligned speech and MT.
Google launches a new dataset and benchmark to address the lack of region-awareness in machine translation (MT) systems and support under-resourced dialects.
Google demonstrates the capability of LLMs to create synthetic datasets that can be used to train semantic similarity metrics for evaluating MT quality.
January 2023 paper from ADAPT Centre finds GPT can enhance real-time adaptation to user feedback; “promising” results, and number of fuzzy matches needed, vary by language.
Using ChatGPT for machine translation, the meaning of DeepL’s Unicorn status for the language industry, companies involved in M&As in 2022, and the fading translator CV scam.
Research by Tencent AI Lab compares ChatGPT’s performance in machine translation with Google Translate, DeepL, and Tencent’s TranSmart.
Microsoft’s NTREX-128, the second largest human-translated test set, is another benchmark for the evaluation of massively multilingual machine translation research.
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.
Unlike some fields in machine learning, machine translation still requires large sets of training data. The solution? Creating more data when none (or not enough) exists.
New research from IBM and UC San Diego explores synthetic parallel data as a means of pre-training machine translation models — with promising results.
Prevalence, severity of interference — the negative influence of other language pairs in multilingual machine translation models — may be overstated; solutions might be simplified.
Multilingual e-commerce searches introduce shoppers to new products; researchers identify language pairs with most to gain from launching or improving machine translation.
All you need to know about how you score against postediting translation speed standards and the factors affecting your performance.
Preview of what to expect at Intento’s Machine Translation Playbook Webinar on December 13, 2022. Nike, Stripe, GAP, AstraZeneca, NetApp share biggest takeaways from 2022; 2023 plans.
Very fluent but not yet highly accurate — this is how Google researchers describe machine translation performance of large language models versus state-of-the-art MT.
BNP Paribas, Europe’s second largest bank, applies domain adaptation for multilingual neural machine translation models — without excessive loss of knowledge across language pairs.
Slator Weekly: Join over 15,500 subscribers and get the latest language industry intelligence every Friday
Tool Box: Join over 9,000 subscribers for your monthly linguist technology update.
Your information will not be shared with third parties. No Spam.
This will close in 0 seconds