machine translation

Deepseek for Translation 2: a Robin Hood Moment in AI

Part 1 of the evaluation with scores Full-sized infographic Сommunity’s evaluation of Deepseek’s translation accuracy is complete. Conclusion: Deepseek is a top-notch translation powerhouse racing nose-to-nose with the market leaders. The differences were small, and the ratings depended more on personal preferences of evaluators towards computer-generated translation, rather than model performance. And it will get […]

Deepseek for Translation: a Flash Evaluation

On January 28 we called for language industry peers to evaluate the new large language model Deepseek for translation tasks. More than 30 volunteers came forward, and the first results have already come in. We’re hoping to have at least 10-15 language combinations evaluated within the scope of this expercise. We will publish information as […]

Mix Machine Translation + GenAI

Custom.MT Console has rolled out a key update: a way to combine the output of popular machine translation engines with generative AI. Localization specialists may now easily style MT output and “mix and blend colors” to get a more accurate and evocative machine translation that speaks with the audience. Machine translation engines are reliable but […]

Designing AI Translation Performance Dashboards

Localization teams in 2024 had a renewed interest in implementing AI translation in workflows. It was a reasonable way to trim their budgets and improve per-word costs. However, just like today, monetization often became a struggle because the mechanism to track human post-editing effort – unlike that of an AI – fairly and responsively is […]

GPT-4 Turbo and Vision in Localization

On Monday, November the 6th, OpenAI upveiled the new improved models. Let’s explore the main features of GPT-4 Turbo and its possible implementations in the localization field. The release is a gauntlet of challenge to a broad range of AI companies. Not just LLM builders like Antropic and Cohere, but also speech recognition, synthetic voice, […]

Custom.MT enrolls in the Nvidia Inception program

Custom.MT, a leading provider of applied AI for localization, has been approved for Nvidia’s Inception program for startups. With this program, Nvidia supports and nurtures promising startups in the fields of AI and data science. Now that Custom.MT is a member of Inception. So we will have access to significant benefits that will help us […]

Custom.MT Brings ChatGPT to Trados Users

Custom.MT integrated ChatGPT and made it available through a Trados Plugin. Try it, the first 50,000 characters are on us. Like all technology teams out there, Custom.MT is experiencing the AI revolution with awe and excitement. As soon as OpenAI made waves, we decided to make it work for localization people. Working on our first […]

Guide: How to Train a Microsoft Translator AutoML

This guide is useful to train your own Microsoft AutoML translation model for customized MT using Microsoft Translator. For example, you can train a domain model, such as medical, legal, video games, financial reporting with your translation memory accumulated over the years. Alternatively, you can make an organization-specific model that knows all the product and […]

Guide: How to Train a Google Translate AutoML v3 Model

This guide is useful to train your own Google AutoML translation model. For example, you can train a domain MT model, such as medical, legal, video games, financial reporting with your translation memory accumulated over the years. Alternatively, you can make an organization-specific model that knows all the product and people names, and follows your […]

Guide: How to Adapt an Amazon Active Custom Translation Model with Your Data

This guide is useful to train your own Amazon MT model. For example, you can train a domain model, such as medical, legal, video games, financial reporting with your translation memory accumulated over the years. Alternatively, you can make an organization-specific model that knows all the product and people names, and follows your individual styles. […]

Tools for Data Labeling in Machine Translation Evaluations

Running professional human evaluations of machine translation performance requires detailed methodology and software tools to streamline the process. The most detailed approach to evaluation today is through labeling data such as errors and assign weights to critical issues using a variation of DQF/MQM ontology. In this article, we outline Custom.MT’s journey to selecting and implementing […]

Why TAUS Changed from a Think Tank to an MT Data Provider

Founded in 2005 as a think tank, TAUS has turned into a prominent marketplace for machine translation training datasets, and a data services provider. Gone are the days of hosting conferences, the TAUS team is now busy collecting text and speech data for the likes of Google and Microsoft in a crowded space alongside Appen, […]

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