Reasoning models brought the biggest change in LLMs the last few years. They dramatically improve model intelligence, esp. in science, math and coding, tool use skills, reduce hallucinations and improve safety. They also pose challenges in training and their increased latency needs to be mitigated in products. I will give an overview of all these issues and focus on one more - how do reasoning models impact multilingual capabilities? I will show their potential for low-resource languages and specialized settings. I will also highlight how they require to adopt a very different approach from the standard LLMs in data gathering and fine-tuning.

Mark will give a sneak preview of recent work in this area, with some astonishing demos. The study entails (no doubt foolhardy) efforts to abstractly and operationally define intelligence, language, and understanding.

One-size-fits-all Spanish doesn’t exist. Juan and Paola reveal how Meta and RWS used AI to capture regional authenticity across Latin America.

Philipp, co-inventor of phrase-based SMT, has lived through a few revolutions in the world of Machine Translation. In his talk he will share his perspectives on the latest innovations: embracing speech and video, multilinguality in LLMs and address the question whether we are better off with LLMs or standalone models.

E-learning courses aren’t documents—they’re clicks, branches, media, variables, and timing, and that’s why existing solutions fall apart. In this talk Simon presents Articulate's journey to a purpose-built workflow for streamlined e-learning localization.

TRSB is one of the early movers implementing Quality Estimation (QE) for its Canadian customers. Ron will share the experiences from exploration to full implementation and the benefits

Embracing cultural nuances and under-resourced languages promotes diversity, autonomy, and equality in multilingual translation and makes AI more intelligent, accurate, and reliable. Ilan will describe Lexicala’s corresponding QE enhancements for language and translation models.

AI only works if the business wants to pay for it and if the training data are available. That leaves the majority of languages still in the ‘dark ages’. Jace Norton will share his perspectives on the long road for indigenous languages to travel into the future and what that means for the language workers.

In this keynote, Paco will talk about how the field of multilinguality has evolved, moving towards doing translation LLMs. LLMs continue to evolve, adding more complex capabilities that push the boundaries of scientific discovery. More than ever, developing LLMs requires access to the most specialized human data. In this talk, he will discuss his journey, going from pushing boundaries in translation, to LLM post-training in GenAI, to now pushing the boundaries of intelligence through the creation of frontier data. He will also outline the opportunities that lie ahead for LSPs and multilingual experts, to democratize the access to progress for everyone.

Turning data into the most valuable AI assets is both an art and a science. Amir would know this: he has been a member of the NLP team at TAUS that converted the largest industry-shared repository of translation data into the most used industry resource for training and customizing translation models.

The Agentic ecosystem does not include suppliers or a TMS. Wayne shares the Dell vision for the near future. A threat or an opportunity?

Traditional demarcations between clients and suppliers are blurring. Uber turns its vast global network of earners into the largest AI data annotation workforce.

Marco will present updated data on the latest progress toward “human parity” in the field and share insights into how the scientific community’s perspective has evolved. Drawing on his recent participation in the Vatican meeting, and as a signatory of the Global Appeal for Peaceful Human Coexistence and Shared Responsibility — together with Nobel laureates, leading scientists, and AI pioneers — he will reflect on the convergence of technological advancement and ethical responsibility. He will highlight the central role of language for understanding, and ultimately for coexistence, illustrating how innovation and collective awareness must progress hand in hand.

Centific is not the typical superagency you would think of when it comes to translation. Is that a pro or a con? Venkat shares insights in Centific’s strategy of building a scalable AI infrastructure to support globalization of long-tail customers.

Panel conversation on topics like:

Marcus has lived through the technology evolution of the localization industry, from CAT tools to TMS, GMS and MT. What is his take on the new paradigm of AI orchestration workflows? Something you build yourself, you buy or select your partners for?

Mathijs brings new life to Translation Memories, outside the CAT tool, into the AI configuration architecture of Blackbird.