Azercell Telecom LLC, Azerbaijan’s leading telecommunications provider, wanted to build an Azerbaijani large language model (LLM) on Amazon SageMaker AI for telecom use cases and a customer-facing chatbot. The challenge: adapting foundation models (FMs) to a morphologically rich language with limited training data and no existing blueprint for efficient LLM training in Azerbaijani. In a six-week collaboration, Azercell worked with the AWS Generative AI Innovation Center to establish a production-ready framework on Amazon SageMaker AI.

Through its Community Education Initiative, Apple has been working with OCU and Cherokee Nation to equip young learners with iPad and Mac.

As a vector of communication and identity, languages are dissolving in the intelligent machine. With AI, a word becomes a concept, a concept that can be transcribed into hundreds of languages, transformed into sound, image or data linked to a region, style, author, emotion or use. Combined in this way with 1,000 meanings depending on the context, the concept acquires a flexibility and dynamism that no lexicon has ever been able to offer.Faced with this immense potential, thousands of less formalized languages feel their demise approaching through attrition, while others act like sponges, blithely integrating influences into techno-assisted languages, creoles, pidgins, sabirs and other developing shengs. Pleasing the machine is now part of a new techno-aocial etiquette, like not putting a period at the end of a text message. The sheer number of possibilities opened up by AI is forcing us to question many of our certainties about our intellectual and linguistic superiority. Our ways of learning and teaching are obviously affected, priorities are changing and, beyond learning to read, write and count, it’s the skills of processing information, from its production to its organization and evaluation, that are most often on the agenda.