[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fqgzlyhzbak8h":3},{"date":4,"days":5,"weeks":23,"rubrics":24,"count":22},"2026-09-21",[6,9,12,15,18,21],{"date":7,"count":8},"2026-09-26",43,{"date":10,"count":11},"2026-09-25",34,{"date":13,"count":14},"2026-09-24",26,{"date":16,"count":17},"2026-09-23",19,{"date":19,"count":20},"2026-09-22",14,{"date":4,"count":22},2,[],[25,35],{"key":26,"items":27},"models",[28],{"id":29,"url":30,"source":31,"rubric":26,"date":4,"top":32,"title":33,"summary":34},541,"https:\u002F\u002Fwww.vedomosti.ru\u002Ftechnology\u002Farticles\u002F2026\u002F09\u002F21\u002F1230344-yandeks-sozdal-novuyu-yazikovuyu-model","Ведомости",1,"Yandex makes the weights of its Alice AI Foundation LLM available","Yandex introduced Alice AI Foundation LLM, a model with 80 billion parameters, of which 3 billion are active during operation. It was trained on 18 trillion tokens. The company made the weights available for commercial and research use, allowing developers to run the model themselves and fine-tune it.",{"key":36,"items":37},"dev",[38],{"id":39,"url":40,"source":41,"rubric":36,"date":4,"top":22,"title":42,"summary":43},578,"https:\u002F\u002Fhuggingface.co\u002Fblog\u002Ftokenizers-v1","Hugging Face","Hugging Face is preparing tokenizers v1, which could be tens of times faster","Hugging Face described tokenizers v1 in a post, saying it could make tokenization tens of times faster than v0.23. The 1.0.0 implementation is already ready. This could reduce latency in ML pipelines where data processing becomes a bottleneck as they scale."]