Topic
Model Training
4 stories on this topic, newest first.
ModelsAnalysis
Apertus 1.5 opens the recipe, including the parts that did not work
The multimodal release makes its tokenizer, training stages and limitations inspectable. Its most useful contribution is the ability to trace behaviour back to decisions.
ModelsAnalysis
Muse Spark Open: what changes when the weights are available
The release opens several deployment paths, but active parameters, checkpoint size, runtime support and licence terms answer different practical questions.
ResearchAnalysis
Can one small model inherit several specialists' skills?
A new distillation study combines teacher feedback with parameter priors. The result sharpens the question of how to consolidate expertise without losing weaker domains.
ResearchExplainer
Why Google wants language models to sleep between tasks
Periodic consolidation offers a different answer to stale knowledge. The important questions are what persists, what changes and whether older capabilities survive.
