Today we bake into these large language models a lot of knowledge. We require them to actually memorize a lot of information. That's not very efficient. And so I think that if you can distill the knowledge and storage part of it from the compute and reasoning and language part of it, you would end up with models that are significantly smaller and more efficient and not any less accurate. Or if you want to take about in a different way, if you kept the models the same size, it'll be a heck of a lot smaller.