Foundation models are so versatile and powerful. Almost daily, additional applications of these models are discovered. Foundation models understand and generate many languages and they seem to have an immensely broad knowledge covering nearly every aspect of life. Thus, at least for large language models, one foundation model such as GPT-x should at first glance suffice, which would then be incrementally extended and improved as we have already witnessed it.

Hans will describe strong reasons for developing or expecting a variety of foundation models. To this end, Hans will highlight emerging differences among models and also discuss differences among the desiderata and expectations concerning future models. Finally, existing limitations of the models will be investigated, some of which reduce their reliability while in contrast others contribute to their overall safety.