In his talk, Thomas Tomow explores why the miniaturization of Large Language Models (LLMs) is so important in today's technological world. Thomas focuses on the significant benefits of smaller and more efficient models in various fields such as robotics, healthcare, and customer service.

He provides insights into the innovative methods that enable the downsizing of LLMs, including model compression and fine-tuning. These approaches allow models to remain powerful and flexible despite their reduced size while saving resources.

Thomas also sheds light on the challenges and opportunities associated with developing and using these more compact AI models. Not only the technical aspects but also ethical and practical considerations are taken into account, particularly with regard to the use of these technologies in sensitive areas.

Finally, Thomas Tomow looks at the future prospects of this technology. He discusses how ongoing research and innovation can help develop these models further to create effective and ethical solutions for various applications.

Companies, especially in audited fields, often lack free access to the cloud for several reasons. Generally, data residency and ownership are what are needed to have Large Language Models hosted on-premises. But OpenAIs ChatGPT or GEMINI aren't simply downloadable, so this is I am talking about: The possibility to do it nevertheless and have much more control over you own data in conjunction with the comfort of ChatGPT-Style.