We examine the power of large models of large languages (MLLMs) to deal with different structures that are higher than the indigenous language and these types of these species are often trained. Specially, our focus is lying in areas such as Equidious Ai, games, UI control, and planning. To date, we introduce a MLLM synchronization process in the normal agent (GEA). GEA is one united model that can support themselves in different backgrounds in the Tokenzer of a lot of action. GEA trained by monitored learning to the Great Databases for experienced experience and online online information in the contact simulators. We examine data data and algorithmic options needed to improve such model. Our acquisition shows the importance of training with the CROSS-Domain Data and the Internet's internet construction of Gervals Agents. The last GEA model reaches the strong functionality of unseen functions in all different benchmarks compared to other common models and Benchmarks.
