# Amberi neural network Amberi Neural Network We've orchestrated an ensemble of NNs (Neural Networks) and christened it Amberi. It represents an intuitive, trailblazing modality for interfacing with our Metaverse 2.0. Crafted to streamline player interaction, Amberi shatters language barriers and eases gamers into the rules of the game, whilst facilitating acclimatization to the VR hotel ecosystem. Further, it harnesses the power of UE5 (Unreal Engine 5) to instantiate 3D environments and pioneer unique mechanics, all triggered by player voice commands. A salient impetus behind Amberi's inception is to optimize smartphone user interaction within our Metaverse. With a whopping 80% of the demand for NSFW content emanating from smartphones - devices notorious for their constrained screen real estate - the challenge of accommodating an expansive array of in-game actions becomes apparent. Amberi, our voice assistant, swoops in to save the day, rendering the need for cluttering control buttons obsolete, while ensuring optimal visual engagement. Leveraging its ML (Machine Learning) capabilities for continuous self-improvement, Amberi refines your requests and performs implicit corrections. Looking forward, we're placing our bets on BCI (Brain-Computer Interface) technology. As neuroprosthetics become reality, we anticipate the potential to interpret cognitive constructs and manifest them in our Metaverse, transcending the need for voice commands. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://hotel-of-secrets.gitbook.io/white-paper/functional/amberi-neural-network.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.