sentimentscan

    Lack of Human and Social Interactions: This is a significant drawback when you look it as the social thing, however, they require scheduling. For me I wanted to venture beyond the typical fantasy/sci-fi settings and good bored of those D&D/warhammer world.

    LLM Versatility: LLMs can take you on wild (now non-NSFW) adventures. I wanted to play a D&D-style game set in the Venetian Renaissance and GPT delivered with accurate locations, families, and artists. It can do the same with medieval settings from my country, ancient Rome, surrealist landscapes, and whatever your favorite books, movies, or games involve.

    Customization: Want a game master who replies in poetry, slang, in style of you favourite author? No problem.

    Context: This is a tough one, but there are two approaches:
        Retrieval-Augmented Generation (RAG)
        Summarization, and then summarization of the summary. I've used this approach in my previous startup and in this game.

    Characters: I utilised the randomness of different character styles. You might meet smart/beautiful/evil/good characters with predefined styles, and the LLM quite effectively supports roleplay.

    Lack of Continuity: The biggest downside is the lack of continuity. Even if I generate a world and scenario, after a few rooms, it doesn't come together like a game would, where previous events feed into current ones, even when I provide again LLM with previous details. I kinda lack big picture design of story. I am working on that