GenQuest is a generative text adventure game that leverages Large Language Models (LLMs) to facilitate second language learning through immersive, interactive storytelling. The system engages English as a Foreign Language (EFL) learners in a collaborative "choose-your-own-adventure" style narrative, dynamically generated in response to learner choices. Game mechanics such as branching decision points and story milestones are incorporated to maintain narrative coherence while allowing learner-driven plot development. Key pedagogical features include content generation tailored to each learner's proficiency level, and a vocabulary assistant that provides in-context explanations of learner-queried text strings, ranging from words and phrases to sentences. Findings from a pilot study with university EFL students in China indicate promising vocabulary gains and positive user perceptions. Also discussed are suggestions from participants regarding the narrative length and quality, and the request for multi-modal content such as illustrations.

Back in the 1960s, Joseph Weizenbaum of the MIT Artificial Intelligence Laboratory created one of the first chatbots, which he named ELIZA. Weizenbaum modeled its conversational style after Carl Rogers, a psychotherapist who was known for parroting patients' responses back at them. His hypothesis was that while chatbots could emulate human conversation superficially, they could not fully capture the nuances of a genuine discussion between humans. To Weizenbaum's complete surprise, ELIZA did end up fooling many people into believing they were having a therapeutic breakthrough with a real live therapist. While modern customer service bots aren't likely to help customers dig deep into their psychological issues, the technology behind computers processing human language is getting more advanced day by day.

What would an adventure game designed by the world's most dangerous A.I. look like? A neuroscience grad student is here to help you find out. Earlier this year, OpenAI, an A.I. startup once sponsored by Elon Musk, created a text-generating bot deemed too dangerous to ever release to the public. Called GPT-2, the algorithm was designed to generate text so humanlike that it could convincingly pass itself off as being written by a person. Feed it the start of a newspaper article, for instance, and it would dream up the rest, complete with imagined quotes.

What would an adventure game designed by the worlds most dangerous A.I. look like? A neuroscience grad student is here to help you find out. Earlier this year, OpenAI, an A.I. startup once sponsored by Elon Musk, created a text-generating bot deemed too dangerous to ever release to the public. Called GPT-2, the algorithm was designed to generate text so humanlike that it could convincingly pass itself off as being written by a person. Feed it the start of a newspaper article, for instance, and it would dream up the rest, complete with imagined quotes.

We've seen people turn neural networks to almost everything from drafting pickup lines to a new Harry Potter chapter, but it turns out classic text adventure games may be one of the best fits for AI yet. This latest glimpse into what artificial intelligence can do was created by a neuroscience student named Nathan. Nathan trained GPT-2, a neural net designed to create predictive text, on classic PC text adventure games. Inspired by the Mind Game in Ender's Game, his goal was to create a game that would react to the player. Since he uploaded the resulting game to a Google Colab notebook, people like research scientist Janelle Shane have had fun seeing what a text adventure created by an AI looks like.

The answer is pretty weird. Shane aptly describes the experience as "dreamlike," with the setting frequently, and seemingly without reason, changing from scene to scene. For example, in one playthrough, the AI opened the game with a scene set in space only then to quickly transition things to a "labyrinth of twisty little passages, all alike." If there's a throughline to many of the scenarios, it's Zork, one of the games used to train the neural net and a classic in the genre. The AI will frequently call on the 40-year-old game to react to the player, more often than not presenting trolls as an obstacle to progress.

Jason Scott's first documentary in 2005 was about bulletin board systems (BBSs), which were in a sense the PC world's parallel evolution of the early Internet. This documentary, really more a multi-disc series of interviews with BBS pioneers than a documentary film as such, brought back to me my early years in personal computing and my subsequent forays into shareware software development through the mid-1990s. Now, Scott has tackled a subject from roughly the same era: the text adventure game. My involvement here was more peripheral but no less a part of my memories. As his new "Get Lamp" documentary recounts, the text adventure genre began with Will Crowther's Colossal Cave Adventure game in the early 1970s, more commonly referred to as just Adventure.