Raw LLM Responses

Edit, downvoting the comment does not stop it being true, LLMs are far more than search engines, they are closer to reasoning engines with a data store. They generalize outside the training distribution. The only way to correctly predict the next token is if there is semantic understanding derived from the text it was trained on. > It's a glorified search engine https://www.wired.com/story/fast-forward-gpt-4-minecraft-chatgpt/ >"The Nvidia team ... created a Minecraft bot called Voyager that uses GPT-4 to solve problems inside the game. The language model generates objectives that help the agent explore the game, and code that improves the bot’s skill at the game over time." >"Voyager doesn’t play the game like a person, but it can read the state of the game directly, via an API. It might see a fishing rod in its inventory and a river nearby, for instance, and use GPT-4 to suggest the goal of doing some fishing to gain experience. It will then use this goal to have GPT-4 generate the code needed to have the character achieve it. " >"The most novel part of the project is the code that GPT-4 generates to add behaviors to Voyager. If the code initially suggested doesn’t run perfectly, Voyager will try to refine it using error messages, feedback from the game, and a description of the code generated by GPT-4. " >"Over time, Voyager builds a library of code in order to learn to make increasingly complex things and explore more of the game. [A chart created by the researchers shows how capable it is compared to other Minecraft agents.](https://voyager.minedojo.org/assets/images/exploration_performance.png) Voyager obtains more than three times as many items; explores more than twice as far; and builds tools 15 times more quickly than other AI agents. Fan says the approach may be improved in the future with the addition of a way for the system to incorporate visual information from the game." https://www.youtube.com/watch?v=ar5k4jFZapk