TypeSafe AI debuts model for machines that plays Doom

TypeSafe AI, a startup bestowed with $40 million in funding, on Tuesday declared itself a maker of frontier models with the release of Jev, a new type of AI model intended for interaction with machines rather than people.

Instead of returning natural language in response to a text-based prompt, TypeSafe AI designed Jev to return typed probabilistic decisions for use by other software or AI models.

Type safety in programming is a way to catch errors that arise when software processes an unexpected type of data, as might happen if an operation tried to divide an integer by a text string.

By providing typed, structured values, Jev can avoid the parsing and validating that must be done to process text responses from LLMs.

This approach can be useful for scenarios where interactions with an AI system need to be constrained to a limited set of answers.

It can, for example, play Doom, when fed structured data describing the player's game state.

But it's more likely to be used for sorting customer service problems and other business workflows.

With Jev, the developer starts with a state value, which can be a JSON object or simply a string like "My card was charged twice." The model gets presented with state information through a set of question primitives (Choice, Score, Noul), each of which returns a different type of structured response with probabilities.

So a question asking the model to choose which of three departments should handle a particular customer service query might come back: {"billing": 0.08, "technical": 0.85, "sales": 0.07}, with a confidence score of 0.82.

That's not very useful for a person seeking the answer to a question but for a software developer, that might be just the thing to make a particular customer service function run more reliably.

Jev is a System One model, which relies on a different architecture called Reinforcement Learning for Calibrated Decisions (RLCD).

Diogo Almeida, co-founder and CEO of TypeSafe AI, is a former OpenAI researcher and one of the co-inventors of reinforcement learning for human feedback (RLHF) and ChatGPT.

"TypeSafe was founded to pursue an alternative path for AI research, focused on machine-native AI," said Almeida in a statement.

"I spent years working on models designed to make AI better at interacting with people.