OpenAI Announces a New AI Model, Code-Named Strawberry, That Solves Difficult Problems Step by Step

OpenAI made the final huge breakthrough in artificial intelligence by rising the dimensions of its fashions to dizzying proportions, when it introduced GPT-4 final yr. The corporate at present introduced a brand new advance that alerts a shift in method—a mannequin that may “cause” logically by many troublesome issues and is considerably smarter than present AI with no main scale-up.

The brand new mannequin, dubbed OpenAI-o1, can remedy issues that stump present AI fashions, together with OpenAI’s strongest present mannequin, GPT-4o. Reasonably than summon up a solution in a single step, as a big language mannequin usually does, it causes by the issue, successfully considering out loud as an individual would possibly, earlier than arriving on the proper consequence.

“That is what we contemplate the brand new paradigm in these fashions,” Mira Murati, OpenAI’s chief expertise officer, tells WIRED. “It’s a lot better at tackling very complicated reasoning duties.”

The brand new mannequin was code-named Strawberry inside OpenAI, and it’s not a successor to GPT-4o however relatively a complement to it, the corporate says.

Murati says that OpenAI is at present constructing its subsequent grasp mannequin, GPT-5, which shall be significantly bigger than its predecessor. However whereas the corporate nonetheless believes that scale will assist wring new talents out of AI, GPT-5 is more likely to additionally embrace the reasoning expertise launched at present. “There are two paradigms,” Murati says. “The scaling paradigm and this new paradigm. We anticipate that we’ll carry them collectively.”

LLMs sometimes conjure their solutions from enormous neural networks fed huge portions of coaching information. They will exhibit outstanding linguistic and logical talents, however historically battle with surprisingly easy issues equivalent to rudimentary math questions that contain reasoning.

Murati says OpenAI-o1 makes use of reinforcement studying, which entails giving a mannequin constructive suggestions when it will get solutions proper and adverse suggestions when it doesn’t, with a view to enhance its reasoning course of. “The mannequin sharpens its considering and wonderful tunes the methods that it makes use of to get to the reply,” she says. Reinforcement studying has enabled computer systems to play games with superhuman skill and do helpful duties like designing computer chips. The method can be a key ingredient for turning an LLM right into a helpful and well-behaved chatbot.

Mark Chen, vice chairman of analysis at OpenAI, demonstrated the brand new mannequin to WIRED, utilizing it to resolve a number of issues that its prior mannequin, GPT-4o, can not. These included a complicated chemistry query and the next mind-bending mathematical puzzle: “A princess is as outdated because the prince shall be when the princess is twice as outdated because the prince was when the princess’s age was half the sum of their current age. What’s the age of the prince and princess?” (The proper reply is that the prince is 30, and the princess is 40).

“The [new] mannequin is studying to assume for itself, relatively than sort of making an attempt to mimic the best way people would assume,” as a traditional LLM does, Chen says.

OpenAI says its new mannequin performs markedly higher on plenty of drawback units, together with ones centered on coding, math, physics, biology, and chemistry. On the American Invitational Arithmetic Examination (AIME), a take a look at for math college students, GPT-4o solved on common 12 p.c of the issues whereas o1 bought 83 p.c proper, in keeping with the corporate.