While we still don’t know all the main points, there have been reports that researchers at OpenAI had made a “breakthrough” in AI that had alarmed staff members. Reuters and The Information each report that researchers had give you a recent approach to make powerful AI systems and had created a recent model, called Q* (pronounced Q star), that was capable of perform grade-school-level math. In keeping with the individuals who spoke to Reuters, some at OpenAI consider this could possibly be a milestone in the corporate’s quest to construct artificial general intelligence, a much-hyped concept referring to an AI system that’s smarter than humans. The corporate declined to comment on Q*. 

Social media is stuffed with speculation and excessive hype, so I called some experts to learn the way big a deal any breakthrough in math and AI would be.

Researchers have for years tried to get AI models to resolve math problems. Language models like ChatGPT and GPT-4 can do some math, but not thoroughly or reliably. We currently don’t have the algorithms and even the proper architectures to find a way to resolve math problems reliably using AI, says Wenda Li, an AI lecturer on the University of Edinburgh. Deep learning and transformers (a type of neural network), which is what language models use, are excellent at recognizing patterns, but that alone is probably going not enough, Li adds. 

Math is a benchmark for reasoning, Li says. A machine that’s capable of reason about mathematics, could, in theory, find a way to learn to do other tasks that construct on existing information, equivalent to writing computer code or drawing conclusions from a news article. Math is a very hard challenge since it requires AI models to have the capability to reason and to essentially understand what they’re coping with. 

A generative AI system that might reliably do math would wish to have a very firm grasp on concrete definitions of particular concepts that may get very abstract. Lots of math problems also require some level of planning over multiple steps, says Katie Collins, a PhD researcher on the University of Cambridge, who makes a speciality of math and AI. Indeed, Yann LeCun, chief AI scientist at Meta, posted on X and LinkedIn over the weekend that he thinks Q* is more likely to be “OpenAI attempts at planning.”

Individuals who worry about whether AI poses an existential risk to humans, one among OpenAI’s founding concerns, fear that such capabilities might result in rogue AI. Safety concerns might arise if such AI systems are allowed to set their very own goals and begin to interface with an actual physical or digital world in some ways, says Collins. 

But while math capability might take us a step closer to more powerful AI systems, solving these styles of math problems doesn’t signal the birth of a superintelligence. 

“I don’t think it immediately gets us to AGI or scary situations,” says Collins.  It’s also very essential to underline what type of math problems AI is solving, she adds.