AI leaders have a new term for the fact that their models are not always so intelligent

• Google CEO Sundar Pichai says there's a new term for the current phase of AI: "AJI."
• Pichai said it stands for "artificial jagged intelligence," and is the precursor to AGI.
• AJI is marked by highs and lows, instances of impressive intelligence alongside a near lack of it.

Progress is rarely linear, and AI is no exception.

As academics, independent developers, and the biggest tech companies in the world drive us closer to artificial general intelligence — a still hypothetical form of intelligence that matches human capabilities — they've hit some roadblocks. Many emerging models are prone to hallucinating, misinformation, and simple errors.

Google CEO Sundar Pichai referred to this phase of AI as AJI, or "artificial jagged intelligence," on a recent episode of Lex Fridman's podcast.

"I don't know who used it first, maybe Karpathy did," Pichai said, referring to deep learning and computer vision specialist Andrej Karpathy, who cofounded OpenAI before leaving last year.

AJI is a bit of a metaphor for the trajectory of AI development — jagged, marked at once by sparks of genius and basic mistakes.

In a 2024 X post titled "Jagged Intelligence," Karpathy described the term as a "word I came up with to describe the (strange, unintuitive) fact that state of the art LLMs can both perform extremely impressive tasks (e.g. solve complex math problems) while simultaneously struggle with some very dumb problems." He then posted examples of state of the art large language models failing to understand that 9.9 is bigger than 9.11, making "non-sensical decisions" in a game of tic-tac-toe, and struggling to count.

The issue is that unlike humans, "where a lot of knowledge and problem-solving capabilities are all highly correlated and improve linearly all together, from birth to adulthood," the jagged edges of AI are not always clear or predictable, Karpathy said.

Pichai echoed the idea.

"You see what they can do and then you can trivially find they make numerical errors or counting R's in strawberry or something, which seems to trip up most models," Pichai said. "I feel like we are in the AJI phase where dramatic progress, some things don't work well, but overall, you're seeing lots of progress."

In 2010, when Google DeepMind launched, its team would talk about a 20-year timeline for AGI, Pichai said. Google subsequently acquired DeepMind in 2014. Pichai thinks it'll take a little longer than that, but by 2030, "I would stress it doesn't matter what that definition is because you will have mind-blowing progress on many dimensions."

By then the world will also need a clear system for labeling AI-generated content to "distinguish reality," he said.

"Progress" is a vague term, but Pichai has spoken at length about the benefits we'll see from AI development. At the UN's Summit of the Future in September 2024, he outlined four specific ways that AI would advance humanity — improving access to knowledge in native languages, accelerating scientific discovery, mitigating climate disaster, and contributing to economic progress.

But, first, it needs to learn to spell "strawberry."