Demis Hassabis, the CEO of Google DeepMind, pinpointed a significant obstacle in the path of Artificial General Intelligence (AGI) development.
What Happened: Hassabis, in a recent episode of the “Google for Developers” podcast, highlighted the lack of consistency in AI as a major barrier to achieving AGI, according to a Business Insider report.
He illustrated this inconsistency by explaining that while advanced AI models like Google’s Gemini can win gold medals at the International Mathematical Olympiad, they still struggle with basic high school math problems. This inconsistency, he said, is what is holding AI back from achieving full AGI.
See Also: ClarityCheck Launches Innovative Reverse Lookup Tool to Empower Users Against Digital Scams
Hassabis also echoed Sundar Pichai, the CEO of Alphabet Inc. GOOGL GOOG, who previously referred to the current stage of AI development as “AJI” — artificial jagged intelligence. This term describes systems that excel in some areas but fail in others.
He further emphasized that addressing AI’s inconsistency issues will require more than just scaling up data and computing. He suggested that the industry needs better testing and new, more challenging benchmarks to determine precisely what the models excel at and what they don’t.
Why It Matters: The development of AGI, a theoretical threshold where AI can reason like humans, is a hot topic in the tech industry. Hassabis had previously offered a more cautious outlook on the arrival of AGI than Google’s co-founder, Sergey Brin. He had also pointed out that the industry needs to set a higher bar for AGI.
Meanwhile, Alibaba Cloud pioneer Wang Jian has pushed back against the buzz around AGI and artificial superintelligence (ASI), arguing that such labels oversimplify the nuanced growth of AI systems.
Read Next:
Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.
Photo courtesy: Shutterstock