@SingularityNET As Big Tech companies continue channeling billions of research dollars and attention into developing and scaling Large Language Models (LLMs), a fundamental question is emerging in tech circles: Are LLMs actually leading us away from true Artificial General Intelligence (AGI)?

At a recent Consensus 2025 panel addressing whether Web3 is losing the AI race, our CEO, Dr. Ben Goertzel, challenged the conventional wisdom driving investment strategies at many leading AI companies and sovereign wealth funds, including the recent multi-billion-dollar investments from Saudi Arabia and the UAE in US AI infrastructure.

"I would quote Yan LeCun, a pioneer of deep learning and the head of AI at Facebook, who said on the highway to AGI, LLMs are an off-ramp," Dr. Goertzel told attendees, rejecting the premise that Web3 approaches are falling behind centralized AI development: "If you've gotten off the off-ramp, it doesn't matter if you're going 1,000 miles an hour and the other guy's only going 300 miles an hour if they're going on the right highway to the destination."

The panel, which featured Ben Fielding (Founder, Gensyn), Jesus Rodriguez (CEO, IntoTheBlock), Clara Tsao (Founding Officer, Filecoin Foundation), and Jeff Wilser (Founder and Host, The People's AI Podcast), revealed a stark divide in how industry experts view the future of decentralized AI. While other panelists pointed to Web3's current disadvantages in talent, datasets, and infrastructure, Dr. Goertzel addressed a deeper issue: the incremental improvement of LLMs is not a viable approach to achieving human-level AGI.

However, "If scaling up transformer neural nets is the crux of how you get to AGI, it's hard to see how the US and Chinese governments and the Big Tech companies in their orbit don't win the race," Dr. Goertzel acknowledged, noting the immense capital these entities are deploying.