Meta Platforms, Inc‘s (NASDAQ:META) multibillion-dollar push toward “personal superintelligence” has reinforced the view that the AI race will be won by companies with the deepest pockets, biggest training runs and most powerful computing infrastructure. But Ben Goertzel, often referred to as the ‘Father of AGI’, believes investors may be placing too much faith in precisely those advantages.
In an exclusive email interview with Benzinga, the SingularityNET CEO argued that Meta’s perceived AI moat is rooted in assumptions that may not hold as the industry moves beyond today’s scaling-focused approach to AI development.
Meta’s AI Advantage May Rest on an Outdated Assumption
Goertzel expects investors to continue pricing Meta’s AI leadership on the idea that bigger models, larger datasets and greater computing power will continue to create lasting competitive advantages.
“The moat being priced into these valuations is a scaling-era moat,” he said. That assumption reflects a phase of AI development where success depended largely on scaling models through increasingly expensive training runs.
“It assumes durable advantage comes from bigger training runs and locked-up weights,” Goertzel added.
While Meta has invested heavily in building that capability, Goertzel argues the industry is approaching a point where simply scaling existing models may no longer be enough to stay ahead.
Instead, he believes the next breakthroughs will depend on advances in AI architecture—the underlying design that enables systems to reason, retain knowledge and develop more sophisticated capabilities.
“We’re moving into a phase where the real bottleneck is algorithmic and architectural, not raw compute,” he said.
Why Goertzel Thinks Investors Should Look Beyond Compute
Goertzel’s criticism is not that compute, data and capital have become irrelevant. Rather, he argues they are necessary building blocks, but no longer the defining source of competitive advantage.
“Compute plus data, plus money” are necessary, he said, but “nowhere near sufficient” to build superintelligence.
Instead, future leadership will depend on better cognitive architecture rather than simply expanding existing models, he explained. That could change how investors consider companies whose competitive edge is closely tied to scale.
Goertzel also says open, distributed communities could prove particularly effective in this next phase of AI development. “That’s precisely the terrain where an open, distributed community tends to out-innovate a single closed shop, the way it has with Linux, with the web stack, with a dozen other technologies before this one,” he said.
For investors, his message is not that Meta cannot remain an AI leader, but that the assumptions supporting its competitive moat deserve closer scrutiny if architectural innovation begins to matter more than scale alone.
“Betting heavily on a walled garden’s permanence right as the walls themselves are starting to stop mattering strikes me as a pretty real mispricing,” Goertzel said.
Image Courtesy SingularityNet
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