Meta Platforms Inc. (NASDAQ: META) generated $59.36 billion in advertising revenue during the second quarter, representing a 27% year-over-year increase. This figure constituted nearly the entirety of the company’s $60.8 billion total revenue for the period. Despite the strong top-line performance, Meta raised its full-year 2026 capital expenditure guidance range to $130 billion-$145 billion, signaling continued heavy investment in artificial intelligence infrastructure.

Ad Machine Funds AI Ambitions

The financial results underscore the tension between Meta’s profitable core business and its costly AI expansion. Technology analyst Ben Thompson argued that Meta’s advantage lies in its advertising marketplace, where AI-driven improvements in targeting and recommendations can be tested against conversion data, potentially generating billions in incremental revenue.

Chamath Palihapitiya, however, highlighted a strategic branding challenge. He stated that Mark Zuckerberg avoids emphasizing Meta’s advertising roots because "great engineers" prefer to work for companies perceived as leaders in space, search, or AI, rather than an "advertising company." This perception gap exists even as the advertising business provides the capital necessary for Meta’s AI push.

Talent War and Monetization

The increased spending has intensified competition for elite AI talent. Last year, OpenAI CEO Sam Altman disclosed that Meta offered some OpenAI employees signing bonuses of up to $100 million. Zuckerberg personally led recruiting efforts for Meta Superintelligence Labs following setbacks with Llama 4.

While Palihapitiya previously argued that Meta "completely fumbled" its early AI advantage, the company is now pursuing external monetization strategies. These include lower-priced model access and potential compute sales beyond its traditional advertising model.

Market Position and Outlook

Reuters described Meta as still "almost entirely advertising-driven," with analysts noting that the underlying ad business is financing the company’s broader transformation. Emarketer projected in April that Meta could overtake Alphabet Inc. in global digital advertising this year, estimating $243.46 billion in net ad revenue for Meta versus $239.54 billion for Google in 2026.

Benzinga edge rankings indicate that Meta’s stock currently holds a Momentum score in the 9th percentile and a Growth score in the 77th percentile.

Ben Goertzel, often referred to as the 'Father of AGI' and CEO of SingularityNET, argues that investors may be mispricing Meta Platforms (NASDAQ: META) by overvaluing its reliance on compute-heavy artificial intelligence strategies. In an exclusive interview with Benzinga, Goertzel suggested that the market's faith in Meta's 'personal superintelligence' push rests on assumptions that may not hold as the industry evolves beyond simple model scaling.

The Shift From Compute to Architecture

Goertzel contends that the current valuation of Meta reflects a 'scaling-era moat,' based on the belief that bigger models, larger datasets, and greater computing power create durable competitive advantages. While these factors remain necessary building blocks, he argues they are no longer sufficient for achieving superintelligence.

'We're moving into a phase where the real bottleneck is algorithmic and architectural, not raw compute,' Goertzel said. He emphasized that future leadership will depend on advances in cognitive architecture—the underlying design enabling systems to reason and retain knowledge—rather than merely expanding existing models through expensive training runs.

Access Versus Power

Mark Zuckerberg's vision for 'personal superintelligence' focuses on putting advanced AI assistants into the hands of billions of people. Goertzel agrees that AI should not be controlled by a single organization, stating that concentrating superintelligence in one lab aligned to one value set is not a path society should trust.

However, Goertzel argues that Zuckerberg's argument slides from 'distributed power' to 'distributed access,' which are fundamentally different concepts. In his view, Meta's proposal gives billions of users access to AI assistants, but those systems remain developed, trained, priced, and governed by Meta.

'Billions of people get free agents that run on Meta's data centers, trained in Meta's runs, shaped by Meta's fine-tuning, priced by Meta's compute auction, and ultimately governed by Meta's board—that's the old client-server internet wearing a friendlier UI,' Goertzel said.

He described this model as 'home ownership in a company town,' noting that genuine decentralization requires users to have meaningful influence over the systems they use, not just access to them. 'A balance of power among the users of a system is a completely different thing from a balance of power over the system,' he stated.

Open Source Versus Walled Gardens

Goertzel highlighted that open, distributed communities are likely to out-innovate single closed shops in this next phase of development. Drawing parallels to the success of Linux and the web stack, he noted that decentralized innovation tends to surpass proprietary approaches when architectural design becomes the primary driver of progress.

Instead of a corporate walled garden, Goertzel argues beneficial superintelligence should be built on open-source ecosystems with open governance. This allows companies to build products on shared infrastructure rather than owning the underlying platform. The ability for users and developers to leave such ecosystems keeps them accountable, he argued. 'Exit is always on the table, and it's exactly the availability of exit that keeps everybody honest.'

By contrast, Goertzel says companies operating closed AI ecosystems face inverted incentives. 'Try to build the 'open network' inside a corporate walled garden instead, and the incentives just invert on you,' he said. 'All the engineering effort goes into stopping people from taking their stuff and leaving, rather than into actually serving them.'

What the Numbers Show

The core divergence lies in the definition of competitive advantage. While Meta's strategy leverages massive financial resources to secure compute and data, Goertzel's analysis suggests that the marginal value of additional scaling is diminishing. The risk for investors is not that Meta lacks resources, but that the metric used to price its moat—scale—is becoming less relevant than architectural efficiency and open collaboration. Betting heavily on a walled garden's permanence right as the walls themselves are starting to stop mattering strikes him as a 'pretty real mispricing.'