Meta is going all out to win the 'superintelligence' race

Zuckerberg is doing all he can to leapfrog Generative AI and develop machines that can 'think'

- SIDDHARTH PAI

Meta's audacious pivot towards what it calls 'superintelligence' marks more than a renewal of its AI ambitions; it signals a philosophical recalibration.

A few days ago, Meta unveiled a nearly $15 billion campaign to chase a future beyond conventional AI—an initiative that has seen the recruitment of Scale AI's prodigy founder Alexandr Wang and the launch of a dedicated 'superintelligence' lab under the CEO's own gaze (bit.ly/3ZHgYIh).

This is not merely an attempt to catch up; it is a strategic gambit to leapfrog competitors like OpenAI, Google DeepMind, Anthropic and xAI.

Currently, Meta's AI offerings, its Llama family, primarily reside within the predictive and Generative AI paradigm.

These systems excel at forecasting text sequences or generating images and dialogue, but they lack the structural scaffolding required for reasoning, planning and understanding the physical world.

Meta's chief AI scientist Yann LeCun has been eloquent on this front, arguing in a 2024 Financial Times interview that large language models, while powerful, are fundamentally constrained—they grasp patterns but not underlying logic, memory or causal inference (bit.ly/3SVYYGi).

For LeCun and his team, superintelligence denotes AI that transcends such limitations and is capable of building internal world models and achieving reasoning comparable to—or exceeding—human cognition.

This definition distances itself sharply from today's predictive AI, which statistically extrapolates from patterns, as well as GenAI, which crafts plausible outputs, such as text or images.

Superintelligence, by contrast, aspires for general-purpose cognitive ability.