Growing AI like a Child, at Scale

Humans never "learn" intelligence. Humans develop intelligence. Biological lives on this planet take heavy advantage of intelligent primitives embedded in their genes. Cats never "learn" to backflip. Birds never "learn" to fly. In the same way, humans never "learn" to cognize. Humans are born with a set of core cognition, that sets the foundation for our perception and action in the physical world.

Our core cognition unravels through a specific developmental trajectory as we grow into adulthood. Here, we seek to do the same for our machines, leveraging heavy cognitive literature in developmental psychology, e.g., Piagetian theory of cognitive development, to design our growing up curriculum. In addition, we also want to learn from the current success of machine intelligence, specifically the scaling law.

Instead of putting growing up and scaling up into opposite camps, we argue the next step towards human-like artificial general intelligence is to grow AI like a child, at scale. We come together as GrowAI, an open-source community uniting researchers from computer science, cognitive science, psychology, linguistics, philosophy, and beyond. Our ongoing research focuses on the following areas:

• Cognitive Competence: Investigating and evaluating the cognitive behaviors and limitations of pre-trained models beyond leaderboard chasing.
• Core Knowledge: Identifying and building fundamental knowledge and core cognitive scenarios for benchmarking and evaluating human-like intelligence.
• Developmental AI: Understanding the developmental trajectories and training dynamics of scalable systems toward human capabilities.