How the human brain effects AI and AGI

This article summarizes the research paper "When Brain-inspired AI Meets AGI"

The human brain, an intricately woven network of approximately 10,000 synapses connecting distinct neurons, manifests a multifaceted repertoire of cognitive abilities:

• Sensory Acumen: The brain's faculties encompass vision, auditory perception, and tactile sensation, collectively synthesizing an expansive array of sensory inputs.

• Parallel Information Processing: Operating in parallel akin to a high-performance computing system, the brain orchestrates the simultaneous execution of myriad cognitive tasks.

• Neuroplasticity: Distinguished by its plastic nature, the brain demonstrates an exceptional capacity to reconfigure its structural framework in response to environmental stimuli, thereby furnishing an exceptional aptitude for adaptive learning.

• Cognitive Proficiency: The brain demonstrates adeptness in problem-solving and decision-making, reflecting its capacity for intricate deliberation.

• Innovation Nexus: Embedded within the neural matrix is an innate wellspring of creativity, driving artistic expression and inventive ideation.

The nexus of psychology, neuroscience, and artificial intelligence (AI) has engendered a trajectory toward the realization of Artificial General Intelligence (AGI). Notably, this symbiosis has yielded transformative outcomes:

A paradigmatic instance is the infusion of neural insights into AI, where the seminal Transformer Model has become the cornerstone underpinning neural networks such as BERT and GPT. These achievements in artificial neural networks and convolutional neural networks underscore profound correspondences with their biological counterparts.

Within the realm of cerebral-mimetic concepts, innovations like the Adversarial Visual Attention Network (BI-AVAN), Core-periphery Principle Guided Vision Transformer (CP-ViT), and Spiking Neural Networks (SNNs) have emerged as pivotal developments.

Pioneering AGI-Enabling Hardware:

Neuromorphic computing, representing a novel facet of hardware design, emulates the computational paradigms intrinsic to the human brain. This innovative domain holds the potential to catalyze AGI breakthroughs, thus forging a tangible bridge between cognitive human faculties and machine intelligence.

Intrinsic Traits of AGI:

Central to the AGI landscape are Large Language Models (LLMs), typified by exemplars like GPT-2 and GPT-3. These models, characterized by their expansive linguistic capabilities, furnish insightful parallels to brain-inspired AGI. Their utility extends to powering conversational agents, content generation, and translation engines.

The entwined relationship between LLM scaling and cognitive attributes mirrors the phenomenon of a larger brain exhibiting heightened cognitive aptitude. Analogously, scaled LLMs evince enhanced acumen for acquiring novel proficiencies with reduced exemplars. This correlation stimulates contemplation on the indispensability of scaling in the quest for AGI actualization.

Embracing Multimodal Cognitive Paradigms:

A salient facet of cerebral function is the ability to process information emanating from disparate sensory modalities in tandem. AGI's trajectory towards sophistication hinges upon Multimodal Information Processing (MIP). Exemplars such as CLIP, DALL-E, and VisualGPT exemplify this, encapsulating the fusion of heterogeneous sensory data into a cohesive cognitive panorama.

As we navigate a realm where the intricate architecture of the human brain guides the evolution of artificial intelligence, we stand at the cusp of epochal advancements. Deciphering the intricacies of cognition paves the way for AGI to transcend conventional boundaries, redefining the contours of human innovation.

References:

Zhao, Lin, et al. “When Brain-Inspired AI Meets Agi.” arXiv.Org, 28 Mar. 2023, arxiv.org/abs/2303.15935.