Exploring the Mysteries of the Biological Brain and Digital Brain: Insights from Ant Group’s Graph Computing Lab and Fudan University

At the 2024 Inclusion·外滩大会创新者舞台, Professor Wang Yun from Fudan University’s Brain Science Institute and Zhu Xiaowei from Ant Group’s Graph Computing Lab presented their joint exploration of the "Biological Brain and Digital Brain".

Professor Wang described the human brain as a 2.5‑3% body‑weight organ that consumes 20% of the body's oxygen, containing roughly 100 billion neurons and ten thousand synapses per neuron, forming complex networks that enable cognition, memory, and emotion, while noting that humanity currently understands only about 10% of its functions and faces challenges in data acquisition, analysis, and dynamic network modeling.

The two institutions announced a collaborative project titled “Graph Computing‑Based Brain Simulation Architecture,” aiming to create a next‑generation, large‑scale, high‑precision brain simulation system.

Zhu Xiaowei defined a digital brain in two ways: (1) a virtual brain aligned with biological brain in function, structure, and behavior, and (2) an intelligent software or system operating in the digital realm, noting that current AI models can be seen as digital brains but that achieving parity with biological brains requires breakthroughs in computing power, algorithms, and system design.

He cited recent advances such as the FlyWire dataset (140 k neurons and over 30 million synaptic connections) and the inspiration of convolutional neural networks and multilayer perceptrons from brain science, while emphasizing the limitations of existing artificial neural networks, particularly the lack of intra‑ and inter‑regional feedback connections, and calling for future research to incorporate richer feedback mechanisms.

In conclusion, Zhu highlighted that studying both biological and digital brains can mutually benefit each other—digital brains can aid biological brain research, and insights from neuroscience can improve AI models—underscoring the power of interdisciplinary collaboration for future technological innovation.