Research

Computing

Neuromorphic Computing

Neuromorphic Computing mimics the structure of the human brain by emulating the spiking activity of individual neurons, which allows the flexibility to simulate only the active neurons in the network to achieve extreme computational efficiency. This is further enhanced by the binary information transfer paradigm represented by a spike, resulting in an impressive reduction in memory, power, and computational overhead. The simulation of single neurons also allows the implementation of biologically plausible learning methods that enable local learning.

EmbodiedIntelligence

Embodied Intelligence

Embodied intelligence focuses on the fusion of physical robot bodies with cognitive processes. This approach integrates sensory perception, motor control, and cognition and mimics how living organisms interact and adapt to their environment. Embodied intelligence systems use real-world experience as a critical component of their cognitive processes, enabling adaptive behavior and learning through direct interaction with the physical environment.

GeneralistAI

Generalist AI

Unlike specialized AI, which excels only in specific domains, Generalist AI, or Artificial General Intelligence (AGI), aims to replicate human-like cognitive abilities for learning and excelling at multiple tasks. At the core of AGI lies the ability to generalize, which implies learning from previous experiences and extrapolating that information to new, unseen situations. This ability to constantly learn from experiences without retraining or overwriting previous information is also known as Continual Learning.

Student Works
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