Transistor mirrors human brain function
Researchers developed a groundbreaking synaptic transistor inspired by the human brain. This device can simultaneously process and store information, mimicking the brain’s capacity for higher-level thinking
Unlike previous brain-like computing devices, this transistor remains stable at room temperature, operates efficiently, consumes minimal energy, and retains stored information even when powered off, making it suitable for real-world applications.
The study presents a major step forward in creating AI systems with greater energy efficiency and advanced cognitive functions.
Key Facts:
- The synaptic transistor combines two atomically thin materials, bilayer graphene and hexagonal boron nitride, in a moiré pattern to achieve neuromorphic functionality.
- It recognizes patterns and demonstrates associative learning, a form of higher-level cognition, even with imperfect input.
- This technology represents a significant shift away from traditional transistor-based computing, aiming to improve energy efficiency and processing capabilities for AI and machine learning tasks.
Designed by researchers at Northwestern University, Boston College and the Massachusetts Institute of Technology (MIT), the device simultaneously processes and stores information just like the human brain. In new experiments, the researchers demonstrated that the transistor goes beyond simple machine-learning tasks to categorize data and is capable of performing associative learning.
Source: Northwestern University
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