Revolutionizing AI: A New Model Inspired by the Human Brain’s Efficiency
In a groundbreaking development, researchers at Cold Spring Harbor Laboratory (CSHL) have designed a new AI model inspired by the efficiency of the human brain. This innovative model allows AI neurons to receive feedback and adjust in real time, enhancing learning and memory processes.
The current AI technologies, while impressive in their capabilities to read, talk, and analyze data, still face limitations in interacting with the physical world. Kyle Daruwalla, a NeuroAI Scholar at CSHL, recognized these challenges and sought unconventional ways to design AI that can overcome computational obstacles.
Taking inspiration from the human brain, Daruwalla developed a new machine-learning model that mimics how our brains efficiently process and adjust data. By allowing individual AI neurons to receive feedback and adjust on the fly, data processing becomes more efficient and real-time.
The new model provides evidence for a theory linking working memory with learning and academic performance. Working memory is crucial for staying on task while recalling stored knowledge and experiences, and the new AI model incorporates this concept into its design.
This breakthrough could lead to a new generation of AI that learns more like humans, enhancing both the AI and neuroscience fields. By bridging the gap between AI and neuroscience, this innovation paves the way for more efficient and accessible AI systems.
The research, published in Frontiers in Computational Neuroscience, showcases the potential of combining neuroscience principles with AI technology. With this new model, AI may soon be able to learn and adapt in a manner more akin to human cognition, marking a significant advancement in the field of artificial intelligence.
