Your brain does on 20 watts what AI needs a nuclear reactor to attempt. Last week a team figured out how to print something that actually speaks to living brain cells.
Summary
Northwestern University researchers have printed artificial neurons from MoS2 and graphene ink that produce biologically realistic electrical spikes, which living mouse brain cells recognized as natural signals, a breakthrough with major implications for energy-efficient neuromorphic computing.
Similar Articles
The human brain runs on 15W. Simulating it in real time would need 2.7 billion watts. Here's why that gap exists and what's being done about it.
Explores the vast energy efficiency gap between the human brain (15W) and AI hardware (billions of watts needed for real-time simulation), highlighting neuromorphic computing approaches like spin-memristors, phase-change materials, and Super-Turing AI that aim to close this gap.
Neuromorphic Computing With Sound Waves Cuts Power Use
Researchers propose using sound waves and phi-bits to create neuromorphic devices that better mimic biological neurons, potentially enabling faster, more energy-efficient computing for pattern recognition and data analysis.
World-first biological data center packs 16 mn living human neurons
Researchers in Singapore unveiled a world-first biological data center prototype using 16 million living human neurons, aiming to provide a more energy-efficient computing alternative to traditional silicon for AI and other applications.
NSRAM: The Artificial Neuron on a Silicon Chip
The article discusses NSRAM, a new artificial neuron on a silicon chip that aims to dramatically improve energy efficiency in AI by mimicking biological neurons, addressing the high power consumption of GPUs in data centers.
Brain-inspired AI architecture could computing faster and far less power-hungry
A brain-inspired AI architecture promises to deliver faster computing while consuming far less power, potentially advancing energy-efficient AI hardware.