Many works of science fiction have been conceived around the idea that machines will become more and more human. Machines that think, learn and make decisions the way humans do have been the subject of speculative fears even as scientists and engineers work to create them.
With The Singularity just looming on the horizon, there were some fascinating developments in the world of artificial intelligence and machine learning that we wanted to delve into.
Purdue University researchers are building material inspired by the human brain for artificial intelligence (AI) to help AI learn continuously over time. The goal of the project is to make AI more portable so that it can be used in isolated environments such as robots in space or autonomous vehicles. By building AI directly into hardware rather than running it as software, these machines could operate more efficiently.
MIT engineers have designed a brain-inspired chip by putting tens of thousands of artificial brain synapses, or memristors, on a single chip smaller than a piece of confetti. Memristors (memory transistors) are silicon-based components that mimic the information transmission synapses of the human brain. This so-called “brain-on-chip” could one day be embedded in small, wearable AI devices that could perform complex computational tasks currently only performed by supercomputers.
And researchers from Northwestern University and the University of Hong Kong have has developed a device inspired by the human brain that simulates human learning. The device is able to learn by association via synaptic transistors that process and store information at the same time.
Here are more details about these three projects that aim to allow computers to imitate the human brain:
The Purdue Project
In an article published in Science in February, Purdue researchers explained how computer chips could dynamically rewire themselves to absorb new data like the brain does, allowing AI to continue learning over time.
To enable learning, the brain is constantly forming new connections between neurons. So, to build a brain-inspired computer or machine, the circuitry of a computer chip must also change. However, a circuit that a computer has used for years is the same circuit that was built for the computer at the factory.
Therefore, researchers must be able to “continuously program, reprogram and change the chip”, According to Shriram Ramanathanprofessor in the School of Materials Engineering at Purdue University whose work involves discovering how materials could mimic the brain to improve computing.
Ramanathan and his team have built new hardware that can be reprogrammed with electrical pulses on demand. The team believes that because this device is adaptable, it will be able to take on all the functions needed to build a computer inspired by the human brain.
“Through simulations of the experimental data, Purdue team collaborators from Santa Clara University and Portland State University have shown that the internal physics of this device create a dynamic structure for a neural network machine that can recognize EKG patterns and numbers more efficiently than static networks,” according to Purdue. “This neural network uses ‘reservoir computing,’ which explains how different parts of a brain communicate and transfer informations.”
The team now aims to demonstrate this on large-scale test chips that could be exploited to develop a brain-inspired computer, the researchers said.
MIT’s “Brain on a Chip”
MIT researchers are preparing for the day when people ‘might be able to carry artificial brains [that can work] without connecting to supercomputers, the Internet or the cloud”, according to a statement.
“Like a brain synapse, a memristor would also be able to ‘remember’ the value associated with a given current strength and produce the exact same signal the next time it receives a similar current,” the statement said. “This could ensure that the answer to a complex equation, or the visual classification of an object, is reliable – a feat that normally involves multiple transistors and capacitors.”
In an article published in “Nature’s nanotechnology“, the scientists explained how their brain-inspired chip could remember a grayscale image of Captain America’s shield – each pixel was associated with a corresponding memristor on the chip – and recreate the same crisp image of the shield multiple times. time.
In the paper, the MIT researchers pointed out that its “brain on a chip” could be used to perform complex tasks on mobile devices – tasks that only supercomputers can currently handle.
Brain-like device simulates human learning
Inspired by Russian psychologist Ivan Pavlov’s book, which trained dogs to associate the sound of a bell with food, researchers from Northwestern and the University of Hong Kong trained their computing device to associate light with pressure, according to a press release.. the research has been published in the journal “Nature Communications”.
This new device mimics the brain by using electrochemical “synaptic transistors” to process and store information at the same time, the release noted. “These synapses allow the brain to operate in a highly parallel, fault-tolerant, and energy-efficient manner,” the statement read. The device’s plastic organic transistors work like a biological synapse.
“With its brain-like capability, the new transistor and circuitry could potentially overcome the limitations of traditional computing, including their power-hungry hardware and limited ability to multi-task,” the statement said. “The brain-like device also has higher fault tolerance, continuing to operate smoothly even when some components fail.”
In today’s computer systems, memory and logic are physically separated; however, combining these functions would save space and reduce energy costs. And the new computing device’s flexible, plastic-like polymers would allow researchers to integrate it into smart robotics, wearable electronics and even devices implanted in humans.
Conclusion
While a robot uprising is still firmly in the realm of science fiction, these advances are just some of the ways scientists are working to replicate the biological machinery of the brain and it could one day lead to computers that work like the human brain.
