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Williams says it’s time for memristors to scale up. “Our lab results have been good, and it’s time to test memristors in the fab.”
Memristors have similar physical behavior as synapses in the human brain. Production scale memristor memory with tens of billions of memristors should mean that memristors that mimic over one hundred billion synapses could only be a few years away. The human brain has one hundred trillion synapses. A human scale emulation of one hundred trillion synapses might only take one hundred near term memristor chips. Having comparable hardware in terms of numbers of similar components does not mean you can make them behave like a brain, but getting hardware with the right number of neurons and synapses would give researchers a reasonable chance at human brain emulation. The hardware could be ready in the 2020-2025 timeframe for neurons and synapses.
UPDATE: Welcome Instapundit readers.
There are levels of detail of possible brain emulation.
Possible Brain Emulation Complications
The Synapse program is trying to build an electronic element like a brain synapse and then scale to brain levels. They are targeting 220 trillion synapses for a human cerebral cortex, which is 400 times larger than a recently completed rat cortex simulation. A successful synapse circuit will be 20 or more times better than a transistor for simulating a brain. The memristor could be a better synapse circuit.
Memristors are nanoscale devices with a variable resistance and the ability to remember their resistance when power is off. HP fabricates them using conventional lithography techniques: laying down a series of parallel metal nanowires, coating the wires with a layer of titanium dioxide a few nanometers thick, and then laying down a second array of wires perpendicular to the first. The points where the wires cross are the memristors, and each can be as small as about three nanometers. This cross-bar structure also makes it possible to pack memristors in very dense arrays.
Both flash and memristor memory are nonvolatile, meaning they hold on to data even when power is cut off. Flash has some limitations, though. It can only withstand about 100,000 data-writing cycles, and, like all devices based on silicon transistors, it will come up against physical limits as it’s scaled to make more storage-dense memory devices. Williams says that memristor memory can withstand up to about a million read-write cycles in lab tests. “We will be able to scale faster and farther than flash because the memristor is a very simple structure, and it can be stacked,” Williams says.
The memristor circuits reported in Nature are also capable of both memory and logic, functions that are done in separate devices in today’s computers. “Most of the energy used for computation today is used to move the data around” between the hard drive and the processor, says Williams. A future memristor-based device that provided both functions could save a lot of energy and help computers keep getting faster, even as silicon reaches its physical limits.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
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