On top of that, the chip also helps Intel advance its own manufacturing technology.
The chip also can be programmed better to help researchers tackle more computing tasks.
Some experiments have focused on artificial skin that could give robots a better sense of touch.
“We can detect slippage if a robot hand is picking up a cup,” Davies said.
It differs from conventional chips in profound ways.
You won’t see Loihi 2 in your phone or laptop.
Instead, it’s geared for researchers at automakers,national labsand universities.
Germany’sDeutsche Bahnrailway web connection is testing how well it can optimize train schedules.
Neuromorphic computing
Low power use is a characteristic of biological gray matter, too.
Human brains are made of about 80 billion cells called neurons, connected into elaborate electrical signaling networks.
When enough input signals reach an individual neuron, it fires its own signal to other neurons.
Learning is the process of establishing and reinforcing those connections.
Computer brains
Intel isn’t the only one pursuing the idea.
TheHuman Brain Projectin Europeincludes neuromorphic computingin its work.
Getting it to work requires configuring the proper connections between neurons.
Each neuron is connected to 100 others on average, though some may reach as many as 10,000.
Programming neuromorphic chips is a big challenge, Davies said.
For example, in biological brains, electrical signals are either fully on or fully off.
The chip can be connected to others, too, for greater scale.
One improvement over the first Loihi is better networking that shortens the communication pathways that link neurons.
“The brain achieves accuracy and reliability through tremendous redundancy,” Davies said.
“The hope is indeed we can solve some of the same problems in a more economical way.”
“We have small quantities in the lab now,” Davies said.
Manufacturing at Intel’s full scale of operations, with millions of processors, brings other challenges.
