Tianjic - was that the riderless bike we looked at last year? It has a CPU and an SNN on the one chip.
https://news.cgtn.com/news/2019-08-02/Chinese-scientists-develop-world-s-first-hybrid-AI-chip--IPeC4ywGLm/index.html Far beyond an auto-pilot bike, Chinese scientists develop world's first hybrid AI chipUpdated 10:38, 03-Aug-2019 ... The bicycle, installed with the AI chip dubbed 'Tianjic', performs self-driving, automatically responding to different situations. The Tianjic chip was developed by a group of researchers from China's Tsinghua University led by Professor Shi Luping.
They installed about 40,000 neurons and 10 million synapses in the fingernail-size chip of 3.8x3.8 square millimeters.It's the first-ever chip that integrates computer-science-oriented and neuroscience-oriented approaches, two general ways to develop artificial general intelligence (AGI).Usually, the two approaches, both representing some of the patterns in which the human brain processes information, rely on different platforms, which are incompatible due to their fundamental differences in the formulations and coding schemes.
But a combination of the two is generally recognized as the best solution.The research team proposed a multi-core architecture to accommodate the two approaches and developed the Tianjic chip on this basis, "can not only accommodate computer-science-based machine-learning algorithms, but also easily implement brain-inspired circuits and several coding schemes," read the research paper abstract.
The second-generation Tianjic was developed from the 2015 version. It features high-speed, high-performance and low-power consumption.
Compared with the current advanced TrueNorth chip from IBM, Tianjic has more comprehensive functions, greater flexibility and better scalability. Its density is increased by 20 percent, speed by at least 10 times, and bandwidth by at least 100 times.Functions of the unmanned bicycle system like voice recognition, autonomous decision-making, and visual tracking use the brain-inspired model, while the target detection, motion control, and obstacle avoidance use the machine-learning algorithm model, researcher Deng Lei told Thepaper.cn.
This is a PCT application by Prof Shi Luping. It is still mostly in Chinese except for the Abstract and Search Report. They have until about the end of June to decide where to file the national phase applications.
A brain-like computing system, comprising an arithmetic/logical operation and control unit, a brain-like coprocessing unit, a memory unit, an external port, and a bus connecting the various units and the external port. The arithmetic/logical operation and control unit is used to perform programming and configuration on the brain-like coprocessing unit, execute arithmetic operations or logical operations, and control the running and data exchange of the other units by means of the bus. The brain-like coprocessing unit is provided with an artificial neural network processing function and a pulsed neural network processing function, and is used to execute artificial neural network computation and pulsed neural network computation on the basis of instructions from the arithmetic/logical operation and control unit and store a computation result in the memory unit.
The present system is able to achieve higher computational efficiency when processing different tasks in general artificial intelligence computation, and achieve real-time response to tasks by means of low-delay continuous execution of computing tasks, while also reducing the energy consumption of computation execution in the whole system. He has an earlier SNN patent which appears to be only filed in China.
https://worldwide.espacenet.com/patent/search/family/053694308/publication/CN104809498A?q=Shi%20Luping%20intelligence CN104809498A Brain-like coprocessor based on neuromorphic circuit The invention provides a brain-like coprocessor based on a neuromorphic circuit. The brain-like coprocessor comprises a storage module storing training characteristic information, a processing module of the neuromorphic circuit based on a hierarchical structure, an encoder and a decoder which are respectively connected with the input end and the output end of the processing module, and a comparison module which is respectively connected with the output end of the storage module and the output end of the decoder. The storage module of the brain-like coprocessor comprises a training characteristic database and/or a configurable training characteristic database.
The processing module comprises a solidification function network module and/or a configurable function network module and has a quite good expansion capability. According to the invention, the brain-like coprocessor employs a distributed storage and parallel cooperative processing mode, is especially suitable for processing non-formal problems and unstructured information and can also process formal problems and structured information, such that the speed of a computer in processing such problems as brain-like calculation, artificial intelligence and the like is substantially accelerated, the energy consumption is reduced, the fault tolerance capability is greatly improved, the programming complexity is reduced, and the computer performance is enhanced. ...
While he seems to have got the spike bit right, he failed to disengage his thinking entirely from 20th century von Neumannism.
Claim 17: ... the neuromorphic device in the neuromorphic node generates a neural-like transmission signal, adds AER information through an on-chip routing network, and transmits to the next neuromorphic node. [AER information includes anode address and an on-chip neuromorphic device address]
(You need the addresses to ride the bus.)
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