IBM developed a chip called TrueNorth that simulates the function of the human brain. IBM is testing the chip to prove how fast it is and how much energy it can save compared to existing computers.
The result of the positive confrontation is impressive. According to IBM, TrueNorth can use deep learning techniques to make decisions by associating analysis and judging the possibility, like the human brain. New computers consume less energy than other computers that have the same purpose.
IBM stated in its blog that TrueNorth chips have learning and computing capabilities. It creates a possibility that we can embed intelligence in all computing devices, including the Internet of Things, smart phones, robots, cars, cloud computing, and supercomputing.
Earlier this year, IBM demonstrated the chip, when the chip was loaded into a computer called the NS16e. It was modeled on the human brain. The computer can recognize pictures, speech, and patterns, which are performed by the processing unit's neural network.
The human brain has 100 billion neurons that can communicate with each other through trillions of neural nodes (synapses). Among them, visual cortex can identify visual information, and other parts are responsible for motor function.
Like the brain, the NS16e has "digital neurons," but the number is much smaller and the system includes 16 TrueNorth chips. Each TrueNorth chip has 1 million neurons and 256 million synapses, which are connected by circuits. The NS16e has a redesigned memory, computing, and communications subsystem that can handle data processing and consume much less power.
IBM has said that TrueNorth processors can classify image data at 1200-2600 frames per second, consuming only 25-275 milliwatts of energy. The processor also recognizes picture patterns that were generated with 50-100 cameras at 24 frames per second. If the chip is installed in a cell phone, it can also have this capability, without charging for a few days.
Compared with today's servers, new chips consume much less energy. Today's servers rely on traditional chips such as GPUs, CPUs, and FPGAs. Enterprises use these components to recognize pictures and voice. Facebook, Google, Microsoft, and Baidu use deep learning technology to learn by parsing answers related to pictures and speech recognition. These deep learning systems are generally GPU-driven and have a power of more than 150 watts.
TrueNorth has algorithms and deep learning models, including recognition patterns that can relate past and existing data. IBM developed corresponding algorithms for different deep learning models, but the chips can be applied to existing systems such as MatConvNet. Essentially, developers can use MatConvNet to develop learning models and TrueNorth is responsible for background processing. There is no need for developers to directly contact TrueNorth.
IBM's strategy is somewhat similar to early game development. At first, programmers did not touch the GPU because most people didn't know how to use the features of the chip. Recently, Vulkan replaced the OpenGL API and showed the GPU functionality directly to programmers so that they can better utilize the capabilities of the chip.
The potential of deep learning has been demonstrated in driverless cars. A powerful computer guides the safe movement of cars and correctly identifies signals, lanes, and other objects. Like chips in cars and servers, TrueNorth performs low-level processing on each neuron and then summarizes the results to identify the objects in the image or identify a sound. Nvidia and Intel's chips also use the same technology, but their chip power consumption is much higher than TrueNorth.
The TrueNorth chip is still in its early stages of development. IBM plans to develop a computer that will install TrueNorth chips with specifications that are comparable to the human brain, but IBM faces certain challenges, mainly because the computer is too big to develop algorithms and applications.
Since 2004, IBM has been developing brain chips. In 2009, computers have been able to simulate the brains of cats. In 2011, IBM developed a prototype chip with 256 digital neurons with pattern recognition capabilities. If you really want to develop a computer and let it simulate the human brain, it will take a long time.
IBM is also developing quantum computers, which can replace existing PCs and servers. The design of existing devices has been very old and has been used for decades. Other companies and institutions are also developing chips that can simulate the human brain, such as Hewlett Packard Enterprise, Stanford University, Heidelberg University in Germany, and Manchester University in the United Kingdom.
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",n+="
",n+=" "+e.stitle+"",n+="
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Source: pcworld
.wxdigi { padding:20px 0; border-top: 1px dotted DBDBDB; } .wxdigi dt { display:inline; float:center; margin-right:17px; } .wxdigi dd strong { display:inline-block; padding-top :0px; color:414141; font-size:14px; } .wxdigi dd { font-size:14px; color:606060; }
Teaching Equipment
Special equipment for university physics laboratory
Teaching Equipment,Optical Bench Kit,Optical Instruments In Physics,Electrooptical Modulator Experimental Instrument
Yuheng Optics Co., Ltd.(Changchun) , https://www.yhenoptics.com