Calculating power of nerve rod

1. No, the hardware specially used to assist AI learning in neural stick calculation has nothing to do with the hardware of the computer itself. It can't improve the performance of the hardware.

2. This neural computing stick has a very wide range of uses. It is a very sacred thing to calculate things, but most people don't use it

3. The neural computing stick cannot be used as a graphics card. Neural compute stick (NCS) is used as an accelerator - it is inserted into the computer to gain more local computing power when training and designing new neural networks. Users can chain multiple NCS together to improve linear performance. The neural computing stick can easily and quickly execute the neural network locally.

4. In theory, it's OK. If you want to change the software, only pcplus and Lite2 are tested

5. Now it seems to be very powerful. I hope that human beings can give full play to their more powerful functions and roles in the future

6. Deep learning neural network accelerator chip development scheme provides computing power for terminal and cloud AI procts or systems.

7. It's for deep learning. Let machine learn. Because of the direct, high computational efficiency
video surveillance, reference eye. It's a big integration project

8. Answer: 1) Linux system can check whether the model path is correct and whether the model file is complete. You can use md5sum command to check whether the file is complete and whether you have read permission; 2) Whether the Android system adds read and write permissions to the file in XML, and whether the path is correct.

9. For feedforward neural networks, the robustness of neural networks means that when the input information or neural networks have limited perturbation, the neural networks can still maintain the normal input-output relationship; For the feedback neural network, the robustness of neural network means that when the input information or neural network has limited perturbation, the neural network can still maintain a stable input-output relationship.

10. No
today's computers are logic computers with poor perceptual thinking ability, and quantum computers are still far away

according to the current theory and engineering practice, no matter how large the scale of neural network algorithm is, whether you really want the robot to move a finger or write programs in C + + or other languages honestly

neural network is a kind of information processing algorithm in essence, and only programming can make robot proce behavior. At present, there is no theory to integrate the two, that is, we can't achieve the purpose of automatic programming through information processing, and we can't generate unpredictable information through programming. Without this foundation, we can only say that we haven't even touched it.