At the global artificial intelligence and robotics summit held today, Huang Jiangji (kk), co-founder of Xiaomi Technology, shared the millet's methodology for the development of artificial intelligence technology with an introduction to a series of millet smart home devices.
The vast majority of people in the industry believe that the success of artificial intelligence is attributed to big data, and Huang Jiangji believes that the development of artificial intelligence cannot be separated from these three preconditions: product + big data + machine learning.
First of all, machine learning and big data are inseparable from high activity products. These products include commonly used software and smart hardware such as wristbands, televisions, boxes, network devices, and smart homes. Huang Jiangji mentioned that millet mobile phones have 20 million MIUI system users, of which 8 applications are daily active 10 million, and 17 are active daily over 1 million. This lays the foundation for big data and machine learning capabilities.
When a highly active product lands, a large amount of data will be generated , and the establishment of high-quality data is achieved through data collection, data cleaning, data mining, and data intelligence. We know that any data will ultimately serve people, so it is especially important to create a portrait of each person. Xiaomi collected 200 TB of data for each scene and data generated by each piece of debris in order to create user portraits.
In addition, Huang Jiangji pointed out that they understand that the content of the user's attention needs to be searched, recommended, guided, and manually operated. Finally, someone asked Huang Jiangji the following two questions:
What do you think is the most intelligent product of Xiaomi?
Huang Jiangji: If you ask an open KK, I will tell you that our products are very intelligent. If you ask the close-door KK, I will tell you that no product is really simple and it is not even necessary for you. The intervention can make things extremely extreme. This is a bit demanding. If you ask us to do the highest degree of intelligence, there is no doubt that our mobile phone. I don’t know if everyone knows that Xiaomi’s development model is not known. After you bought Xiaomi’s mobile phone, our basic system was upgraded once a week. From the first mobile phone started five years ago, today we basically update it once a week. Most of the updates for most of the needs are from users, that is, we can actually let them tell us what the top three things he updated this week are, and tell us the worst three things he is not satisfied with. What is it, we vote for us every week, and we do today's mobile phone is the most mature business, and its degree of intelligence is also relatively mature.
Millet's focus is not on the front end. If it is on the front end, what is the use of data analysis behind you? How can it be industrialized and how can it make money?
Huang Jiangji: I hope that my report today will solve the problem just now. If you do a thing well, you don't need to divide the front end, the back end, the cloud, and the midrange. We must first do a good job of the hardware of this product, and then do a good job of the system's software, only real users are willing to use this product, and then there is the cloud, only the cloud can generate data, after generating this data can go Whether it is machine learning or how to go for deep learning, let it turn into a data model, and make your products more and more intelligent. The commercialization inside can make it more of an experience. The better. If you really want to put intelligence down, if you don't put every ring down, you can't be intelligent.
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