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"Car Public Opinion" Issue 23

Author Miao Jian Research Institute

May is an important period for the automobile market. Many new cars exhibited at the Shanghai Auto Show began to appear on the market one after another. Joint-venture brands and independent brands are competing to launch brand-new, mid-term and annual models, bringing more choices to consumers. This also makes the domestic auto market more exciting and interesting.

According to the statistics of Miaojian Information Public Opinion Monitoring Platform, in the TOP10 public opinion hot list of new cars listed in May, domestic brands dominated, and among the new cars listed, fuel/plug-in models accounted for over 60%.

40% of the new models were launched in this month’s list, mainly medium and large SUVs. Among them, the price is divided into multiple grades, the highest is 389,800 yuan (Chuanqi E9) and the lowest is 79,800 yuan (Baojun Yueye).

In the list, the old best-selling models Accord and LaCrosse are all replacement models. Small and medium-term models are all plug-in models except Seal, which is pure electric.

01

List of new cars on the market: the new Haval Xiaolong won the No.1 new car communication in May, and BYD dominated the list of three models.

Haval Xiaolong (brand new) is the model with the highest heat index this month. On May 15th, the launch conference of Haval brand new energy night and Haval Xiaolong series was successfully held in Beijing, officially releasing the brand new energy strategy of Haval brand and launching a brand new energy product-Haval Xiaolong series, with the starting price of new cars ranging from 139,800 to 179,800 yuan.

Nearly 6.5% of Haval Xiaolong’s sound volume is generated at the client. Know the car emperor, today’s headlines and Sina Weibo are the main communication channels, among which Weibo has 91,000 interactive voices, which is the second highest interactive car in this month’s list. "Intelligent four-wheel drive" and "travel audio-visual room" are the main communication points of Haval Xiaolong.

There were many hot spots in the launch of Haval Xiaolong. In addition to the introduction of new cars, Feng Mu, president of Great Wall Motor, launched the "Five Questions of the Soul" on the spot. In addition to expounding the current situation of China’s automobile market and the development prospect of Haval brand, Feng Mu also pointed out the bad practices of disrupting the market, such as friends raising the water army and worrying product quality, saying that some car companies regard "controlling public opinion as the primary productivity" and even commented that some car companies "won sales and lost the bottom line"

Guangqi Honda Accord (replacement) is another popular model this month, which was officially launched on May 20th. As an old-fashioned best-selling model, the new car was widely discussed and paid attention to during the listing period, and "brand-new" and "intelligence" were the main communication points.

Guangzhou Automobile Chuanqi brand continues to maintain the new strength and communication potential of "new cars every month".

During the listing of Chuanqi E9, Guangzhou Automobile Chuanqi 4S stores all over the country, with today’s headlines, knowing the car emperor and car home as the main positions, made a lot of momentum. The marketing text is short, matched with key words of product characteristics, emphasizing electricity and oil, four-fold luxury gifts and so on. Reflect saving and highlight preferential treatment.

02

Pre-sale release list: two brand-new models were officially unveiled, and Musa’s publicity momentum was strong.

In addition to the listed models, the models pre-sold and unveiled in May are mainly medium/large SUVs. Fuel vehicles account for 60%. There are two brand-new models, namely Beijing Hyundai Mussa and JAC Yttrium 3. Most of the other models were changed in the medium term.

On May 17th, MUFASA, a brand-new compact SUV product of Beijing Hyundai, officially announced its Chinese name-Musa, and started the pre-sale. Musa spread strongly, and "smart two rooms and one living room on board" was its main propaganda point.

On May 20th, the global pre-sale conference of Yttrium 3, an intelligent pure electric car of Jiangqi Group, was held in Hangzhou. Yttrium 3 (brand new) is Jianghuai Yttrium’s first intelligent pure electric vehicle. The new car is positioned as a pure electric small car with a pre-sale price of 97,900 yuan, focusing on "space, battery life and safety".

03

Observation on the launch of new cars this month

Enter the hall! Stars help out

Chuanqi E9 conference site: held in the Great Hall of the People, Zhang Yue, general manager of Guangzhou Automobile Passenger Car, explained the whole process, and sports star Su Bingtian helped out …

Combined with selling points, multi-scene layout

Bao Junyue also released the conference site: multiple scenes fit different product points of Bao Junyue, such as outdoor cross-country, modified life, intelligent driving, etc., so that the audience can understand the products more intuitively …

Senior executives go into battle together and explain in sections.

Haval Xiaolong conference site: Feng Mu, president of Great Wall Motor, and Qiao Xinyu, executive deputy general manager of Haval brand, respectively took the stage to explain …

Accord conference site: Li Jin, director of Guangqi Honda Automobile Co., Ltd., and Xiao Zhihui, general manager of the four-wheel development center of Honda Technical Research Industry Co., Ltd., took the stage to explain respectively.

Song ProD M-i conference site: Lu Tian, general manager of BYD Dynasty Network Sales Division, and Yu Yang, product manager of BYD Dynasty Network Sales Division, respectively took the stage to explain.

　　Photo courtesy of vision china

　　Ai growing pains

　　Editor’s note In recent years, artificial intelligence has developed rapidly and its application fields have been expanding. However, at the same time, AI "rollover" cases are frequently searched. Based on this, this edition opens the column "AI Growing Pains" to focus on AI "rollover" events, analyze the phenomenon, analyze the reasons, explore the solutions, and look forward to its growth.

　　Intern reporter Dai Xiaopei

　　After the game, it is probably unprecedented for fans to ask referees to wear hats or wigs.

　　At the end of October, Scottish fans experienced an "unforgettable" football match. In the Scottish Football Champions League match between Furness and Elven, the AI cameras on the sidelines turned a blind eye to whether the players passed the ball or attacked with the ball. Instead, they followed a linesman and took a close-up of "C position" from time to time. It turned out that the AI camera mistakenly identified the referee’s bald head as a football, so he chased the whole game crazily.

　　Fans who watched the 90-minute game at home spent most of their time not watching the ball, but watching the bald heads. Many netizens joked that this game really "saw a loneliness".

　　Why does the AI camera regard the bald head as a football? What do we need to do to prevent AI from making similar mistakes? Can you think that AI is "weak" when there is a "rollover" incident?

　　Unconscious "provocation" from bald referees

　　From direct participation in sports events to recording athletes’ performance, to live broadcast of competitions and analysis of athletes’ health status, AI is becoming the darling of the sports world. A few months ago, Barcelona Football Club (Barcelona) also joined hands with video technology company Pixellot to create an artificial intelligence coaching solution.

　　Unexpectedly, AI, which has made great strides in sports, unexpectedly encountered an unconscious "provocation" from a bald linesman. Because the linesman’s bald head is too bright and the sun shines, the AI camera can’t tell which is the ball and which is the head. Previously, because the Furness team said that the AI tracking technology they used could clearly transmit the live images to the homes of every season ticket buyer, so that fans who could not go to the home due to the COVID-19 epidemic would not miss any game.

　　It is reported that the camera used in the live broadcast of this competition is the multi-camera system provided by Pixellot, which cooperates with Barcelona. The system is powered by NVIDIA’s graphics processor (NVIDIA GPU), and the captured video resolution can reach 8K. These cameras can be installed in a fixed position without being manipulated by the camera operator. In order to capture the key moments, Pixellot collected hundreds of thousands of hours of sports videos to train its algorithm on the NVIDIA GPU of the local workstation.

　　With a huge amount of available data, using deep learning algorithms and high-performance GPU computing blessing, it has three major driving forces to push AI forward. Why did Pixellot’s AI camera "roll over"?

　　After the event, the relevant clubs and the technology companies that make cameras reflected. The problem seems very clear: the size and shape of football are similar to those of a human head, and the direct sunlight makes the AI camera fall into "confusion". I hope this will not happen again, because the Furness team responded that it knew the problem and will improve the next game to bring a better experience to the audience.

　　Pixellot also said that it is not difficult to solve this problem. The existing target detection and tracking technology is mature. Pixellot didn’t consider the influence of bald head in the design stage, so it needs to collect some data of football and bald head to fine-tune the algorithm to eliminate the interference from bald head.

　　Some technicians said that not only "this is a ball" data set, but also a "this is not a ball" data set is needed when training the AI camera of the live ball game. Bald head, bright white shoes, lighting, balls on the training ground next to the competition field and balls used by players to warm up are all interference factors that need to be considered when training AI.

　　AI "poor eyesight" is the norm.

　　Although the performance of AI cameras can be improved by increasing data "feeding", strengthening training and improving algorithms, some professionals believe that with the gradual expansion of AI application scenarios, such "rollover" incidents will exist for a long time.

　　“AI‘ Rollover ’ It’s normal, no ‘ Rollover ’ It’s strange. " Professor eecs and Huang Tiejun, president of Beijing Zhiyuan Artificial Intelligence Research Institute, spoke frankly when interviewed by Science and Technology Daily reporter.

　　Huang Tiejun believes that on the surface, the failure of the AI ? ? camera may be due to insufficient pre-training, but the main reason is that the current computer identification system is only trained with specific data. For example, in the above example, the neural network trained with a large number of football videos has surpassed humans in identifying football, but it ignores that this network is more sensitive to bald heads.

　　It is common to recognize or "turn a blind eye" unknown objects at random.

　　Machine vision is to endow the machine with visual perception, so that the machine has the scene perception ability similar to that of biological vision system, which involves optical imaging, image processing, analysis and recognition, execution and other components.

　　"Take the camera as AI ‘ Eyes ’ In real scenes, there is still a long way to go for AI to recognize football and baldness like human eyes. " Huang Tiejun said.

　　When can I finish this road and even realize that the eye of AI surpasses the human eye?

　　It depends on when machine vision will bridge the gap with biological vision. "The brain in the skull senses the outside world in real time through more than 3 million nerve fibers, of which there are more than 1 million behind each eye." Huang Tiejun said, "The machine vision developed to this day is still a drop in the bucket compared with the biological vision system that took hundreds of millions of years to evolve."

　　The human eye has strong adaptability, can identify targets in complex and changing environments, has advanced intelligence, and can use logical analysis and reasoning ability to identify changing targets and summarize laws. On the other hand, machine vision can use artificial intelligence neural network technology, but it can’t identify the changing target well. Due to the constraints of hardware conditions, the current general image acquisition system has poor color resolution.

　　"Compared with biological visual neural networks, the visual neural networks of artificial intelligence are far apart in structure and scale, so their functions are much worse." Huang Tiejun said, "In real applications, machine vision ‘ Rollover ’ It is not an accident. It is only a case to identify the bald head as a football. Similar problems actually exist in large numbers. "

　　Huang Tiejun said: "This time, the technology provider can make up for the loophole that the bald head mistakenly thinks of football, but there are still more loopholes. Deceiving the face recognition system with antagonistic picture training is only the tip of the iceberg."

　　Different technical routes are racing.

　　"Machine vision based on deep learning has made great progress in image recognition, but it has not really solved the perception problem." Huang Tiejun believes that deep learning is far from grasping the complexity of human visual system.

　　Deep learning is based on the training of image and video big data, which is far from the biological vision that actively perceives the dynamic world, and it is still not out of demand for computing power. For example, if the video frame rate is increased from 30 to 30,000, the computing power of deep learning needs to be increased by 1,000 times.

　　Biological neural network is a pulse neural network, which is more suitable for completing visual information processing. Huang Tiejun believes that learning from the neural network structure and information processing mechanism of biological vision system and establishing a new set of brain-like vision information processing theory and technology is the hope of restarting machine vision.

　　Experts said that there are two main technical routes to develop artificial machine vision. One is to build a powerful intelligent system by collecting more data, increasing the amount of data and strengthening training; The second is to imitate the biological nervous system, follow the gourd painting gourd ladle, clarify the structure and even mechanism of the biological nervous system, and develop future intelligence on this basis.

　　Huang Tiejun believes that the second path is more effective than the first one. "In a short time, the first one is easier to achieve results. But in the long run, it is more direct to start with biological neural networks and more confident to achieve the goal. "

　　At present, most AI scholars support the first path, that is, to develop artificial intelligence including machine vision through "big data+big computing power". Huang Tiejun set foot on the road taken by a few people because he firmly believed that the biological visual neural network had great potential to be tapped. "Biological brain is the product of hundreds of millions of years of evolution, and it is the best transcendental structure. Powerful intelligence must rely on complex structures and stand on the shoulders of evolution. It seems difficult, but it is the fastest. "

　　Turing, the "father of computer science", has long expressed his admiration for the biological brain. At the beginning of 1943, Shannon suggested that "cultural things" could be instilled in the electronic brain. Turing once retorted in public: "No, I’m not interested in building a powerful brain. What I want is just an ordinary brain, just like the head of the chairman of AT&T."

　　Is developing machine vision, or artificial intelligence, starting from scratch, imitating biological neural networks, or is there another way? There is no conclusion yet. On different tracks, artificial intelligence is accelerating.

　　Although there are many cases of AI "rollover", such as the practicability of Google AI eye disease diagnosis system is greatly reduced in Thailand, Tencent AI translation made a joke at the Boao Forum in 2018. But the AI era is accelerating and unstoppable.

　　"It must be admitted that AI has indeed solved many practical problems, and it will gradually replace some functions of people. But we can’t exaggerate it too much. It is still far from our imaginary intelligence and needs more breakthroughs. " Huang Tiejun said that to keep an open mind and bridge the gap between "experimental simulation" and "real world", the development of AI technology has a long way to go.