These days, if you start a business without talking about artificial intelligence, you can't get money at all.

 

Large companies engage in artificial intelligence, large company executives jump to start businesses to engage in artificial intelligence, investors invest in artificial intelligence, so that artificial intelligence companies have undoubtedly become the current Internet companies in the gold pool, not to mention reliable companies, as long as they are reliable employees, can get a large amount of venture capital, enough to flutter in the tide of artificial intelligence for a period of time.

 

But to be practical, the current artificial intelligence research directions of these technology companies are actually mainly three: deep learning, natural speech processing, and machine vision. Deep learning is a compulsory course in artificial intelligence. Natural language processing can directly apply technology to virtual intelligent assistants, while machine vision can be directly transferred to autonomous driving technology.

 

Smart speakers equipped with virtual voice assistants have been around for a long time, but from the feedback of consumers, they do not think that intelligent voice assistants are smart things, and even smart speakers look a little tasteless at present. Unlike smart speakers, which are hot in the market but cold in the consumer circle, autonomous driving seems to be a project that both investors and ordinary consumers are optimistic about. Many people expect autonomous driving to improve future traffic conditions and solve the current congestion and inefficient traffic problems, and capital markets are also particularly favored by autonomous driving companies and autonomous driving talents.

 

This morning, autonomous driving startup Momenta announced a $46 million Series B investment. The round was led by NIO Capital, along with Daimler Group (parent company of Mercedes-Benz), Shunwei Capital, Innovation Works and Jiuhe Ventures. In 2016, Momenta received Series A financing led by Blue Lake Capital, Innovation Works and Zhen Fund. In early 2017, it received Series A1 financing led by Shunwei Capital.

 

The company was established less than a year to raise multiple rounds of funds, B round 46 million is indeed a small investment, especially at present the company has no external output.

 

Let's dig deeper into this company.

 

Momenta is a Beijing-based autonomous driving company founded in September 2016. Founder Cao Xudong previously worked at Microsoft Research Asia and SenseTime Technology. The company's goal is to get the brain of Daao autonomous driving, and the core technology is deep learning-based environmental perception, high-precision mapping, and driving decision-making algorithms. Products include different levels of autonomous driving solutions, as well as derived big data services.

 

In other words, Momenta is an autonomous driving solutions company.

 

Compared with other companies, Momenta's technical advantage lies in visual recognition. According to Cao Xudong, Momenta has the world's top deep learning experts, the author of Faster R-CNN and ResNet, the most advanced frameworks in the field of image recognition, and the champion of ImageNet 2015 and MS COCO Challenge 2015. The team comes from Tsinghua University, MIT, Microsoft Research Asia, etc., and has deep technical accumulation and strong technical originality. Ren Shaoqing, the company's R & D director, is the inventor of Faster RCNN, the world's most widely used object detection framework.

 

This visual recognition technology advantage has given the company a significant advantage in the most basic perception part of the autonomous driving solution. Because from the current point of view, visual recognition will become the main solution in the perception part of autonomous driving. Compared with the lidar that was widely used in the early days of autonomous vehicles, the cost of camera sensors is lower, and the data generated by the lidar is also smaller than the generated data of the surrounding environment.

 

However, the difficulty of visual recognition lies in the high-precision visual recognition algorithm. Only when the algorithm is well optimized can the on-board computer recognize and process the images collected by the camera, and divide the drivable area, pedestrians, street lights and other road traffic elements.

 

And algorithms are precisely what Momenta is good at.

 

But to achieve autonomous driving, it is not enough to have good perception alone. Decision-making and control are the most critical technical modules of autonomous driving. To adjust the decision-making algorithm of autonomous driving, a large amount of actual road test data is required to optimize the algorithm, so as to achieve the final intelligent and safe autonomous driving control.

 

But accumulating autonomous driving data is a costly task that is difficult for small companies to achieve, so it requires tremendous financial and human support.

So it is possible to look back at where the $46 million financing will be used. "The financing will be used for three aspects: 1. Strengthening the core capabilities of artificial intelligence, including big data, big computing and excellent AI talents; 2. Productization of vision-based environmental perception and high-precision mapping technology; 3. Development of L4 unmanned driving technology for high-frequency rigid demand scenarios," Cao Xudong said.

 

In the current stage where companies are accumulating autonomous driving technology, talent is the most expensive investment, because companies are attracting autonomous driving technology talents, resulting in a rise in the income of these talents. Many large companies are even willing to invest hundreds of millions of dollars in order to acquire a small autonomous driving team established by several technicians.

 

On the other hand, for autonomous driving start-up companies, capital will not allow long-term investment in non-productive consumption. Everyone thinks that autonomous driving can make money in the future, but how much money can autonomous driving make? How to earn this money when autonomous driving has not yet become popular is still a problem. Therefore, start-up companies still need to gradually productize their technology to give investors enough confidence and company prospects to continue to invest in the development of their own technology. For autonomous driving companies like Momenta that are good at machine vision, the initial productization plan is likely to provide driving assistance technical support for automakers to make profits (as can be seen from investors, Mercedes also participated in the investment, but also to make up for its own technical weakness in the visual recognition of driving assistance. It is important to know that Mercedes-Benz's research and development of driving assistance is not later than Tesla's, but it is the visual recognition that lags behind Tesla so much that Mercedes-Benz's high-level driving assistance seems to have been tepid in the consumer market).

 

Of course, the ultimate goal of each company is to achieve L4-level fully autonomous driving. Momenta's goal is to limit L4 autonomous driving technology in high-frequency rigid demand scenarios to deal with traffic conditions in our country, and it is likely to be low-speed autonomous driving in traffic jams.

 

Now most start-up companies are targeting L4-level fully autonomous driving, and such ambitious goals are particularly attractive to investors. However, autonomous driving is not something that can be achieved in a short time. The previous predictions of major automakers in 2020 or 2021 are definitely not a year when autonomous driving can be fully profitable. Investors love to play with trends. How long will the wind energy of artificial intelligence and autonomous driving continue to blow? It depends on how much patience the investment circle has.