In the field of self-driving cars, there is IBM's black hand behind it!

A few days ago, IBM announced its first quarter 2017 results, and then the stock was sold short. According to Bernstein's Toni Sacconaghi, "IBM's revenue is not good." IBM delivered $18 billion in results, with a net income per share of $2.38, up year-on-year. I don't believe the result is very bad. Annual revenues have declined for 20 consecutive quarters, but long-term investors and analysts should understand that IBM's business model is future, in fact he is an artificial intelligence company.

The author firmly believes that selling is a wrong choice, of course, low-priced buying is also an opportunity. Post Watson believes that IBM's next growth driver will be autopilot. Compared to today's industry leaders such as Intel and NVIDIA, Big Blue is different in the autopilot world. Its recently announced patent for artificial intelligence related to autonomous driving has great potential. Despite this, investors and analysts do not believe that IBM is an important player in the field of autonomous driving. The author will analyze how IBM's patents change autonomous driving.

From an observer's point of view, patenting is an encouraging news as it will help IBM profit sooner or later. Auto-driving cars will not be on the road within ten years, and semi-automatic and timely cars will be completed by 2020.

When Google’s Waymo and Uber are trying to enter this complex market, a Chinese-era car company has revealed that its electric car has an L4 autopilot rating called NIO EVE, which is expected to be in the US by 2020. The market has landed.

So, what is a 4th-level self-driving car? According to the National Highway Traffic Safety Administration, 4

The self-driving car is capable of autonomously performing almost all driving functions as well as road monitoring. However, such a vehicle cannot completely replace the driver, which means that the driver is still in need of driving.

Here IBM's patent will play a role, it will introduce AI driving technology. This technology will monitor when human control is required and when it is semi-automatic, like the upcoming NIO EVE.

This technology will continuously monitor the driver's physiological condition and the automatic technical system of the semi-automatic car. A large number of online sensors will be fed back with compatible software, making the technology work, which will boost IBM's revenue from autonomous driving, with the ultimate goal of preventing accidents.

Although Intel, NVIDIA and Waymo are working together to develop technologies for autonomous driving, their technology does not focus on the interaction between people and machines. Instead, they are interested in developing fully automated vehicles, such as the gradual realization of Level 5 safety.

Investors should note that in this gradual development process, IBM's top priority and ultimate goal mentioned above is to make the vehicle reach level 5 autopilot. Intermediate goals, such as the upcoming level 4, are only part of the final goal being studied. However, in fact, the five-level goal is still far from being realized, even after ten years.

Although the current speculation is that vehicle automation can radically reduce traffic accidents, in fact, compared to the total number of car accidents on the global road, the proportion of traffic accidents caused by human error is negligible. In this context, if we look at the semi-automatic Tesla Model S accident, we will come to the conclusion that semi-automatic vehicles will cause more accidents on the road than full-drive vehicles.

In fact, the investigators of the US Safe Transportation Bureau did not find any errors in Tesla's semi-automatic technology. This does not mean that in the upcoming level 4 autonomous vehicles, accidents will not be taken seriously. This traffic accident was actually caused by the driver's excessive dependence on the auto-driving technology of the car. It seems that when driving a semi-autonomous car, the driver first needs to learn how to interact with a particular technology. I believe this is more difficult than driving a manual car. Standardization is the big question to be solved in the next step. With a variety of technologies used by a variety of car and chip manufacturers, adapting to the new driving environment will not be a child's gameplay for manual driving.

Alphabet commissioned a study by the Virginia Institute of Transportation and Technology to show that compared to manually driven cars, autonomous vehicles cause fewer car accidents. At the same time, the researchers also acknowledged the lack of data on accidents caused by manual driving. As an investor, I doubt the credibility of the research. Instead, the 2015 study looks more convincing, as stated below:

Most car accidents are caused by human error. If better autopilot operations reduce or eliminate these mistakes, the benefits to road safety can be enormous. However, most driving will not cause an accident. The real safety test of self-driving cars will be how they replicate the human driver’s accident-free

Now.

IBM's patents will solve this problem, such as replicating the performance of manual driving without collision (with the help of a manual driver). AI Corporation has obtained US Patent #9,566,986, which is intended to control the controlled driving mode between the automatic driving system of the semi-autonomous vehicle and the driver. IBM's patent co-inventor James Kozloski explains:

Autonomous vehicles have great development prospects and potential, but the safety of passengers and drivers is the first consideration for vehicle manufacturers and manufacturers. We focus on finding new ways and using our understanding of the human brain and inventing systems to help these companies improve the safety of self-driving vehicles.

Other patents IBM obtained earlier, US Patent #9,361,409, to help semi-automatic vehicles to better interact with the driver. Clearly, IBM's goal is to generate revenue from semi-autonomous vehicles, while the automotive and related industries are busy making fully automated vehicles.

Automated driving cannot quickly become a reality, and IBM's technology will have reasonable demand in the semi-automatic vehicle market for the foreseeable future. In addition, since the successful cooperation between IBM and Watson, the company has become a leader in the AI ​​field, and its AI technology in the automotive industry will also pass.

The popularity of L4 semi-automobiles on American roads is only a matter of time. It takes at least a decade for such vehicles to dominate the automotive sector. The ADAS platform for such vehicles requires the help of AI. IBM's leadership in the AI ​​field has allowed it to take the lead in autonomous vehicles. The current problem is that NVIDIA's GPU-driven ADAS technology and Intel's acquisition of Israeli automatic chip maker Mobileye to catch up, will enable them to integrate AI into the ADAS platform? The answer is that IBM's approach is different.

NVIDIA and Intel's approach to autonomous driving involves the use of devices to expand a variety of sensors on the ADAS platform, including 3D-mapped radars, motion-measuring radars, and object-recognition cameras. IBM's approach is to extend cognitive capabilities to the vehicle's ADAS platform. IBM's original goal was to make the vehicle's autonomous driving system look like a human, so the driver and the vehicle's automatic driving system could interact like two people. As the saying goes, "The three stinkers have won a Zhuge Liang", so the car accident on the road will be greatly reduced.

To develop such a system, I believe that IBM will not spend much time converting patents into actual devices, because the company has already made significant contributions to the IoT field through Watson's cognitive platform. How will IBM profit from its autonomous vehicle technology through AI technology? The answer is simple. Selling sensors developed with partners, such as Texas Instruments, will also benefit from the development of the Bluemix platform. The software is part of the IBM Automated Vehicle Platform, which is powered by AI.

In short, IBM has a lot of room to rise in the future, and its potential lies in its patents and artificial intelligence in the field of automatic driving.