Will the self-driving cars come to us in 2020?

city-1284400_640Since last year, the progress of development of self-driving cars are accelerated rapidly.  When I wrote about it last year, someone may not be convinced that the self-driving cars come true. But now no one can doubt about self-driving cars anymore. The problem is when it comes in front of us.  I would like to consider several key points to develop the technology of self-driving cars.

 

1.Data from experiments

It is key to develop self-driving car effectively. Because self-driving cars need artificial intelligence in it to drive cars by themselves without human interventions. As you know, artificial intelligence looks like our brains.  When we are born, our brain is almost empty. But as we grow, we can learn many things through our experiences.  This is the same for artificial intelligence. It needs massive amounts of data to learn. Recently, Google and  Fiat Chrysler Automobiles NV announced that they cooperate to enhance development of self-driving cars. According to the article on Bloomberg, “The carmaker plans to develop about 100 self-driving prototypes based on the Chrysler Pacifica hybrid-powered minivan that will be used by Google to test its self-driving technology.”(1)  The more cars are used in the experiments, the more data they can obtain. Therefore, it enables Google to accelerate to develop self-driving cars more rapidly.

 

2. Algorithm of artificial intelligence

With data from experiments, artificial intelligence will be more sophisticated.  The algorithms of artificial intelligence, which are called “Deep Learning” should be more effective from now.  Because driving cars generates sequences of data and need sequential decision making processes, such as stop, go, turn right, accelerate, and so on,  we need algorithms which can handle these situations. In my view, the combination of deep learning and reinforcement learning can be useful to do that.  This kind of technologies is developed in research centers, such as Google DeepMind which is famous for the artificial intelligence Go player. It says this technology can be used for robotics, medical research and economics.  So why not for self-driving cars?

 

3. Interactions with human drivers

It seems to be very difficult to decide who is responsible for driving cars.  Initially, self-driving cars might appear with the handle and brakes. It means that human can intervene the operations of self-driving cars. When accidents happen,  who is responsible?  Human or machines?  When self-driving cars without handle and brakes are available,  machines are responsible as human can not control cars anymore. So the machines are 100% responsible for accidents. It is very difficult to decide which is better, self-driving cars with and without handle and breaks. It depends on the development of technologies and regulations.

 

Impact on society is huge when self-driving cars are introduced to us.  Bus, Taxi, Track could be replaced with self-driving cars.  Not only drivers but also road maintenance  companies, car insurance companies, roadside shops, traffic light makers, railway companies, highway running companies,  car maintenance companies and car parking providers are also heavily impacted. Government should consider how we can implement self-driving cars to our societies effectively. I do not think we have spare time to consider it. Let us start it today!

 

(1) http://www.bloomberg.com/news/articles/2016-05-03/fiat-google-said-to-plan-partnership-on-self-driving-minivans

 

Note: Toshifumi Kuga’s opinions and analyses are personal views and are intended to be for informational purposes and general interest only and should not be construed as individual investment advice or solicitation to buy, sell or hold any security or to adopt any investment strategy.  The information in this article is rendered as at publication date and may change without notice and it is not intended as a complete analysis of every material fact regarding any country, region market or investment.

Data from third-party sources may have been used in the preparation of this material and I, Author of the article has not independently verified, validated such data. I accept no liability whatsoever for any loss arising from the use of this information and relies upon the comments, opinions and analyses in the material is at the sole discretion of the user. 

Will the age of “Brain as a Service” come to us in near future?

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15 March 2016,  I found two things which may change the world in the future,  The former, artificial intelligence Go player “AlphaGo” and the latter is an automated marketing system “Google Analytics 360 Suite“. Both of them came from Google. Let me explain why I think the age of “Brain as a service” is coming  based on these two innovations.

1. AlphaGo

You may know what AlphaGo achieved on 15 March 2016.  At  Google DeepMind Challenge, where artificial intelligence Go player had five games against a top professional Go player. It beats Lee sedol, who is one of the strongest Go player in the world, 4 to 1.  Go is one of the oldest games, which are mainly played in China, Korea, Japan and Taiwan. At the beginning of the challenge, few people thought AlphaGo could win the games as it is always said that  Go is so complex that computers can not win professional Go players at least in 10 years. The result was, however, completely opposite. Therefore,  other professional Go players, artificial intelligence researchers and even people who do not play Go must be upset to hear the news. AlfaGo is strengthened by algorithms, which are called “deep learning” and “reinforcement learning“. It can learn the massive amount of Go patterns created by human being for a long time.  Therefore, we need not to program specifically, one by one as computers can learn by themselves. It looks like our brains. We are born without any knowledge and start learning many things as we grow.  Finally, we can be sophisticated enough to be “adult”. Yes, we can see “AlphaGo” as a brain.  It can learn by itself at an astonishing speed as it does not need to rest.  It is highly likely that Google will use this brain to improve many products in it in the future.

 

2. Google Analytics 360 Suite

Data is a king.  But it is very difficult to feed them into computers effectively.  Some data are stored in servers. Others are stored in local PCs. No one knows how we can well-organize data effectively to obtain the insights from data.  Google is strong for consumer use.  G-mails, Android and google search are initially very popular among consumers. But the situations are gradually changing.  Data and algorithms have no-boarders between consumers and enterprises. So it is natural for Google to try to obtain enterprise market more and more. One of the examples is  “Google analytics 360 Suites”. Although I never tried it yet, this is very interesting for me because it can work as a perfect interface to customers. Customers may request many things, ask questions and make complains to your services. It is very difficult to gather these data effectively when systems are not united seamlessly. But with “Google analytics 360 Suites”,  data of customers could be tracked in a timely manner effectively.  For example, the data from Google analytics 360 may be going to Google Audience Center 360,  which is a data management platform (DMP).  It means that the data is available to any analyses that marketers want.  “Google Audience Center 360” can collect data from other sources or third party data providers. It means that many kind of data could be ready to be fed into computers effectively.

 

3. Data is gasoline for “Artificial intelligence”

AlfaGo can be considered as “Artificial intelligence”. “Artificial intelligence” is like our brain.  There is no knowledge in it initially.  It has only structures to learn.  In order to be “intelligent”, it should learn a lot from data. It means that massive amount data should be fed into computers. Without data, “artificial intelligence” can do nothing. Now data management like “Google Audience Center 360” is in progress. It seems that data are getting well organized to be fed into computers.  The centralized data management system can collect data automatically from many systems. It becomes easier to feed massive amounts of data into computers. It enables to computers learn the massive amount of data. These things must be a trigger to change the landscape of our business, societies and lives. Because suddenly computers can be sophisticated enough to work just like our brain.  AlphaGo teaches us that it may happen when a few people think so. Yes, this is why I think that the age of “Brain as a Service” will come in near future.  How do you think of that?

 

 

Note: Toshifumi Kuga’s opinions and analyses are personal views and are intended to be for informational purposes and general interest only and should not be construed as individual investment advice or solicitation to buy, sell or hold any security or to adopt any investment strategy.  The information in this article is rendered as at publication date and may change without notice and it is not intended as a complete analysis of every material fact regarding any country, region market or investment.

Data from third-party sources may have been used in the preparation of this material and I, Author of the article has not independently verified, validated such data. I and TOSHI STATS.SDN.BHD. accept no liability whatsoever for any loss arising from the use of this information and relies upon the comments, opinions and analyses in the material is at the sole discretion of the user.