[PYTHON] Is it a problem to eliminate the need for analog human resources in the AI era?

Introduction: The future of AI and analog human resources

It's not about the code, but this time I'm trying to do what I'm thinking while programming.

I usually use R on weekdays for work. I've recently started studying Python as well.

[Practice content page](https://weblab.tu-tokyo.ac.jp/%E6%BC%94%E7%BF%92%E3%82%B3] published in Professor Matsuo's laboratory at the University of Tokyo % E3% 83% B3% E3% 83% 86% E3% 83% B3% E3% 83% 84% E5% 85% AC% E9% 96% 8B% E3% 83% 9A% E3% 83% BC% E3 When I look at% 82% B8 /), I'm grateful ... It is around this time that I think the University of Tokyo students who can pull this off in their teens and early twenties are amazing. DL4US, which even working adults can apply for, is also attractive. ** The selection test for the GCI online course was also Python **, though it was almost a line. I am looking forward to the start of the course from now on.

By the way, I'm currently working in programming, but for some reason when I was a student, I was in a liberal arts laboratory and devoted myself to organizational theory research, so while making data analysis my business, ** "AI is a person. When I hear "take away my job" ** or ** "human resources education in the age of AI" **, I think about it in various ways.

Speaking of Japan from an overseas perspective, it seems that ** there are many latecomers in the technology field and the soil for creating attractive innovation is weak **.

No matter how much programming you can do, it is just a tool, and I think that in order for Japan to regain its international competitiveness in the world of AI and innovation, more fundamental learning and the way of thinking of human resources will be necessary.

Was it until the 1980s that Japan was at the top of manufacturing manufacturing in the past?

Where is the ** domestic human resources spirit ** that was shining brightly in analog manufacturing? It's been a long time since I've been called digital, but after all, do you need analog human resources?

While thinking that this is not the case, I would like to leave a memorandum about the theory of human resources utilization in the AI era.

(Quote: Deep learning free course supervised by Matsuo Lab (figure below))

Practical use of AI in Japan: What is your position in the world?

Professor Yutaka Matsuo, a professor at the University of Tokyo and chairman of the Japan Deep Learning Association, is now a director of the SoftBank Group, which plans Ai investment and business in Japan.

In recent years, I haven't heard about the business utilization of artificial intelligence (AI) and deep learning, but in terms of practical utilization in companies ** Japan is far behind the United States and China. **.

Under such circumstances, the news that academic authority Mr. Matsuo will join the SoftBank Group, which promotes active deep learning business utilization, does not feel the hope that deep learning utilization in Japan has finally become serious. I can't enter.

A little while ago, Mr. Matsuo's keynote speech at the ** Deep Learning Community Event "DEEP LEARNING LAB (DLLAB)" ** jointly operated by Microsoft and Preferred Networks held on June 8, 2019 was also in Japan. It was emphasized that the introduction of AI in Japan / utilization of deep learning is lagging behind even in the world.

The background and the five viewpoints that were mentioned as future improvements are

-** Having a small success experience ** -** Importance of AI team formation ** -** Need for AI training ** -** Clear AI strategy ** -** Importance of internal / external communication (IR / GR [Government Relations] / customer development / human resources acquisition / internal communication) **

It was clearly stated, and it was just a point of view that I felt exactly.

It's not about programming skills, but about how to create an organization that operates, develops, and plans.

Utilization of deep learning by Japanese companies The background of the struggle

In addition to the above five issues, I think that the actual situation of Japanese companies is as follows when summing up the real voices I heard from my time working in foreign-affiliated IT.

** Unable to prove the effect of introducing AI (lack of small successful experience) → Cannot withdraw investment / lack of internal understanding (lack of internal communication) → AI team formation / training is secondary → From “something” without setting purpose Trying to get started (AI strategy / lack of external communication) → Start with an inexpensive trial → Failure at the verification stage → Unable to prove the effect of introducing AI… **

I think that the business will succeed by winning the one that breaks out of this infinite loop. Looking at this, the first step to take for strategic AI / deep learning utilization is • Securing investment and investing appropriately • Acquisition of AI human resources with abundant practical experience

Is likely to be the key.

The first point is that the skill of the management of each company and the efforts of fund operating companies such as SoftBank's "SoftBank Vision Fund" are questioned.

The second point is ** acquisition of AI human resources **, but this seems to be the number one issue for domestic companies. This is because, in order to acquire excellent human resources, ** it is necessary to strategically and systematically review the environment for demonstrating performance, the system of cooperation with internal business, and branding for customer development **.

Many issues remain in order for AI human resources, which have been increasing in recent years, to select “Japanese companies”. This is because the fields of activity are expanding to technologically advanced countries such as the United States, China, and Europe from the perspective of excellent domestic human resources. Overseas, the strategies of each company are already shining from the perspective of ** "cultivation" ** before acquiring AI human resources.

These days, especially overseas, ** iSchool ** is gaining popularity, and the word ** "STEM education" ** is attracting attention, so in many disciplines the logic of technology thinking and data utilization The approach is emphasized, and there is a tendency to develop useful human resources in the AI era.

On the other hand, ** Japan where programming education will finally start in elementary school from 2020 **.

** In addition to the short circuit of "AI = programming" **, I even feel the need to relearn from the fundamentals of human resource development in the AI era from Western and Asian countries that are a few steps ahead.

Analog human resources that shine in the era of IoT / modularization

With STEM education drawing attention, I think that ** "analog human resources" ** should also come here and be spotlighted.

The analog human resources here are specialties that enable manufacturing in terms of hardware.

Even if the market seems to be overwhelmingly software-oriented due to the progress of cloud computing, ** IoT and data acquisition by wearable terminals will increase, and how small hardware can be made in the future is a showcase of skill * *is.

However, due to the recent increase in demand for digital (software) human resources, there is an overwhelming shortage of analog human resources in the market.

As a result, the trend of hardware development of electronic components is also popular as ** "modularization" ** that combines multiple functions into one.

As an example, a processor that plays the role of a "brain miso" as the core of data, communication equipment, industrial equipment, medical equipment, etc. Taking the example of a step-down converter that supplies power to this, analog human resources Against the background of the lack of power, it is said that it is popular that the resistors and capacitors that make up the DCDC converter circuit can be mounted in a single unit in a short time.

Due to the shortage of human resources, it seems that the manufacturing method itself is becoming more efficient **.

It makes me wonder if the craftsmen who once supported the Japanese manufacturing industry and manufacturing might have shown a stronger commitment.

** What you want to make is first, and the organization and strategy to make it come along. ** **

The return of Japan in the coming AI era is before saying "programming is awesome, this is awesome" It may be necessary to review this kind of commitment. (Of course, I will continue to learn programming hard!)

The future is the crucial moment for AI / deep learning business in Japan. We would like to continue to pay attention to each company's investment and human resource education efforts.

Reference: Searching for "practice" for successful AI utilization