Making AI Work Better by Bridging the Gap Between Data, AI and the Issue at Hand

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[Publisher] ORIX Group

It is not only large corporations that create world-changing innovative technologies. Around Japan there are many SMEs and start-ups that are pushing the boundaries of innovation, and which ORIX supports through its corporate financial services business. Ridge-i Inc. (“Ridge-i”), is one such company. It is an AI solutions provider that tackles issues ranging from business to the environment and even in space. The company was founded in 2016 and focuses on providing AI solutions such as image recognition based on deep learning*1, while also providing consulting to help resolve issues in a corporate context.

Ridge-i's President and CEO Takashi Yanagihara, and Takumi Takayama, from ORIX’s Corporate Business Headquarters sat down to talk about Ridge-i's vision and how to approach corporate digital transformation (DX).

*1 Deep learning: A method of machine learning in which a computer learns the work and tasks naturally done by humans. By inputting enough reference data, it is possible for the AI to automatically extract trends and features.

Three Key Points Necessary for the Success of AI Projects

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Ridge-i President and CEO Takashi Yanagihara

—First of all, what kind of company is Ridge-i?

Yanagihara: We are a start-up founded in 2016. Our primary business is identifying issues that corporations and public organizations are facing, and then resolving them through the development of AI solutions and supporting their practical implementation.

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Examples of projects that Ridge-i has tackled. Familiarization with issues and data utilization know-how are key (image courtesy of Ridge-i)

Around 70% of the solutions we provide are based on image recognition deep learning. We have developed and provided solutions ranging from black and white video colorization and landslide analysis systems using satellite data to, in recent societal situations, crowd analysis where captured video is analyzed in real time to measure the density and flow of people. The other 30% of our solutions are non-image based AI. For example, we recently developed a system to automatically design the construction of logistics warehouses.

—Many corporations are currently focusing on AI and promoting DX to increase efficiencies, but there are many instances where projects haven’t live up to expectations. What are the key areas for success in DX using AI?

Yanagihara: As you said, right now there is a lot of attention surrounding AI and DX, and there are high expectations for such solutions.

However, on the other hand, it is said that in Japan, the success rate for AI projects that reach implementation is only 3%*2. It seems that this is due to scope and definition-related problems such as vague goals to be achieved and lack of cost benefits, as well as technology and resource-related problems such as a lack of personnel with skills in data acquisition and the introduction/operation of technology. The personnel problem is particularly significant, and there is a growing demand for not only development personnel who can handle the AI technology, but also those who can design optimal solutions while mastering AI as one of their suite of tools.

In these situations, I believe it is the role of Ridge-i to provide true AI solutions which leverage data conversion know-how, AI technology and properly clarify the problem and expected outcome. We are an AI technology company but in order to fit these three pieces together properly, we need to have not only technology but also a high level of business sense. Without an accurate understanding of a client’s issues in all fields, we can’t introduce a technology that will yield results.

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The three pieces that Ridge-i considers to be essential factors for the success of AI projects. If any of these pieces are missing you cannot garner effective results (image courtesy of Ridge-i)

 

The “Ridge” of our company name “Ridge-i" represents the ridge of a mountain and expresses the concept of “providing peak solutions that pursue the highest peaks of both technology and business”.

Our company has supported DX and the introduction of AI for more than 30 companies since our founding five years ago. About 30% of the success of a project is related to technology such as AI. The remaining 70% is in properly defining the requirements. Based on the three points mentioned above, as long as we can clarify issues and properly define the requirements, I believe the success rates of many projects will greatly increase.

*2 Ministry of Economy, Trade and Industry “Projects to Support the Advancement and Collaboration of Strategic Core Technologies (Research Project on Promoting the Use of AI by Small and Medium Enterprises)”

The Key to Success in AI Projects is On-Site Dialogue

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—What are some examples of projects that have succeeded due to defining the requirements properly?

Yanagihara: For example, we received a consultation request from a customer who operates a waste processing facility and wanted to save manpower and automate, and we spent four months defining requirements.

We started by carefully identifying the areas where the manpower savings from automation would have the biggest impact on all work processes, such as waste collection, dumping into waste pits, transportation via crane, and incinerator management. We ultimately discovered that the key process was using cranes to throw waste into the incinerator.

We then had to identify the tasks which could not be automated. For this kind of work, it’s common that 80% can be automated but the last 20% of the work requires manpower. However, if that 20% can be done by someone who also looks after other processes, you can still save on manpower. We made proposals from the perspective of operations and flow improvements so that tasks that required manpower could be done with the bare minimum number of people.

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The project was jointly developed and focused on the flow of automatic operation of a crane by using AI to identify the situation of a garbage pit captured on camera, such as the state of agitation of the garbage, then using an advanced controller to make decisions on crane operation in the pit (image courtesy of Ridge-i)

—You must have faced some resistance on-site when it came to saving on manpower?

Yanagihara: Obviously there were people on-site who were worried that they might lose their jobs. However, AI is a replacement for tasks that people considered to be troublesome or risky. It provides support so people can focus on tasks that only people can perform. When we explained this, everyone was convinced.

I talked earlier about the importance of defining requirements based on a combination of these three pieces. That is the common foundation for all of our initiatives. Additionally, the most important thing in implementing the ideal form of technology for each individual case is to respect and properly understand the customer’s business. Communication with people on-site is critical. Within the company, it is essential to not only discuss profits and efficiency from the perspective of the corporation, but also the merits from the perspective of the people on-site.

  • Click here for more information about the project.

Collaboration with ORIX to Bridge the Gap Between Data, AI and Issues

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Manager of Equity Solutions Team 2, Domestic Business Promotion Department at ORIX’s Corporate Business Headquarters, Takumi Takayama

—The capital and business partnership with ORIX was announced in February 2021. When did the relationship between ORIX and Ridge-i first start?

Takayama: We first met at an event organized by a venture capitalist in 2019. Mr. Yanagihara’s easy-to-understand explanations of the cutting-edge technologies were very impressive. At the time, as AI and other advanced technologies were becoming increasingly important in society, I was trying to think about how ORIX could play a role in that area as well.

—What will the structure of the partnership look like?

Takayama: We’re hoping that ORIX will become a platform for resolving issues for a variety of industries and corporations, and that we can provide solutions using AI along with Ridge-i.

ORIX has functions that allow us to listen to issues faced by our customers in a variety of industries and departments across Japan. By analyzing the common elements of these issues, we can develop AI/DX solutions that further contribute to resolving them.

Yanagihara: There is a strong need for the introduction of AI, not only at large companies but also at SMEs – but cost is still a bottleneck. However, for example, even if a single company isn’t able to cover the cost of the development of a system for 30 million yen, if 30 corporations with similar issues gather together, they may be able to develop it by pooling 1 million yen each.

It is inevitably difficult for a company of our size to hold interviews about issues with a wide range of small and medium corporations and recognize their common challenges. However, having ORIX, who has been developing businesses in a variety of fields for many years and has a deep understanding of the businesses of many different companies, act as a bridge will allow us to proceed more smoothly.

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“Identical Person Tracking,” one of the services developed by Ridge-i. Enables identification of people without prior registration. Individual IDs are assigned to each person on camera, and even if the person’s appearance changes such as by taking off a jacket or mask, the person can still be tracked as the same person. (From the official Ridge-i YouTube channel)

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“GRASP EARTH,” a global change detection service also developed by Ridge-i., is a service that allows users to obtain once-expensive satellite images at an affordable price, enabling fixed-point observation of any place on earth. Its use in disaster detection is currently under consideration.
(From the official Ridge-i YouTube channel)

Takayama: Of course, it’s not actually that easy in reality (laughs). However, if we can realize this kind of sharing system, it will greatly lower the hurdles for introduction of AI at SMEs.

To achieve this, the ORIX Group needs to absorb more knowledge about cutting-edge technologies, so we want to actively promote the exchange of personnel with Ridge-i. The infusion of AI and DX knowledge within the Group will make it possible for us to make proposals to a wider range of customers.

Yanagihara: Companies like ORIX who can gather a lot of needs-related information from SMEs are invaluable, so we want to use their strength to promote the spread of technology in these smaller businesses.

Takayama: I think that Ridge-i, which works one-on-one with companies to resolve issues, is a great fit with ORIX’s corporate culture. There are a lot of SMEs in the world who want to use technology to make reforms and realize DX could be an answer, but haven’t clearly identified their issues. To help these corporations, we will continue to partner with Ridge-i to bridge the gap between data, AI and issues.


To learn more about Ridge-i's solutions, click the following links for more information.

GraspEarth


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