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Introduction to our Generative AI Development Project

somawada
somawada
Cover Image for Introduction to our Generative AI Development Project

Introduction

Hello! This is Wada (@cognac_n), a data scientist at KINTO Technologies.
In January 2024, KINTO Technologies launched the "Generative AI Development Project team" and I was assigned to be a team member. This article serves as an introduction to our project.

What is Generative AI?

Literally, it refers to an artificial intelligence that produces new data. The release of ChatGPT by OpenAI in November 2023 thrust it into the spotlight.
AI has experienced a number of temporary booms(*1), the emergence of the fourth AI boom(*2), driven by the development of generative AI, has gone beyond a mere boom and is beginning to take root in our daily lives and work. I believe that the use of generative AI, which will become increasingly popular in the future, will have such a significant impact that it will overturn many of the conventional norms in our daily lives and work.

Past Initiatives

The project was launched in January 2024, but we have been working on the use of generative AI for a long time. Here are just a few of our efforts:

And so on.
However, there were many initiatives that unfortunately could not be undertaken due to our lack of resources... But now that the project has officially been established as a team in the organization, I believe we will be able to promote the use of generative AI even more broadly. I am very excited for what’s to come!

What Our Project Aims For

Our Mindset

What we value is “contributing to the company's business activities” through technology.
Our goal is to solve internal issues with overwhelming “speed, quality, and quantity” as a “problem-solving organization”. Instead of merely trying things out and critiquing, we will continue to work as an organization that focuses on value!

The Impact We Want To Have On Our Company

We aim to become a company where the use of generative AI is normalized by each and every employee!

... but how to arrive to that point?

  • We could by realizing which tasks are suited for and what can be entrusted to a generative AI.
  • By learning how to create basic prompts depending on the task.
  • By creating a culture of acceptance of AI-generated output.

Maybe elements such as the above could help. In the rapidly changing world of generative AI,
what kind of shape should we aim for? I think we need to keep thinking about this.

To Do So

The project is currently dividing its initiatives on generative AI into three levels.

  • Level 1: With the existing systems, "Give it a try" first
  • Level 2: Create more value with minimal development
  • Level 3: Maximize the value added to the business

The following is an image of the level classification and how to proceed with the initiative.

Level classification of initiatives on generative AI
Level classification of initiatives on generative AI
Level classification of initiatives on generative AI
Estimating the value of initiatives while aiming for the appropriate level

This does not mean that all initiatives should aim for Level 3. If sufficient value can be created at the Level 1 layer, there may be no need to spend cost and man-hours to take it to Level 2. The key is to <i>try</i> lots of ideas for quick wins at Level 1. For that purpose, it is ideal that all employees, including non-engineers in the company, have a high level of AI literacy to implement Level 1.

What We Want To Work On In The Future

From An Assisted Form of "Let’s Give It a Try"

It has been several months since the introduction of in-house generative AI tools, but we still hear people saying that they don't know what they can do or when to use them. First of all, as whose with the expertise in generative AI, we are planning to increase the number of use cases where generative AI could be applied, while providing careful support for identifying its suitable tasks and in writing effective prompts.

  • At first, with careful support, we encourage giving ideas a try
  • Increase the number of in-house use cases of generative AI
  • Make in-house use of generative AI the norm

Towards An Autonomous Form of the "Let’s Give It a Try" Formula

If we continue with the above setup, our capacity will soon become a bottleneck and the problem-solving won't be scalable if we're constantly providing assistance. We would like to encourage those responsible for operations to recognize tasks suitable for AI and to entrust them to generative AI by 'trying out' the Level 1 model with basic prompts for this purpose.

  • Enabling operational teams to make use of Level 1 themselves
  • We instead offer advice and consultancy for improving Level 1 ideas, or on how to take them to Level 2 models

Trainings To Achieve These Goals

We will enhance in-house training to raise the level of AI literacy among employees.
The goal is to foster a culture where many employees share a common understanding of generative AI, enabling smooth conversations about its use and acceptance of its output.

  • Enhance in-house IT literacy trainings
  • Tailor trainings according to job type and skill level
  • Conduct trainings with fine granularity, such as image generation, summarization, and translation
  • Provide trainings that are truly necessary based on trainees' feedback, with a quick turnaround time

Sharing Information

We share our initiatives across various media platforms, including this Tech Blog. We plan to release a variety of content, including technical reviews of generative AI and introductions to the project's initiatives. We hope you look forward to it!

Conclusion

Thank you for reading my article all the way to the end!
It was a lot of abstract talk, but I hope this will be helpful to those who, like us, are seeking to leverage generative AI.

References

[*1] Ministry of Internal Affairs and Communications. "History of Artificial Intelligence (AI) Research". (See 2024-01-16)
[*2] Nomura Research Institute. "Future landscapes changed by Generative AI". (See 2024-01-16)

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