What we do

Role of Team AIBOD:

As evolution of information technology is swift, even large companies should seek more from new technologies in order to make their teams to share, merge or acquire new data.

 

Beyond that trend, how companies collaborate and manages internal and external information will be a key to success.

 

Team AIBOD fills the technological gap when it comes to offer users an efficient tool to have deep insights from data and share them with other individuals.

 

View on data flow:

Recent technological advances in Big Data, Open Data, IoT and AI towards the Fourth Industrial Revolution have been creating a large trend on data utilization. One trend is for data sources, and the introduction of Open Data and IoT has been enabling us to access a gamma of data that was impossible some decades ago. Technology related to Open Data has been maturing so that every citizen is able to access public data. Technology related to IoT has been evolved so that we can sense status of a variety of things.

 

Another big trend is on data processes.  Since the introduction of Big Data, combined with the latest advances in AI, human beings are being provided with the necessary tools to process and analyze variety of data. Technology related to Big Data has evolved so that we can process large volumes of data in different formats. Techniques that are employing AI has been grown enough so that we can have new insights easier and faster.

 

IoT and AI also have increased the demand of powerful hardware, which pushed forward the boundaries of current technology, which resulted in more advanced hardware, such as faster and energy-efficient processors, faster memory, larger storage systems, and so on.

 

As a result of such trends, we can now have a network based Software product / service development environment. With the advent of the Micro Service Architecture (MSA), it enabled companies to develop large systems as a combination of existing services. Using this technique, it became easier to public a common Access Point Interfaces (APIs) that contain many functionalities for the outside users.

 

 

Team AIBOD products / services:

 

AIBOD Share & Mill

Team AIBOD’s primary and core product is AIBOD Share & Mill, called ASM. ASM offers a “Place” for data utilization among teams. AIBOD Share provides users a tool to share their internal and external data / insights. AIBOD Mill allows users to analyze those contents with easy-to-understand operation. Users can have a data journey through the following four steps, Collect, Accumulate, Share and Utilize.

 

The first step is to collect deep information on data. ASM automatically generates metadata from input data. The generated metadata includes keywords, description of data, quick analysis of pictures and URL links if data is a text or PDF, quick analysis results and quick visualization of numbers if data is CSV, images or time-series. ASM generates tags from these Meta data.

 

The second step is to accumulate those contents. ASM does analysis on those contents for users’ convenience, offering appropriate recommendations to show users’ desired contents, and comfortable discovery to let users find out more.

The third step is to share those contents with others. ASM does provide marketplace in a catalog view to share users’ contents within a team. Users are able to make their own contents open. All members in the same team are able to view/use the shared contents.

 

The fourth step is to utilize those contents. Open digital contents are used by others to perform the same analysis as the original or to have new insights. ASM does provide an analysis place for these purposes. Using commonly used analysis tools such as R, ASM has generalized library for typical or widely used algorithms.

 

AIBOD Digital Tools

AIBOD Share & Mill (ASM) provides APIs to use ASM functions above mentioned, Auto-generation of Meta data, Recommendation and etc. Third venders can develop their own digital tools using ASM API.

 

AIBOD QuickMill is a digital tool that runs on ASM. There are plenty of data analysis and machine learning tools. Some tools offer beginners or non professionals an easy-to-use experience without programming. However, even such non-programming tools require a basic understanding of data analysis. Without this skill, users may be unable to make process or data flow. QuickMill provides straight forward steps with analysis results visualization. This tool does needs basic knowledge of how to see the results, but shows results in graphs, box-plots, distribution maps, and such so that users can utilize their own created models comprehensively. 

 

AIBOD DataScience

AIBOD DataScience is an extension of ASM that focuses on data analysis users, i.e. Share/Marketplace + QuickMill.

 

Users do data analysis and machine learning with QuickMill GUI. AIBOD DataScience offers collaboration capabilities to load data on the marketplace into QuickMill, to store created learned models or QuickMill workspaces to the marketplace, to load existing learned models or QuickMill workspaces to utilize Team’s results and knowledge. Users can also view / search existing internal (own) and external (other members’) contents that leads to team collaboration.

 

AIBOD DataStadt

AIBOD DataStadt is an extension of ASM to focus on social domains and people’s lives, especially on energy domain. Some members of Team AIBOD have been working on energy data analysis with local university, to estimate power demand, to highly equalize demand and supply. Team AIBOD now continues the work in Japan’s national project and we have a plan to introduce machine learning technology to have more generalized estimation model. Such an electric power analysis application is being developed using AIBOD Mill. 

 

AIBOD Lecture

Members of Team AIBOD have strong academic backgrounds.  Team AIBOD offers an enterprise lecture course in AI / Machine Learning to make good advantage of that hybrid insights of academia and business. Six lecture courses were given last year as in-company training for large companies in Japan. Also, we have been implementing this experience into AIBOD QuickMill and other data analysis related properties.

 

Artificial Intelligence

We will use AI (Artificial Intelligence) technology to help you maximize efficiency and optimize management resources.

 

Although AI is a recent buzzword, it is expected that IT technology will become an indispensable element in the present age not only in the information communication industry but also in various industries. Fintec is a good example, but other industries are expected to be driven by data driven decision-making.

 

Meta AI

Artificial intelligence utilizing data utilizes a wide range of technologies from statistical processing to machine learning. These are logical techniques based on mathematics. It is indispensable to make this practical systematization of artificial intelligence technology, which technology can solve which problem by utilizing which technology.

 

We will systematize machining centered on machine learning, and we will embody it as the AI ​​platform "AIBOD Mill" that can be used by non-experts.

 

Mathematical Approach

Mathematical concept is important for utilization of AI and big data · open data analysis. There are many mathematical applications and tools, but we are focusing on graph analysis that deals with topology and networks.

 

Graph analysis is not a new technique, but there are many relevant data. What is the point of modeling what kind of relationship as graph data, but city infrastructure etc. can clearly be defined as graph data. If there is a killer application there is a potential to become popular.

 

Digital collaboration

Share big data and open data (BOD) held by companies, tools and know-how that utilize them, and create new knowledge and business through collaboration.

 

We automatically generate metadata such as keywords and explanation information from data and files to capture and provide accurate recommendation and search experience to users. We will embody it as a collaboration platform "AIBOD Share".