FRONTEO's in-house developed AI engine "KIBIT
KIBIT" is a "specialized AI" that leads the discovery of optimal information from a vast amount of data.
KIBIT" is an AI (Artificial Intelligence) developed in-house by FRONTEO and continuously improved. It is a "specialized AI" with strengths in natural language processing and network analysis, and by guiding discoveries from a vast amount of data, it offers completely new perspectives and insights to professionals working to solve problems.
Linguistic AI that analyzes text
KIBIT" processes large amounts of data on behalf of humans by reading the tacit knowledge and senses of humans from text and reproducing human judgment and information seeking methods.
It is highly accurate in analyzing not only English, but also Japanese and other Asian languages (Korean and Chinese), including special character codes and delimiter positions.
Discovery and retrieval from unstructured data
Documents, e-mails, and dissertation data, which consist of large amounts of text data, are difficult to analyze as they are as numerical data.
KIBIT excels at analyzing such unstructured data with the power of natural language processing to find the exact information you need.
Proprietary Vectorization and Algorithms
KIBIT has developed and uses a proprietary algorithm that is different from the Transformer, a mainstream generative AI such as ChatGPT.
With an algorithm that specializes in language understanding itself rather than sentence generation, KIBIT is optimized for document discovery and relevance detection.
Intuitive Visualization of Data
In order to intuitively grasp the overall picture of information, its characteristics, and the relationship between elements, we also emphasize "visualization" through mapping.
This "mapping" is a technique that not only enhances the value of information, but also leads to "serendipity" in discovering unexpected information.
Difference between AI "KIBIT" and Generative AI
Generative AI is AI that generates content different from the original data, such as images and text, based on learned patterns. ChatGPT and Gemini are among the most famous generative AI for language systems. Large-scale language models (LLMs) are a type of generative AI and are deep learning models trained on huge amounts of text data.
FRONTEO's AI "KIBIT," on the other hand, uses algorithms to reproduce the judgment and tacit knowledge of highly specialized experts, and excels at finding the necessary information from vast amounts of information and guiding discovery.
Specialized AI "KIBIT
Algorithmic reproduction of experts' thinking
KIBIT specializes in reproducing the superior judgment and tacit knowledge of experts and locating information in documents. Therefore, it can assist experts in making high-level judgments.
Track record of support and implementation for many large companies
We have a track record of being introduced in large companies, including government agencies and major financial institutions, and we have accompanied their operations for many years and continue to achieve results.
Light enough to run on a notebook PC
The amount of calculation required for analysis can be reduced by minimizing the number of parameters. Therefore, it is a power-saving and easy-to-implement AI engine that can be operated at the laptop PC level.
No risk of halcination
Since models are constructed from only the data set to be analyzed, there is no risk of halcination, and analysis can be performed with high accuracy.
Generative AI and large-scale language models (LLM) for language systems
Models optimized to predict the next word
AI models are optimized to keep predicting the next word (token) and can generate answers to questions and sentence summaries based on trained data.
Challenges in optimizing operations for each business
Deep learning used in generative AI requires a large amount of electrical energy due to the huge amount of calculations performed in the hidden layer to output results.
Requires large computational resources
The amount of computation required for analysis can be reduced by minimizing parameters, for example. Therefore, it is a power-saving and easy-to-implement AI engine that can run at the laptop PC level.
Note the halcyonation of output results.
This is a general-purpose model that has been pre-trained with general information, and should be used with caution to avoid halcination of output results.