AI that learns and processes relationships by considering data (modality)
Getting started
Multimodal technology is a technology that combines different types of data (such as text, images, audio, and video) to help AI models process and understand information in various formats. Just as human communication integrates various senses such as language, sight, and hearing, multimodal AI provides richer and more intuitive results by analyzing multiple data modes in an integrated manner.
Key features of multimodals
- Integrate and understand data
Multiple data types such as text, speech, and images are analyzed in an integrated manner to enable accurate understanding based on context. For example, you can use explanations provided with photos to better understand images, or analyze text (subtitles) and speech together in videos. - Interaction between modals
By learning the relationships between each data mode, deeper predictions and generation are possible. For example, generate text based on images or convert speech to text to extract meaning. - Enhanced flexibility
It can learn and predict complex data sets rather than a single type of data, so it works flexibly even in complex environments.
Multimodal applications
Multimodal AI is being used in various industries:
- Content creation: Creation of visual materials combining text and images.
- Video and audio analysis: Create more natural dubbing or subtitles by combining audio and subtitle data from media content such as movies and TV shows.
- Medical image analysis: Disease diagnosis by combining X-ray images and patient text records.
- automotive industry: Accurate environmental recognition by combining camera images and radar data in autonomous driving systems.
Key examples of multimodals
- OpenAI's GPT-4
GPT-4 supports multimodal functionality that can process text and images together. For example, when a user uploads an image and asks a question, they understand the image and provide relevant answers. - DeepMind's Diffraction
Discrever is a general-purpose AI model that can process various data modes in an integrated manner, and flexibly learns and predicts various types of data such as text, images, and audio. - Meta's ImageBind
A technology that can integrate and process various input formats such as text, images, audio, and 3D data into a single model. - Google's Palm-e
It is a robot control technology that combines vision and language, providing the ability to view images and perform appropriate tasks.
Multimodal AI technology at LETR WORKS
Twigfarm's LETR WORKS uses multimodal AI to innovatively provide IT content localization solutions. This technology combines text, voice, image, and video data to improve existing translation and localization processes, and provides the following key features:
- Multimodal translation:
- Simultaneous analysis of text and image data provides context-appropriate translation.
- For example, when translating user manuals, the user experience is enhanced by linking images and text.
- AI-based voice and subtitle sync:
- Supports more natural subtitle production and dubbing by integrating and analyzing video voice and text subtitle data.
- It is particularly beneficial for providing localized content in various languages in the global market.
- Cultural customization:
- Perform translations and localizations that reflect regional cultural differences.
- It is possible to create content suitable for various languages and cultures.
- Linked to Voice Cloning (Voice Cloning):
- Simultaneous localization of text and speech in a multi-modal manner by learning the voice of a specific speaker.
LETR WORKS use cases
- Global media localization:
LETR WORKS is using multimodal AI to help global film companies and broadcasters create localized content reflecting various languages and cultures. The integration of voice, subtitles, and text reduced localization time and improved quality. - B2B content solutions:
When translating IT manuals and technical documents, text and images are combined to ensure both technical accuracy and readability. This contributes to increasing the competitiveness of software companies, especially when entering global markets.
Multimodal AI has broken the boundaries of data and has become an innovative technology that enables more natural information processing and generation. Using these technologies, LETR WORKS presents a new standard for content localization and supports successful communication in global markets.
Twigfarm's LETR WORKS realizes faster, more accurate, and culturally sensitive content creation through AI and human collaboration. The development of multimodal AI technology will bring about even greater changes in various industries in the future.
Editor/Choi Min-woo
