The FIRST Company to Develop Multimodal AI with 200+ Installations Worldwide
The FIRST Company to Develop Multimodal AI with 200+ Installations Worldwide
Multimodal Artificial Intelligence
Multimodal AI
Multimodal AI is a new AI paradigm, in which various data types (image, text, speech, numerical data) are combined with multiple intelligence processing algorithms to achieve higher performances. Multimodal AI often outperforms single modal AI in many real-world problems. Check the following demo video to see what Multimodal AI can do.
Aimenicorn Ecosystem
Aimenicorn is a Multimodal AI software ecosystem developed by Aimesoft. Aimenicorn simplifies the process of applying Multimodal AI technologies in various industries by providing Multimodal AI software packages.
Aimenicorn contains three main layers: The bottom layer is the Multimodal AI framework, which provides complicated data fusion algorithms and machine learning/inference technologies. The middle layer contains the core libraries/frameworks based on Multimodal AI, such as AimeCard for structure analysis and document image examinations of the OCR, with AimeFace being used for face recognition technologies and AimeFluent for natural language understanding. Finally, the top layer contains various applications for specific domains, which combine cutting-edge Multimodal AI technologies with deep domain knowledge to yield an impressive user experience. AimeHotel, AimeHospital, AimeBank, Aime AIShop are just some of these applications.
Technologies
Aimesoft’s technologies to realize Multimodal AI
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Natural Language Processing technologies
Tokenization, POS tagging, keyword extraction, synonym/antonym detection, information extraction, relation extraction, semantic search, natural language understanding
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Computer Vision technologies
Object recognition, semantic segmentation, face recognition, gender/age recognition, OCR (optical character recognition), image search/retrieval, predictive analytics based on image
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Speech Processing technologies
Language model extraction from Web text, acoustic model creation, hot word/trigger word detection, noise cancellation, etc.
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Data Mining technologies
Big Data processing, KPI prediction, predictive analytics based on Big Data, recommendation algorithms, data generation for machine learning
