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Vision AI
Vision AI
is an artificial intelligence technology that
helps computers deeply understand and
interpret the visual world. It can analyze
digital images and videos to accurately
identify and classify objects.

Progress in Vision AI is fueled by
improvements in hardware, massive
amounts of data, algorithms, deep learning,
and other technologies that are spurring
innovation in various sectors like
manufacturing, healthcare, automotive,
security, and beyond.
lvm-main
Advancement
Current state
Industry
transformation
History of XIIlab
and Vision AI
2010~2012
XIIlab Establishment
AlexNet wins image recognition
competition which spotlights Vision AI
2012~2013
Acquire big data processing technology
Convolutional neural networks and others
improved model accuracy
2013~2017
Start developing data-driven AI technology
AlphaGo’s victory boosts interest in AI
2017~2019
Gain the ability to commercialize AI video
Expanding the Vision AI market
2019~2020
Join NVIDIA Partner Network
Expanded use of technologies
such as autonomous driving
2021~Present
Listed on KOSDAQ and incorporated
in the US
Practical applications in multiple fields
The evolution of the
Large Vision Model
Following advancements from Texture
to Vision Transformer, SAM, and GPT,
the next stage in the Large Vision Model
is Computer Vision.
graph
Fixed environment recognition
- Texture
- Image Pattern
Learn data patterns
- Deep Learning
- Convolutional Neural Networks (CNNs)
- Layer
- Image Classification
- Object detection
- Segmentation
Attention is All You Need
- Transformer Architecture
- Reduced training time
- Effective long-sequence handling
GPT, Transformer Base
- Google, Vision Transformer, VIT - image
   sequence
- CLIP
- Effective long-sequence handling
Multi Modal : LVLM
OpenAI (DALL-E, GPT-3, GPT-4)
META, Segment Anything, SAM
Large
Vision-Language
Model, LVLMs
Multi-Modal Learning
Combines both pictures and words to
obtain more valuable and practical
information.
Detailed and accurate situational awareness
Achieve improved situational awareness
by combining text descriptions and visual
content for better accuracy and detail.
Developing creative applications
Develop new forms of creative
applications, such as art generation,
descriptive captions, conversational AI,
and more.
GPT-4 (OpenAI)
Language models for
creativity, visual input
processing, and long
contextual understanding
gpt4
DALL-E 3 (OpenAI)
Models that can convert
text to images
dalle3
SORA (OpenAI)
Models that can convert
text to video
sora
Stable Diffusion
(stability.ai)
Image generation model
stable