Unlock the Potential of AI
Deploy your AI with maximal efficiency
Consider AI compression if you're experiencing any of the following issues
Challenges
Sky-high AI Operation Costs
Excessive GPU cloud costs for operating the AI model.
Latency in Performance
The AI model included in the service is too slow, negatively impacting the user experience.
Need for On-Device AI
Need to run AI on devices for security, cost, and user experience reasons
What is AI Model Compression?
AI model compression is to compress and squeeze the neural network so that less computations are needed, achieving computational efficiency.
Compressing AI creates a tradeoff between speed and performance. Multiple tests should determine under what conditions the tradeoff is smallest and what tradeoffs you need to make given your use case.
Benefits
AI compression can help you
Faster
From research
to real life application
Cost Effective
Equal performance
at a low cost
On-Device AI
The smaller size,
the broader applications
How to Compress an AI Model?
Quantization is a way to lightweight AI models by adjusting the precision with which data is represented. Data commonly represented as floating point 32 or 16 bits can be represented as 8 bits, or even as low as 4,2 or 1 bit.
AI Compression Toolkit
OwLite is the easiest AI compression toolkit, simplifies the process of applying advanced AI compression techniques to pre-existing machine learning models
Compress Your AI Model with Us
SqueezeBits excels in the optimization of deep learning models using state-of-the-art model compression techniques.
