Discover how Pruna AI’s open-source framework revolutionizes AI model optimization with methods like caching, pruning, and quantization for enhanced performance.
Caption:Pruna AI logo on open-source framework for AI optimization.
The Highlights:
- Pruna AI, a European startup, is releasing its optimization framework for AI model compression methods as open source.
- The framework includes efficiency methods like caching, pruning, quantization and distillation to enhance the performance of AI models.
- Pruna AI’s framework can evaluate the quality loss post-compression and measure the performance gains achieved by compressing a model.
- The company offers an enterprise version with advanced features like an optimization agent that automatically finds the best combination for speeding up models without compromising accuracy.
Pruna AI charges by the hour for its pro version. “It’s similar to how you would think of a GPU when you rent a GPU on AWS or any cloud service,” Rachwan said.
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Pruna AI Introduces Open-Source Framework for AI Model Optimization
European startup Pruna AI is set to release its open-source optimization framework for AI models on Thursday.
The company has been developing a framework that incorporates various efficiency methods like caching, pruning, quantization, and distillation into AI models. Co-founder and CTO John Rachwan highlighted that the framework standardizes saving and loading compressed models, applying different compression methods combinations, and evaluating the compressed model’s performance.
Pruna AI’s framework can assess quality loss post-compression and the resulting performance improvements. Rachwan likened their role in standardizing efficiency methods to how Hugging Face did with transformers and diffusers. Notably, big AI labs have been leveraging compression techniques like distillation to enhance flagship models’ speed.
Pruna AI caters to various model types but currently focuses on image and video generation models. The company aims to simplify the optimization process by offering an enterprise version with advanced features such as an optimization agent that automates finding the best combination for speeding up a model without compromising accuracy by more than 2%.
The startup operates on an hourly charging basis for its pro version akin to renting GPU services on cloud platforms. By optimizing models effectively, users can save significantly on inference costs. For instance, Pruna AI managed to reduce a Llama model size by eight times while maintaining performance using its compression framework.
Having recently secured $6.5 million in seed funding from investors like EQT Ventures and Kima Ventures among others, Pruna AI envisions its compression framework as a worthwhile investment that yields long-term benefits for customers.
Romain Dillet from TechVatsalya noted this development as significant within the European tech landscape due to Pruna AI’s innovative approach towards optimizing AI models efficiently.
With over 12 years of experience covering technology startups, Romain is recognized as one of Europe’s leading tech journalists who has consistently identified emerging trends in technology space before they become mainstream.
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Conclusion:
- Pruna AI, a European startup, is making its optimization framework open source on Thursday. The framework includes efficiency methods like caching, pruning, quantization and distillation to enhance AI model performance.
- Pruna AI’s optimization framework can evaluate the quality loss and performance gains after compressing a model. This tool aims to simplify the compression process by combining various compression methods into one easy-to-use platform.
- The company focuses on image and video generation models while supporting other types of models as well. Pruna AI offers an enterprise version with advanced features like an optimization agent that automatically finds the best combination for faster speed without compromising accuracy.
Resources:
Pruna AI Official Website, Hugging Face, OpenAI
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