
iNEPHANY
Optimising neural networks to reduce compute time, energy consumption, and costs for AI model training and deployment.
Date | Investors | Amount | Round |
---|---|---|---|
* | $2.2m | Seed | |
Total Funding | 000k |
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Inephany focuses on enhancing the efficiency of neural networks, particularly in the realm of AI model training and deployment. The company addresses the significant energy consumption and carbon emissions associated with operating data center clusters for AI tasks. By developing an industry-first optimizer, Inephany aims to deliver faster and more capable AI models while significantly reducing the compute time, energy usage, and financial costs involved. Their technology is applicable to various types of neural networks, including Transformers for Generative AI, RNNs for financial time series modeling, and CNNs for object recognition in autonomous vehicles. Inephany's solutions cater to businesses and industries that rely heavily on AI and machine learning, providing them with tools to optimize performance and sustainability. The business model likely involves licensing their optimization technology to companies seeking to improve the efficiency and cost-effectiveness of their AI operations. Keywords: neural networks, AI optimization, energy efficiency, cost reduction, Generative AI, Transformers, RNNs, CNNs, sustainability, compute time.