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Welcome to SkywardAI 🚀

SkywardAI is an open-source community dedicated to developing efficient and specialized AI models. Founded by passionate students from RMIT University Melbourne, our mission is to create high-performing AI solutions that prioritize accessibility, efficiency, and sustainability. We empower users to run advanced AI models on consumer-grade hardware while supporting cloud-native deployment.

The community is inspired by an open-source OpenAI alternative API LocalAI.

🌟 What We Do

Our AI open-source community aims to develop specialized, high-performing models that are not only smaller but also optimized for specific tasks. Unlike massive LLMs, these models prioritize efficiency and accessibility while maintaining top-tier performance. By minimizing data requirements and reducing computational demands, we can create a more sustainable AI ecosystem—maximizing intelligence per watt. This approach ensures that AI remains both powerful and practical, making advanced technology more accessible for widespread adoption.

Screenshot 2024-08-01 at 10 27 05 PM

👩‍🌾 Our Mission

Our mission is to make AI both powerful and practical by developing efficient, accessible, and sustainable models.

We aim to deliver:

  • Highly efficient, specialized AI models optimized for specific tasks
  • Smooth streaming inference on CPUs with open-source multimodal models under 10B parameters
  • Inference with RAG mode for enhanced retrieval-augmented generation
  • A simple trainer for customizing neural net training
  • One-command deployment for seamless integration

🚀 Our Vision

Our vision is to create a thriving community that drives the future of AI with sustainability and efficiency at its core.

  • AI should be both accessible and efficient—maximizing intelligence per watt
  • Everyone can be a neural network hero—today we define functions, tomorrow we define neural networks
  • AI isn't just a trend; it should be a practical, deployable solution on consumer-grade hardware
  • By reducing data requirements and computational overhead, we ensure AI remains sustainable and widely available