The response to our initial announcement about ELNA on the Dfinity Forum has been nothing short of inspiring. The enthusiasm and interest that the ELNA project has garnered within the ICP community are a true testament to the potential of democratized AI. We are deeply appreciative of the hundreds of requests pouring in for the initial beta-testing waitlist, as well as the numerous messages of support and engagement on Twitter and the forum. We extend our heartfelt gratitude to the ICP community for the warm welcome and encouragement. Your enthusiasm fuels our determination to explore the technical intricacies that drive ELNA’s AI ecosystem.
As we delve into the core of ELNA’s technical architecture, we aim to address some common queries that have emerged:
Building the Foundation
ELNA’s inception was rooted in a vision of democratizing AI, enabling users to craft personalized chatbots tailored to their distinct requirements. To manifest this vision, we knew that a robust technical foundation was essential - one that facilitated seamless customization, secure deployment, and efficient data management. It’s the decentralized attributes of the Internet Computer that offered the ideal foundation upon which to construct this revolutionary platform. However, we have encountered some hurdles on our path:
- Developing AI within Canister Web Assembly Environment: One of the challenges we’ve tackled is developing AI technologies optimized for the canister’s web assembly environment.
- Instruction and Memory Limitations: The instruction and memory limitations of canisters pose constraints, particularly when dealing with the inference of larger models.
- Balancing Speed, Scale, Privacy, and Transparency: We are working on maintaining a delicate balance between speed, scale, privacy, and transparency while implementing AI functionality on a decentralized infrastructure.
Advancements on the Horizon
Moving forward, we are optimistic about the advancements that are being made within the Dfinity ecosystem to address these challenges. Some notable improvements include:
- Latest WebAssembly Stable Memory: The incorporation of the latest wasm-native stable memory provides a solid foundation for AI development within the canister environment.
- Advanced Quantization and Distillation Techniques: These techniques are poised to minimize the size and instructions required for fine-tuning and inferencing, without compromising performance.
- Enhanced Data Architectures: Ongoing efforts in data architecture and design are aimed at optimizing vector embedding and data handling.
- Continual Evolution of LLM Models: The ever-evolving landscape of larger language models (LLMs) will continue to provide improved AI capabilities for ELNA.
The Path Forward
Our roadmap reflects our commitment to refining and expanding ELNA’s capabilities:
- Phase 1: Wallet integration and vector embedding for user data on the canister.
- Phase 2: Full inference engine deployment within canisters.
- Phase 3: Introducing fine-tuning capabilities within canisters, including methods like QloRA for efficient storage of weights.
- Phase 4: Exploring standalone Large Language Models (LLMs) akin to advanced AI agents within the Internet Computer ecosystem.
Join Us in Shaping the Future
The journey ahead for ELNA is a collaborative one. We invite developers, researchers, enthusiasts, and the entire ICP community to actively participate in shaping the future of AI on the Internet Computer. Your insights, feedback, and engagement will be pivotal as we continue to innovate, refine, and expand ELNA’s capabilities.
Stay connected with us on Twitter and visit our website to stay informed and engaged with ELNA’s evolution. As we embark on this transformative journey, we look forward to your contributions and ideas, propelling us closer to a future where AI is harnessed by and for the community.
Feel free to reach out with any questions, thoughts, or suggestions. Together, we’re pioneering the next era of AI on the Internet Computer.
Join the initial waitlist for alpha access to ELNA : https://forms.gle/SRP4PoM5AnSERZet7