Run AI models as real smart contracts
Al can be run truly onchain as Internet Computer smart contracts, making it tamperproof and unstoppable, and autonomous if needed
AI Models on ICP Today
Try out the AI demo by yourself
Check out the open-source repo on GitHub and tryout the AI demo by yourself.
let image = imageops::resize(
&image, 160, 160, FilterType::Triangle);
let tensor = Array4::from_shape_fn(
(1, 3, 160, 160), |(_, c, y, x)| {
image[(x as u32, y as u32)][c] as f32 / 255.0
});
let result = model.run(
tvec!(Tensor::from(tensor).into()))?;
A recent study on AI finds that nearly half of the respondents (49%) are concerned about the misuse of AI for nefarious purposes.
Survey in the Artificial Intelligence Index Report 2024 by Stanford University.
What is needed to solve these issues?
Model integrity
Users need assurance that their AI prompts are handled by untampered models. Traditional software integrity methods, such as source code analysis, are infeasible for AI models because they consist of complex numerical weights and extensive matrices, rather than human-readable code, making direct verification impossible.
Data confidentiality
During training and operation, AI models handle sensitive data, like medical inquiries or corporate secrets. Users need guarantees that their information remains secure and doesn't leak to the model creators, other users, or AI infrastructure providers.
Availability
AI models will become essential for business processes and societies in general. As with every critical infrastructure, solutions must be found to keep AI models resilient to interruptions and to protect them from censorship.
What the future holds
Blockchain AI is still in its early stages. Currently, smart contracts can run small AI models like ImageNet for onchain image classification. Short-term improvements will decrease latency and support larger models, while the long-term goal is to enable smart contracts to perform AI computations on GPUs, allowing both training and inference of large models fully onchain.
Short-term
- Faster deterministic floating-point operations
- Wasm SIMD (Single-instruction multiple data)
- Upgrade Wasm memory to 64-bit
Long-term
- Explore API for deterministic AI computation on GPUs.
- Develop public specification for nodes with GPUs.
- Add subnets with the new nodes to ICP.
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