The AI-first language that compiles one codebase to CPU, GPU, and quantum — automatically. From research notebook to production deployment, without rewriting a single line.
Native tensors, autodiff, @gpu kernels, and built-in experiment tracking.
Compile to native binaries. 100x faster than Python. Zero cold-start.
Single binary tools with parallel execution and instant startup.
4KB binaries on ARM Cortex-M, RISC-V, ESP32. TinyML on-device.
Compile to native iOS and Android from a single Aether codebase.
Run Aether in the browser with near-native performance via WebAssembly.
Run independent tasks simultaneously with a single keyword. No asyncio.gather, no Promise.all, no goroutines. Dependencies with after(), racing with parallel.race, and automatic cancellation.
The runtime auto-parallelizes independent operations. You opt out of parallelism, not in.
Write tensor math in Aether. The compiler generates CUDA PTX, ROCm HIP, or WebGPU shaders automatically. Works on NVIDIA, AMD, and Intel GPUs.
No CUDA C++. No manual memory transfers. No thread block configuration. Just math.
No types needed to start. Add them when you're ready. Enable #strict for production. The same code grows from prototype to deployment without a rewrite.
Write once. The runtime auto-places operations on CPU, GPU, TPU, or quantum processor. No code changes.
Compiles to native code via Cranelift/LLVM. Predictable ARC memory management. Zero cold-start.
Use PyTorch, HuggingFace, pandas from Aether. Zero-copy tensor sharing. Zero switching cost.
Mathematical contracts prove your code is correct at compile time. Built for safety-critical AI.
One codebase compiles to server, iOS, Android, WASM, and IoT. No model conversion. No wrappers.
@experiment logs everything automatically. Compare runs, track metrics, snapshot models. Built in.