> For the complete documentation index, see [llms.txt](https://devs.novanet.xyz/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://devs.novanet.xyz/jolt-atlas-zkml.md).

# JOLT Atlas (zkML)

JOLT Atlas is a high-performance zkML framework built upon [JOLT](https://eprint.iacr.org/2023/1217.pdf) for efficient neural network inference from ONNX models with cryptographic proofs.

Traditional circuit-based approaches are prohibitively expensive when representing non-linear functions like ReLU and SoftMax. Lookups eliminate the need for circuit representation entirely.

In JOLT Atlas, we eliminate the complexity that plagues other approaches: no quotient polynomials, no byte decomposition, no grand products, no permutation checks, and most importantly — no complicated circuits.

For an extended introduction to JOLT Atlas and the novelty of its approach, we recommend reading [this article](https://blog.icme.io/sumcheck-good-lookups-good-jolt-good-particularly-for-zero-knowledge-machine-learning/).