flâneur

Sumcheck good. Lookups good. JOLT good. Particularly for zero-knowledge machine learning.

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The a16z crypto research team recently dropped some serious heat with their 6x speedup announcement, showing how JOLT's lookup-based approach with sumcheck protocol can dramatically outperform other SNARK constructions running on just CPU. Their "Twist and Shout" optimizations proved that when you stop trying to arithmetize everything and start embracing lookups and sparsity, beautiful things happen: Less code to audit. Faster prover. Almost “prover killer” proof. While the a16z team was busy revolutionizing general-purpose zkVMs, we were focused on another problem: making zero-knowledge machine learning more practical in NovaNet. Turns out, ML workloads have some very specific patterns that play exceptionally well with JOLT's lookup-heavy architecture. Where other approaches get bogged down in expensive field arithmetic for ML operations, JOLT's sumcheck + lookup combo cuts right through it. Traditional circuit-based approaches are prohibitively expensive when representing non-linear

TL;DR: We made zkML 3-7x faster than everyone else. Here's how. Standing on the shoulders of giants The a16z crypto research team recently dropped some serious heat with their 6x speedup announcement , showing how JOLT's lookup-based approach with sumcheck protocol can dramatically outperform other SNARK constructions running on just CPU. Their " Twist and Shout " optimizations proved that when you stop trying to arithmetize everything and start embracing lookups and sparsity, beautiful things happen: Less code to audit. Faster prover. Almost “prover killer” proof . 🏅 zkML-JOLT (JOLT Atlas) b

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