*This post is about verifying the computations run on GPU. Not using GPUs to accelerate ZKP! GPUs are having a long — moment in the spotlight. Often celebrated for their prowess in rendering lifelike graphics, GPUs now sit at the heart of some of the most demanding computational tasks in modern

In the rapidly evolving world of blockchain and cryptography, we often hear about blazing-fast zero-knowledge virtual machines (zkVMs) designed to scale Ethereum or tackle large-scale computational problems. However, for true privacy, ZKPs need to run locally. This concept, known as local verifiable compute, involves implementing extremely space-efficient ZKPs for use

Zero-knowledge proof (ZKP) systems often require composition with other ZKP systems to achieve specific traits, such as privacy or improved on-chain verification (e.g., Groth16). Traditionally, this process involves cryptographic experts meticulously converting the verifier of one system into an arithmetic circuit for use in another. This labor-intensive task is

Humans have an insatiable desire for speed. From supersonic jets to rockets that breach Earth's atmosphere, we constantly strive to go faster. This obsession with velocity extends to the realm of zero-knowledge proof (ZKP) systems, where we crave for our proofs to run as swiftly as the programs

'Foreign field' or 'non-native field' arithmetic appears everywhere in zero knowledge proof systems. If you want to use ZKP for boolean operations, public-key cryptography, or proof composition you will undoubtedly run into the constraint blowup due to foreign field work. However, if you look into open-sourced

Memory consistency checks (MCC) are an essential part of any zkVM (zero-knowledge virtual machine). However, most of the time, they hide behind the scenes as an unseen but vastly important implementation detail. It would not be surprising if you've never even heard of them! In this article, I

In the near future, zero knowledge proofs (ZKPs) will run on thousands of devices, verifying truth and ensuring privacy. Similar to how advanced cryptography functions seamlessly with protocols like HTTPS today, people will use it ubiquitously in their browsers, operating largely in the background undetected. The only hurdle to this

The full benefits of AI cannot be achieved until AI can be fully trusted–secure, compliant, and privacy preserving. Trusted AI requires integrating privacy-preserving verification software throughout the AI tech stack. The best approach for making secure, compliant, and privacy preserving are zero knowledge proofs. ZKPs are privacy-preserving protocols that