3 code implementations • 20 Aug 2021 • Hammond Pearce, Baleegh Ahmad, Benjamin Tan, Brendan Dolan-Gavitt, Ramesh Karri
The most notable of these comes in the form of the first self-described `AI pair programmer', GitHub Copilot, a language model trained over open-source GitHub code.
no code implementations • 3 Dec 2021 • Hammond Pearce, Benjamin Tan, Baleegh Ahmad, Ramesh Karri, Brendan Dolan-Gavitt
We perform a large scale study of five commercially available, black-box, "off-the-shelf" LLMs, as well as an open-source model and our own locally-trained model, on a mix of synthetic, hand-crafted, and real-world security bug scenarios.
1 code implementation • 13 Dec 2022 • Shailja Thakur, Baleegh Ahmad, Zhenxing Fan, Hammond Pearce, Benjamin Tan, Ramesh Karri, Brendan Dolan-Gavitt, Siddharth Garg
Automating hardware design could obviate a significant amount of human error from the engineering process and lead to fewer errors.
no code implementations • 22 Jun 2023 • Baleegh Ahmad, Benjamin Tan, Ramesh Karri, Hammond Pearce
In this work, we explore the features that help LLMs in this classification and evaluate the performance of FLAG on known bugs.
no code implementations • 28 Jul 2023 • Shailja Thakur, Baleegh Ahmad, Hammond Pearce, Benjamin Tan, Brendan Dolan-Gavitt, Ramesh Karri, Siddharth Garg
In this study, we explore the capability of Large Language Models (LLMs) to automate hardware design by generating high-quality Verilog code, a common language for designing and modeling digital systems.