August 2024 Summaries

Riza, a company focused on safely running untrusted code, explored the performance of OpenAI's GPT-4o model on the HumanEval benchmark, which consists of 164 Python programming problems. The model achieved a high Pass@10 rate of 97.0%, indicating it solved 159 problems within ten attempts, and a Pass@1 rate between 88% and 94% for individual samples. However, five problems consistently failed across ten attempts, highlighting areas where the model struggled with logic errors and misinterpretations of problem requirements. Specific cases are analyzed to understand these failures, such as incorrect handling of sentence delimiters, mismanagement of nested structures, and improper ordering based on digit sums. The examination aims to identify and rectify the errors, with the potential for improvements by feeding failure contexts back into the model for future iterations.

Riza offers a solution for safely and easily running untrusted code by providing a Code Interpreter API that can be hosted locally using their Docker image, rizaio/code-interpreter. This setup ensures all data remains within the user's system while initializing Python and JavaScript runtime environments by default. Users must obtain a license key to run the image and can access a free trial by contacting Riza. The API can be interfaced using Riza's SDKs, which require configuring the base URL to the local server. For those not using Docker, Riza provides downloads for Linux and macOS, with plans to expand support to additional operating systems and architectures. The CLI, currently in early release, allows users to initialize default runtimes which may take a few minutes on the first run, and Riza welcomes feature suggestions through their Discord channel.