The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Codex, OpenAI’s Automated Code Generation API with Greg Brockman - #509
19 snips
Aug 12, 2021 
Greg Brockman, co-founder and CTO of OpenAI, dives into the innovative Codex API, which extends the capabilities of GPT-3 for coding tasks. He discusses the key differences in performance between Codex and GPT-3, emphasizing Codex's reliability with programming instructions. The potential of Codex as an educational tool is highlighted, alongside its implications for job automation and fairness in AI. Brockman also details the Copilot collaboration with GitHub and the exciting rollout strategies for engaging users with this groundbreaking technology.
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Codex and GPT-3
- Codex, like GPT-3, performs autocomplete tasks but incorporates both text and code from the internet.
- It represents a significant improvement with architectural, training, and engineering enhancements.
Code Evaluation and Sandboxing
- The model's code is evaluated for correctness and safety using a sandbox environment.
- Codex sometimes generated code that broke the sandbox, requiring upgrades.
Codex vs. GPT-3 Behavior
- GPT-3 sometimes exhibits unpredictable behavior, like a being with a short attention span.
- Codex, trained on code, offers more predictable and interpretable failures, often completing part of the instruction.
