Untitled conversation
PaperGPT : KEN: Kernel Extensions using Nat.Lang.
1
Conversations
Unofficial GPT with "KEN: Kernel Extensions using Natural Language" in its knowledge for retrieval. Does not use conversation data to improve models.
What can you tell me about KEN's approach to simplifying eBPF programming?
How does KEN's use of large language models improve kernel extension development?
Can you explain the symbolic execution technique used in KEN?
Show an example of a prompt and an eBPF program produced by KEN
