When building and maintaining complex C++ projects, performance optimization and memory management are crucial. When faced with performance bottlenecks or memory leaks, we can use eBPF (Extended Berkeley Packet Filter) and BCC (BPF Compiler Collection) tools for analysis. As we saw in Redis Issue Analysis: “Deadlock” Problem Caused by Stream Data Read and Write (1), we used BCC’s profile tool to analyze Redis’s CPU usage, drew a CPU flame graph, and then could easily find the functions with high time consumption and their call chains.

CAPTCHAs have become an indispensable part of our daily online lives, providing a basic security barrier for websites and applications. From the initial simple numerical CAPTCHAs to various complex ones today, their complexity has been gradually increasing to resist attacks from automated tools and bots.

The following image shows some common CAPTCHAs:

The sole purpose of these CAPTCHAs is to distinguish between humans and machines. However, with the rise of large models like ChatGPT, especially the advent of GPT4-Vision’s multimodal capabilities, can CAPTCHAs still intercept machines?

On September 25th, OpenAI announced new capabilities for ChatGPT: ChatGPT can now see, hear, and speak. ChatGPT finally got “eyes” and can understand images.