Ai

AI has been integrated into daily development workflows, and recent investments have shifted focus from external funds to internal stocks and ETFs.

Open Source Projects

Project Log

Last week, I was bored and tried to obtain GitHub badges, starting to use the Issue module. Previously, when writing code, I always wanted to find a place to record the content of each AI modification, but creating a separate document to record it felt disorganized. Now that we have the Issue module, tagging them to distinguish between bugs, features, enhancements, etc., has made the records clear and efficient. Even if I might not need them in the future, recording them is still a form of accumulation. View Issue List

Cultural Propagation: Its ideological influence, subtle and pervasive. AI Programming: Not performing software design, resulting in a lot of rework.

Cultural Propagation

Initially, the project only supported English, Japanese, and Korean. Thinking it was just AI translation, we wondered if supporting more languages wouldn’t be a good idea. So, French, Russian, and Hindi were added. At this point, no problems were detected; when the program executed translations, formatting issues arose due to historical code problems, requiring re-translation of archived articles.

The initial design of the blog translation project was overly complex – first parsing Markdown format, then using placeholders to protect the content, and finally sending it to a large model for translation. This was entirely unnecessary; large models inherently possess the ability to recognize Markdown syntax and can directly process the original content while maintaining formatting during translation.

Our work shifted from debugging code to debugging the prompting of the model. Model: google/gemma-3-4b Hardware: Nvidia 3060 12GB Indeed, we chose a non-thinking model – thinking models were inefficient when executing translation tasks. We compared the performance of 4b and 12b parameters, and for translation purposes, gemma3’s 4b parameter was sufficient; there was no significant advantage in terms of 12b parameters. 12b parameter speed: 11.32 tok/sec , 4b parameter speed: 75.21 tok/sec.

For many years, I’ve focused on backend development, and recently started to explore AI programming while dipping my toes into some frontend-related content. However, during this period of tinkering, I gradually realized I was falling back into an old habit – being dazzled by shiny new things. I constantly try to use AI to create a frontend interface, but in reality, these attempts haven’t provided much practical benefit for my current work and are actually wasting my energy.

This site is developed using Hugo, but I’ve always used Chinese titles, which results in less friendly generated article links. In simpler terms, when shared, they don’t look as good because the Chinese characters are escaped into formats like %E4%BD%A0%E5%A5%BD within the links. While you can solve this by setting a slug, it’s tedious to do manually every time.

Therefore, I decided to try using Claude4 to develop a translation assistant that automatically converts Chinese titles to English slugs and adds hyperlinks within the articles. This would eliminate the need for manual setup.

Since we’ve established “AI Inspiration Collision Forum,” there’s been a lot of random content being created, with people experimenting with AI to record and publish things, but thoughtful reflection is becoming increasingly scarce. Moving forward, it would be beneficial to slightly control the output of this section and consolidate it into a monthly magazine format – releasing one article per month would suffice.

• Last month, we experimented with cursor, but due to the limitations of the free quota, we didn’t develop overly complex features; we just did some basic testing. We discovered then that Byte also released similar products, both using the same large models – Claude-3.5 – at their core. Byte’s product is called Trae, initially launched in the Mac version and finally released its Windows version in February of this year. Big companies are good because you can freely “white嫖” (literally translates to “free-eat”), without having to pay, with unlimited use of Claude-3.5 – this model performs quite well.

Artificial Intelligence (AI) has undoubtedly been one of the most hotly debated topics in the technology field in recent years, particularly over the past two years, with AI technology experiencing rapid advancements. Whether it’s deep learning, natural language processing, or computer vision and automated decision systems, the application scenarios for AI are constantly emerging. However, despite continuous technological breakthroughs, AI still faces a bottleneck similar to that of a Docker release – a lack of a killer app to truly ignite the market.