Ai

• It’s been almost half a month, and MiniMax and GLM4.6 in China have both had paid trials – the difference is still noticeable. The cc tool is quite useful. Last night I was messing around with optimizing the front-end interface, you know… as a writer, I basically don’t understand front-end development; Vibe Coding will be next, and I’m starting to get into the front-end technology stack. Domestic large models haven’t been figured out; I tried the newly released Gemini3, and it was done in five minutes. Switching to the site’s archived pages, you can see “the bookshelf.”

Alibaba (Ali) has released numerous large models, not simply a matter of “volume chasing,” but a carefully planned “Model-as-a-Service” (MaaS) ecosystem strategy. There are multiple considerations behind this, which can be summarized as “internal empowerment and external ecosystem building.”

Internal Business Driven (Inward Empowerment)

Alibaba possesses an extremely vast and diverse business landscape, including e-commerce (Taobao & Tmall), finance (Ant Financial), logistics (Cainiao), cloud computing (Aliyun), and entertainment (Youku), among others.

Here’s the English translation of the provided text:

“cc provides so many commands, which ones are actually useful? I’m going to watch some video tutorials on Douyin and simply record what I find helpful.

The generated normalized git logs automatically include copyright information, but since we’re now using domestic large models, there’s no need to add the copyright (GitHub displays cc as a collaborating developer).

Find the user configuration file and add the setting "includeCoAuthoredBy": false.

• The convention is to open Trae and prepare to start coding, and a notification arrives: the Claude model has been shut down and cannot be used; it’s highly likely that it won’t be recovered. The official provided a compensation plan, increasing usage by 300 (as of January).
• Checking it out, as expected, Anthropic is following US regulations to prohibit domestic companies from continuing to use the Claude series models. I joined the trae Discord community and saw many people complaining about the shutdown of the Claude model – after all, most people came here for Claude. The signs had already appeared before the Claude 4.5 model was synchronized on Trae; it hadn’t launched.

Attempt

With a last-ditch effort, I experimented with other models that are still supported, including OpenAI’s gpt-3.5-turbo, gpt-4, and Google’s Gemini Pro.

The frequency of article releases has noticeably increased with the use of AI, and I intend to differentiate this in the tags within the text as well. The author’s column will also note the names of large models. However, the issue persists: articles generated by AI have significantly reduced my level of involvement, with many articles being forgotten after a month or so. This occurs similarly when writing code – instead of analyzing problems based on existing knowledge, I instinctively turn to AI for analysis and troubleshooting, leading to a clear increase in “laziness.”

Previously used products, during code development, were largely satisfactory, but Byte’s SOLO introduced significant differences. Initially, participation in beta testing was through invitation codes, and now it involves submitting an email address for review. After approval, the product can be used. I’ve forgotten when I submitted the application, but today I received a notification from Trae indicating that my application had been approved.

ByteSolo’s Advantages

Following a standard project development process, it incorporates UI design, requirements analysis, functional design, technical solution implementation, and finally code development. In other words, the overall interaction logic is more friendly for beginners. For complex projects, the traditional approach remains more effective – AI as an auxiliary tool to modify and optimize existing code.

Using AI too much, we start thinking of AI for everything – often, learning new developments is more reliable with search engines plus official project documentation.

Hong Kong stocks entered on the dip, encountered a pullback, and then just randomly traded, resulting in basic losses.

Strategy Trading

Not necessarily to actually practice and make money, but rather to improve my own abilities through learning. I don’t believe in these trading indicators; I mostly trust the national fortune (luck) and investing in broad market indices via a buy-and-hold strategy.

Currently, no large model stands out as particularly superior; each company has its own strengths and preferred use cases.

Technical Documentation

For feeding code or asking IT technical questions: ChatGPT and Gemini

Write Code

Gather requirements and request code modifications: Claude