Ai

Recently mingling in various programming large model communication circles, the most complained about thing is model degradation.

• Models deployed on local desktop computers are quantized models, essentially downgraded versions.
• With “vibe coding” so popular, could it be that the content output by current large models is the most valuable product – code?

“Previously, it was mentioned that when logging into Gemini Cli, you needed to configure the Google Cloud Project ID. This is already wrong – if it’s a personal account, there shouldn’t be this restriction. The fact that this restriction exists indicates that you’ve started triggering Google’s security system and are being identified as not being a personal account. It’s frustrating; after using it for half a month and getting used to it, now I have to return to the embrace of cc + domestic models.

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.

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 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.

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.