This year, I once again opted for a “no-job” mode, but to my delight, my personal assets actually saw a net increase.

So, where did this income come from? It wasn’t from my strong technical field. The two new projects I attempted this year both fell short of expectations and didn’t bring the anticipated breakthroughs. What truly made a difference was the investment logic of “money making money.”

This was somewhat unexpected, especially given the overall sluggish economy. Yet, the stock market, like fish swimming upstream, displayed unusual activity and enthusiasm. The market trend was consistently positive, as if “riding the tide.” And I, as someone not directly involved in creating social value, also benefited from it.

My roommate was also laid off, and I’m preparing to move. I’m looking forward to my new home (a still-unknown place, I don’t know where my next little nest will be).

I look forward to my passive income covering my living expenses, and I look forward to the daily returns from my investment funds (whether they rise or fall).

After reading several articles about AI, such as “AI is killing the web. Can anything save it?”, “Stack overflow is almost dead” and “Google’s AI search features are killing traffic to publishers” as well as the popular Reddit discussion “Do you believe we’re in an AI bubble?”, I have been led to think deeply about the relationship between AI and the web, and their future development.

In the past, when I needed to look up information or solve a development problem, I would go to a search engine or Stack Overflow. Now, I first ask an AI/LLM, and only turn to a search engine if I don’t get a satisfactory answer. With a search engine, you need to research to find the answer yourself. An AI/LLM, on the other hand, gives you a direct answer based on your situation (context). It feels like consulting a very experienced and courteous person, allowing you to get answers quickly and saving a lot of time on filtering and searching. However, its answers are not always correct (they can have hallucinations). At this point, one must still rely on search engines. If even search engines don’t provide a satisfactory answer, the only options left are to figure it out yourself or consult an experienced person.

Since the emergence of AI/LLMs, everyone has started using them to replace knowledge-based searches. AI/LLMs have captured traffic from search engines and the Web, becoming the new entry point for traffic. Along with mobile apps and social media, they are competing for Web traffic, making a bad situation worse for the Web’s already limited traffic. AI is killing the Web, and its demise is only a matter of time.

Chrome 138 has just been officially released. Having previously written “How to Force Install the World’s Best Ad Blocker uBlock Origin on Chrome”, I decided to investigate ways to keep Manifest V2 support in Chrome. Chrome 138 is the last version to fully support Manifest V2. Starting with version 139, Manifest V2 will be disabled by default. However, there are still methods to keep it enabled in versions 139 and 140.

There was a time when I was a person who spent without a second thought. I’d casually buy premium groceries from Hema¹ and pay for my parents’ vacations without hesitation. I just flipped through my JD.com² order history, and the change in the numbers is startling:

• 2021: ¥9,791
• 2022: ¥22,206
• 2023: ¥5,778
• 2024: ¥10,000 (for a necessary productivity tool)
• 2025 (to date): ¥1,654 (for staples like rice, flour, and oil)

My five-year-old phone was on its last legs, and I thought about replacing it during this year’s “618” shopping festival³. But faced with the idea of “buying a new phone,” I hesitated for days. I kept asking myself: Would a new one boost my productivity? Would it improve my quality of life? Would keeping the old one negatively impact my daily use? The answer to all three was no. However, the temptation of a 24-month interest-free installment plan and a generous subsidy was just too great. I caved and placed the order. But when the delivery arrived at my door, reason ultimately won out over impulse, and I rejected the package.

In today’s world, where the wave of artificial intelligence is sweeping the globe, GPU computing power is a key factor of production. However, a common pain point is that GPU resources are both scarce and expensive.

Take mainstream cloud providers as an example. Not only are GPU instances often hard to come by, but their prices are also prohibitive. Let’s look at a direct comparison:

• Google Cloud (GCP): The price of one H100 GPU is as high as $11/hour.
• RunPod: The price for equivalent computing power is only $3/hour.
• Hyperstack / Voltage Park: The price is even as low as $1.9/hour.

The price difference is several times over! This leads to a core question:

Can we design a solution that allows us to enjoy the low-cost GPUs from third-party providers while also reusing the mature and elastic infrastructure of cloud providers (such as managed K8s, object storage, load balancers, etc.)?

The answer is yes. This article will detail a hybrid cloud solution based on Tailscale and Kubernetes to cost-effectively build and scale your AI infrastructure.

Recently, I encountered a very strange phenomenon: in a newly created cluster, when doing a subPath mount, the file in the container at that subPath is empty. I checked the syntax and configuration; everything seemed correct. But I’m not hitting the known bug where a non-existent ConfigMap subPath is mounted as an empty file nor issue 54514. Moreover, if I mount the ConfigMap directly, the key’s contents show up fine in the container. It really feels like I’ve run into a bug!