Reflecting on years of stock trading experiences, although I didn’t make a fortune, I also didn’t lose too much. The biggest issue was an unreasonable allocation of funds and an unstable mindset. Currently, my primary source of income is work, earning a fixed salary each day through part-time jobs, and my ability to withstand financial fluctuations remains at the level of bonds and bank deposits. However, people are inherently greedy; if you buy too little, even when prices rise, you won’t make money; and if you buy too much, you will lose money. At this point, maintaining a stable mindset is particularly important, as it can help us keep our wealth afloat.

As the earliest web novel readers entered middle age, the type of “revenge” stories catered to them also evolved. The protagonists often appeared as fathers, mentors, or elderly figures, meeting the different needs and demands of middle-aged readers for life and emotion. These works no longer solely focused on upgrades and reversals; instead, they emphasized emotional resonance and life reflections.

Target Audience: Shifting Reader Base Amidst the Passage of Time

Former web novel readers have largely transitioned into middle age. They’ve experienced the trials and tribulations of life, leading to shifts in their mindset and values. The passionate, adventurous elements they once chased are no longer the sole focus for them. Instead, they seek emotional resonance with their current lives and a sense of nostalgia for past years, as well as aspirations for the future. Middle-aged爽文 (shuangwen - a popular genre) emerged specifically to meet this psychological need. It utilizes plot settings that closely align with the lives and attitudes of middle-aged readers, attracting this particular demographic.

Ollama is an open-source AI tool designed to enable users to run and deploy large language models (LLMs) locally. Its goal is to provide a convenient and efficient way for developers to use models like GPT on their local machines without relying on cloud services. Ollama supports multiple models and focuses on optimizing performance, allowing even resource-constrained devices to smoothly run these models.

“I’d gotten used to using zsh on Linux, and when I was writing a blog post the other day, I suddenly realized that PowerShell 7 also supports persistent command-line prediction views, so I tried it out. It turned out to be pretty useful after all.”

“I don’t know what I did to enable this feature, but it just appeared—that’s all.”

In today's diverse operating system environment, system administrators and developers have been constantly seeking a tool that is cross-platform, efficient, and powerful to meet their needs in system management and automation tasks. PowerShell 7 is precisely such a noteworthy tool, offering not only robust scripting capabilities but also the ability to run across Windows, Linux, and macOS operating systems, bringing users unprecedented convenience.

PowerShell 7: A Powerful Tool Across Platforms

Cross-Platform Features

PowerShell 7 breaks down platform limitations, allowing you to perform enterprise-level server management on Windows systems, system administration in Linux environments, or daily development tasks on macOS – all with a unified PowerShell 7 tool. This significantly increases productivity and reduces the learning curve and operational complexity associated with platform differences.

• The U.S. stock market’s sustained bull run is largely driven by the “watering” of the dollar, rather than America’s inherent “hard power.”
• The modern monetary system has gradually become an important theoretical cornerstone for many economies worldwide since the 2008 financial crisis, emphasizing the subjective initiative of large governments in intervening in markets and utilizing government fiscal deficits as a primary tool to achieve full employment while stabilizing inflation.
• The term “large government” is most commonly associated with Keynesianism, which highlights the government’s role in “smoothing peaks and troughs” during economic cycles – for example, suppressing overheating and stimulating contraction. It places great emphasis on the multiplier effect of government spending, i.e., how much an increase in monetary stimulus can amplify consumer multipliers; a 1-unit increase in government expenditure stimulates an equivalent increase in corporate and individual income, leading to business expansion and job creation, and ultimately mitigating economic downturns. Furthermore, it adopts a relatively conservative approach to fiscal deficit limits and sustainability. The multiplier effect will drive market recovery, thereby increasing government revenue, especially during periods of overheating, where government debt potential and interest rate levels can be accumulated as stimulus funds for the next cycle.
• The modern monetary system is more like an extreme extension of Keynesianism, but with differences; its biggest characteristic is the limitation on government debt, which means the central bank should not have independent autonomy, primarily focused on inflation and full employment. With limited resources and productivity, inflation refers to the government continuously increasing purchasing power through unlimited fiscal deficits as technological progress improves production efficiency, until it reaches the ideal level of full employment and production bottlenecks; continuing to increase monetary supply will lead to inflation, at which point it chooses to set a limit on fiscal deficits, as long as there are idle production resources, increased debt will not trigger inflation.

After the Financial Crisis

Of course, reality is not an ideal world, and execution in each stage involves human participation. Keynesianism is also selectively applied, leading to more economic stimulus during downturns and less overheating suppression. Economic imbalances generate achievements, while overheating also does, making it extremely difficult to suppress them. The numerous economic problems brought about, even a new financial crisis, are not inferior to the economic shocks caused by traditional overcapacity. The 2008 global financial crisis was actually a market self-reinforcement resulting from extreme Keynesianism, leading to the proliferation of speculative structural financial investment products such as real estate and financial investment products derived from real estate as their underlying assets. Even before the crisis erupted, there was a lack of risk awareness at academic, political, and market levels, treating debt-fueled prosperity as achievements, and more people benefited from it, such as the enormous financial system: losses are yours, dividends are ours, it’s bankruptcy – we made a fortune, money cannot be spat out. Ultimately, this led to massive investment by participants, bearing the profits of previous stages.

In the foreign exchange market, particularly at banks or currency exchange points, we often see terms like “buy rate” and “sell rate.” Many people may not be clear about these concepts, or even confuse them. Today, let’s help everyone understand the meaning of these rates and their functions through a simple example.

1. What are “Buy Rate” and “Sell Rate”?

• Buy Rate: The bank or currency exchange institution is willing to purchase foreign currencies at this rate, meaning when you sell your foreign currency (such as US dollars) to the bank, the bank will pay you RMB according to the buy rate.
• Sell Rate: The bank or currency exchange institution is willing to sell foreign currencies at this rate, meaning when you buy foreign currency with RMB, the bank will sell you the foreign currency at the sell rate.

Simply put:

When debugging programs under Windows using Visual Studio, if the PDB file does not match the executable file, Visual Studio will display “Unable to load symbol file.” The program crashes and generates a crash dump. If it’s an mismatched PDB file, Visual Studio cannot smoothly enter the crash site.

What is a PDB File?

A PDB file is a debugging information file created by Microsoft, used for debugging programs. It contains information such as the symbol table, source code filenames, line numbers, and other debugging data. A PDB file can be generated during program compilation to aid in debugging.

It seems like another year has passed, and the biggest change at work is a significant increase in AI participation. Previously, switching between different development languages required developers to be familiar with various language-specific API interfaces. Now, these basic code snippets can all be generated by AI, which is a huge blessing for developers.

ChatGPT

As early as 2023, I’ve written two simple introductory articles about it. Now it’s been 25 years – how to put this… I haven’t felt a significant improvement. It still needs to develop its own cognition, be able to reasonably break down tasks, and, of course, most importantly, identify whether AI-generated code contains bugs.