GeoMatrix @GeoMatrix_Dev

If you're interested in GeoMatrix, we invite you to join our beta testing program! 😁 Here's the link to the sign-up form: tally.so/r/ja8LqJ

Today, using the GeoMatrix base environment, I undertook a new and interesting exploration: I created a composite score by weighting and combining the disposable household income, educational attainment at the college level or higher, and homeownership rates across Hong Kong’s 18 districts. First, I used GeoMatrix to create a brand-new sandboxed Conda environment and installed the NumPy and Pillow libraries. Then, I activated the corresponding terminal and ran the script—it went very smoothly. Now, let’s take a look at the results: As can be seen, the Central and Western District and the Wan Chai District on Hong Kong Island are far ahead of the rest. Of course, these two districts are also the foundation of Hong Kong as a financial, trade, and even intelligence hub. Due to factors such as a large floating population and the government’s development priorities, Kwun Tong, Kwai Tsing, and Wong Tai Sin rank at the bottom. The average score for Hong Kong Island is significantly higher than that for Kowloon; this gap is largely driven by income and educational attainment, while home ownership has a relatively weaker influence. I believe this can serve as one of the references for those considering where to settle in Hong Kong in the future.👇 #gischat #gis #geospatial #python #BuildInPublic #Social #gis #Cartography #HK

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@milos_gis This really is a fascinating phenomenon.😂

@milos_gis @OGrease1 Compared to artificial intelligence, politics, and celebrity gossip, the number of people who love GIS and cool maps is inherently small. I wonder if this is perhaps determined by X's algorithm?

This is Tally form link.😄 tally.so/r/ja8LqJ

Just now, I was working on an assignment for my machine learning course. The assignment for the first class was very simple: create a Conda environment, install the NumPy and Pillow libraries, and write code to output the bands of a remote sensing image. The whole process took me 15 minutes, 14 of which were spent writing code and organizing the report. Installing Conda, creating a Conda environment, and activating it took less than a minute—though I did have to wait 20 seconds for the installation to complete (depending on HKU’s internet speed). So, GeoMatrix saved me a significant amount of time. I didn’t have to look up command-line instructions or worry about whether the activated Conda environment was correct—I could just focus on the assignment itself. If you think GeoMatrix will also improve your productivity, join our beta testing program. The beta testing sign-up form is in the comments section below.👇 #GISchat #PythonDeveloper #Geospatial #GIS #Conda #BuldInPublic #GeoAI #HKU #NumPy

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@milos_gis I also really like using soft colors in my maps—it makes them feel very soothing.

But as you said, taking responsibility and interacting with others are traits of mothers with teenage or adult children—it’s part of their nature as mothers. Yet there are other people in society: young men and women, middle-aged and elderly men, and so on. Not everyone possesses maternal instincts. Today’s social division of labor has become extremely specialized; everyone is forced to be nothing more than a cog in the machine—a cog that isn’t allowed to think for itself. This inevitably turns people into robots, even if they don’t want to be.

@simongerman600 @xruiztru Heat waves typically affect a much, much larger area than other disasters, and they also place a tremendous strain on a city’s power and transportation systems, among others.

It’s true—putting myself in their shoes, if I were an employer, I wouldn’t want too many employees over 50 in my company either. Not only would this increase payroll expenses, but it would also make my team lack vitality. When I was an employee myself, repetitive work turned me into a “robot,” and compared to “robots” over 50, I’d much rather have younger “robots.” After all, while experience is important, its value is generally limited. So my view is this: first, we need regulations and safeguards at the government and legal levels; second, everyone should engage in lifelong learning to ensure they don’t become “robots”—not just physically, but mentally as well. That way, no matter how new the technology that emerges in the future or how much it boosts productivity, I believe that as human beings, we can rise to the challenge by maintaining a mindset committed to lifelong learning.

Yes, the government should fulfill its role in addressing, driving, and adapting to change. Similarly, we as individuals should also take the initiative to address and adapt to change. But there’s one question that’s been on my mind: for young people, this might not be an extremely difficult task, but what about middle-aged adults? What about someone who has been working, studying, and living within a fixed routine for decades? From a physiological perspective, everyone has a tendency toward inertia and is reluctant to step outside their comfort zone. “Stepping outside your comfort zone” is easy to say—it’s just a matter of opening your mouth—but putting it into practice is very difficult. Let me give an example: I’m currently a young person, and I can skillfully use large language models (LLMs) to boost my work efficiency. My parents, on the other hand, only use LLMs to chat and apply them to their work to a limited extent. My grandparents—both paternal and maternal—don’t even know what AI is. How to help them adapt to these changes is a question I’ve been pondering constantly, because one day we, too, will grow old. As society continues to evolve and technology keeps advancing, I believe this is an issue worth serious consideration.

@jnmet Is it because of El Niño?

@milos_gis QGIS, as open-source software, might be able to do that, but ArcGIS, as closed-source commercial software, I think will be much slower—after all, it has to take business and profit considerations into account.

Yes, it may be difficult for us to ever board a SpaceX spacecraft in our lifetime to fly into space and see what the Earth really looks like, but satellites allow us to look down on the Earth from the comfort of our homes—and that’s when our “worldview,” shaped by our national identity, is reshaped.

@TheGeoWhisperer This is a very novel perspective. In the past, I’ve always focused on how GIS can solve natural and social problems, and it never occurred to me that GIS could facilitate collaboration across teams and regions!

@simongerman600 I think it would be even better if we could add the corresponding latitude lines.

@simongerman600 Why didn’t the Dallas government properly relocate these people before the highway was built?

Generally speaking, the HPC resources of a university, institution, or company are made available to anyone who needs them. This means we usually have to wait in line or make a reservation. If we were to submit a job to the HPC after merely tweaking a few parameters or the loss function, it would result in a waste of computing power and low efficiency. While large-scale data training tasks certainly need to be performed on HPC, we should first successfully train the model on a small dataset locally to observe real-time results and confirm there are no bugs before submitting it to the HPC. This raises the issue that the local environment must be consistent with the HPC environment. GeoMatrix is designed to address this very problem, allowing researchers to easily switch back and forth between their local environment and the HPC.

Today, the instructor for my Machine Learning course told me that he and his graduate students typically conduct scientific research in an HPC environment, but generally speaking, we still need to fine-tune parameters locally. 🖥️ Moving forward, I plan to continue refining GeoMatrix so that researchers can align their local and HPC environments with a single click. What do you all think? In your work or research, what kind of environment do you typically work in?👇