Things I Like About Linux

Ok, a few weeks ago, I gave my list of things I hate about Linux as a desktop operating system. Now, I want to counterbalance that list with the things I like about Linux. I will state upfront that none of the items on the list will be of the "Because Windows does this..." or "Unlike Windows...". I really dislike that about a lot of discourse around Linux as a desktop environment. It's more Microsoft or Apple bashing than Linux cheerleading. 

So, without further ado, here are the things I like about Linux as a Desktop OS. Keep in mind that none of what I like will depend on which distribution, or distro, that you are running. A distribution is a packaged set of software that includes the Linux kernel, graphical user interface (often Gnome, or KDE, through there are literally dozens of choices), and application software. Choose wisely.

1. It runs on extremely underpowered machines. It's true that you need to find the right distro to match your computer's resources, but Linux does this better than anyone. I'm not talking about running an older version of the operating system; I mean a fresh new version of a Linux distro on practically ancient hardware. Right now, I have a laptop from 2006 running MX Linux. It's not great but it's serviceable and still useful. All of this is due to the design of Linux. It is not monolithic. The kernel stays quite small and creative distro makers find collections of applications and GUIs that fit in under resourced machines. This is why single board computers such as the Raspberry PI run Linux. 
2. All the distribution choices. I can choose a distribution that suits me or my machine. Low resources? There's a half dozen distros for that. Something modern and zippy? Sure, there are lots of mainstream distros for that. What if you don't like the user interface? Choose a distro with something different, weird even. 
3. On that note, there are distributions tailored to functions. There are distributions that are designed for software development, creatives, office work, security professionals, specific update methods, certain languages, some for use as a LiveCD, education, beginners, Mac users, Windows users, and many more. 
4. You can still change almost anything. If you find that no Linux distro gets you 100 percent to where you want to be, you can alter something to get you all the way. Package managers, applications, even graphical interfaces, can all be changed easy enough. You are even able to load multiple GUIs on your computer and switch between them effortlessly. You can also adjust so many small things, allowing you to tweak your installation to your needs and likes.
5. The cost can't be beat. While nothing is truly free, the initial capital cost of many distros, even major ones such as Ubuntu, is zero. You can pay for support if you don't want to rely on community support and your own talents, and there are some distros only sold as commercial products. The vast majority of Linux distros, however, are available for download for free.
6. The difference between a server and desktop is basically only the GUI. You can run all the server software on any Linux installation, alongside the desktop environment. In fact, the main difference between a server distro and desktop distro is that the server distro comes prepackaged with the server software and the desktop distro with the GUI preinstalled. If you want to load the desktop distro, so that you have access to GUI tools, and then load up a bunch of server software, it's pretty easy.
7. There are a multitude of ways to install and manage software. Most desktop OS' come with what is called a package manager. As it sounds, it is a way to package, install, and then manage (remove, update, list) the software on a machine, along with their dependencies. Most distros come with either apt, yum/dnf, or pacman. Most distros have a GUI for searching catalogs of software and then installing, removing, and updating software in those catalogs. You can choose the one that works best for you or stick with whatever came with your distro.
   Ubuntu uses a system called Snap which not only installs and manages software but runs it in a container system similar to Docker. It provides easy control over running software, in addition to installation. Flatpak is similar in that it installs and manages software but runs it in a sandbox to ensure that applications can't harm the system overall. Both have GUI front ends. Snap and Flatpak represent the future of package managers - containerized systems that not only manage software installs, but the runtime environment as well.
8. Even when they look different, Linux systems can interoperate. Assuming that you have installed all the dependencies, pretty much anything that runs on one Linux machine can run on another of equal resources. Ultimately, Linux is Linux, no matter the distro. Sure, if you have something compiled for a completely different microprocessor architecture it may need to be recompiled, but all Intel architecture machines will run all run the same software.

My home lab is a prime example of the versatility and interconnectedness of Linux. I have an ancient (2006) laptop running MX Linux which I use for small monitoring tasks. I have two machines running Debian derived Ubuntu Desktop OS, but configured as servers for various services within my environment. Finally, I have a laptop from 2010 running Pop_OS, itself a variation on Ubuntu, that performs the majority of monitoring and observability for the system. That's four machines with three different Linux distributions, running a host of file and cloud services, plus monitoring. All are capable of running the same modern browser, despite vast differences in age, system architecture, and resources. There was no cost for installing and managing the operating system, outside my labor. This is what I like most about Linux.

Things I Hate About AI

Anyone who knows me will tell you, I'm not a Luddite. Quite the opposite. I like shiny new technology. I have a closet full of broken tech dreams i.e. all kinds of cool gadgets that were either ahead of its time or outlived its rather cool usefulness. So, when I tell you about the things I hate about AI, it's not a knee jerk reaction. In fact, I wrote a number of papers in the mid-2010s about the potential of AI to help us mere humans.

I don't think that AI is reaching that potential. My list of things I hate about AI is partly why I believe that. 

1. It's often wrong but sounds right. Unless you have expertise in an area, you can't tell if the AI answer is true or not. If you do have expertise, you don't need it. This is an example where no answer is a better answer. I've learned to only use AI in situations where I can truly evaluate the answer's veracity.

2. It makes us lazy. We stop doing learning simple things because the AI does it for us, just, you know, wrong. Lazy isn't necessarily bad. A lot of great software was created by people too lazy to do a simple task. Lazy plus wrong, however, is a toxic combination.

3. All that typing or speaking when a couple of button clicks will do is not progress. We moved away from command lines for a reason - they were too much work for a lot of tasks and error prone. GUIs, designed right, have democratized computing. Which brings me to…

4. AI is being used to make up for bad UI design. Instead of spending bazillion dollars on AI, try fixing your horrid interface or placing that one important selection right up front. I guess we're back to the lazy thing again. Seriously, if I have to ask an AI agent to find and change a setting for me, then the UI is not working out.

5. Generative AI slop is ruining art for everyone simultaneously. Art has soul. Art has creativity. A prompt doesn't count as either and all AI can do is mimic something already created. The problem is that people are getting used to the idea that AI can create art and that what it spits out is art. 

6. AI slop in general but especially code. When revered open source projects like cUrl have to stop bug bounties because of it, you know it's destructive. It's another effect of the intersection of lazy and wrong. You get code, plans, writing, and search results that are not useful. So, it's a waster of everyone's time and resources.

7. The environmental impact is not worth the results. Is the consumption of massive amounts of energy, and the pollution that comes with it, worth what we get from AI? The true ROI is lousy when you take the damage into effect.

8. RAM, once a cheap commodity item, is increasingly expensive because of AI needs. The irony is that there may not be PCs capable of running AI apps because of AI. Once the cost of the endpoint exceeds the benefits of the service, which will be discarded first? I'm betting on the AI.

9. General AI is purposeless. Domain specific AI adds value to whatever tasks you are doing. General AI, especially chat, is a time suck. It's like voice activated everything. It makes sense in the car but not in a crowded office, or church. AI is like that. It has to be used where it makes sense and it's not. That means it needs to be tailored to and restricted to specific domains. Copilot for Microsoft 365 is actually useful. General Copilot on Windows? Less so, by a lot.

It is apparent from my list that I doubt the long-term ROI on AI. That's a money problem and hence, not my concern. My chief concern is that using AI doesn't yield consistent, high-value benefits in most instances. The societal costs - cost of RAM, environmental damage, relying on false information, and the laziness it breeds - are everyone's problem. 

RAM It All To Hell!

 Warning: This post has the potential to be acronym laden. Read at your own risk.

As we all know by now, RAM prices are going through the roof. Some companies are even going so far as to exit the consumer market in favor of OEM sales. All of this is caused by the build out of AI systems by major tech companies. These systems have dubious profitability models. Here are some possible effects this sudden rise in RAM prices may have on the broader market.

1. The Mountain Climber. RAM prices continue to climb. And climb. And Climb. This has the effect of making RAM expensive for consumer products such as SSDs, laptops and desktops, and, especially, smart phones. Other devices that rely on computer technology such as smart TVs are also affected. More expensive storage means more expensive devices, which slows consumer and maybe small business purchases. The electronics segment takes a huge hit. They will have to decide between selling equipment and worsening margins. Ironically, many of these companies are the same companies that are building out AI centers. So, the RAM manufacturers win but everyone else loses.
2. The Crash and Burn. It turns out that no one really wants the AI stuff enough to pay for it. After hundreds of billions of dollars in capital investments and labor, most AI companies either go belly up or severely cut back on their AI products. Half or fully built datacenters are snapped up by the handful of tech companies that found a way to make AI useful enough for their customers to see value in them. With the buildout stalled or stopped, all that RAM that was held back floods the market. Consumers get a windfall, as cheap RAM allows for upgrades and lower prices, electronics and computer companies win back some margin, and AI investors go home with lighter pockets.
3. The Old Ways Return. Back when I started my career, in the before times, RAM and storage devices were expensive and limited. You had to learn to optimize your code to run on computers and devices with extremely low resources. That changed when RAM and hard drives became cheap. We could add Gigabytes of RAM and Terabytes of disk space to even low-end consumer devices. Those times may now be at an end, and the software industry may need to go back and find ways to shrink the footprint of software. This means more cost and time for software development. More cost to the consumer too. Given the amount of competition in the software business, companies may not have the ability to raise prices and, instead, take a hit on margins and profits. 
4. The Soft Landing. The boards of companies investing in AI start to demand profits from AI that match the level of investment. In response, CEOs, slow, rather than stop, the build out of new data centers. RAM doesn't exactly flood the market, but prices start to come down as availability comes back up. Eventually, the market finds its equilibrium. At that point, consumer prices are a bit higher but not crazy high and some value from AI is achieved. Rather than a blood bath, larger companies go on a buying spree and consolidation takes hold. Most of the winners will be large tech companies and a handful of now incredibly wealthy entrepreneurs. 

To me, the most likely scenario is the Crash and Burn scenario. This happens all the time in the tech business. Companies jump on a bandwagon, spend stupid amounts of money, discover that consumers aren't in it for the durations, and then retrench. Some companies win; some lose. The AI Crash and Burn is the best scenario for the consumer. They have some short term pain but eventually get lower prices and some AI value. 

The Soft Landing is also possible, though less so than the Crash and Burn. The history of computing is rarely so pleasant. Just look to the Dot Com crash and the Storage Service Provider bloodbath for inspiration. This scenario is probably the best one for the industry and consumers alike. Prices come down and we get new and useful products. If this happens, it will be a unicorn.

The least likely is the Old Ways Return scenario. Software is a bit like food. Our ancestors lived with constant food scarcity. Over time, food became abundant and we no longer know how to live in a scarcity environment. That's why so many of us are overweight to the point that Ozempic is a major drug. Early in my career, I had to jam software into kilobytes of ram and disk space. Very few software developers today have ever lived with that kind of resource scarcity. RAM and disk space were so cheap that you could expect consumers to just buy more to suit your applications. Memory and storage space are just not something that extreme optimization is given time and money to anymore, and no one knows how to do it well.

If we get the Mountain Climber scenario, we're all screwed. If RAM prices continue to climb, it hurts the tech industry across the board. Consumers too.

These are just observations from my 40+ year old perch. I'm typically an optimist until given a reason not to be. I'm rooting for the Soft Landing, even if I think it unlikely. Let's see if we get the AI equivalent of the PC revolution or Dot Com crash.