Following some of my recent LEGO MOC and MOD posts here, here, and here, this LEGO scene of the Desert Skiff rescue above the Sarlacc Pit from Return of the Jedi (1983) is another pre-pandemic build of mine. The desert skiff is an unmodified 9496 set from LEGO. However, I added more minifigures (Han and Chewbacca), and I recreated the scene as it roughly appears in the film when Lando Calrissian falls overboard with one of Jabba’s henchmen who is devoured by the Sarlacc. The base of the build is the high walls of sand surrounding the Sarlacc’s maw with a toothed opening and digestive tract beneath the sand full of bones and skulls of its past meals.
Before building this version of the scene, I had constructed a wider base and used the Sarlacc Pit monster build that came with 9496 as shown on the top shelf in the photo above. Also, Lando was holding onto the Desert Skiff by a whip instead of a chain, which I used on the newer diorama shown in more detail below. Pity the poor bastards who get slowly digested over a thousand years–that is, until Boba Fett took care of the buried beast!
I’ll note that when I was a kid, the Power of the Force Tatooine Skiff by Kenner was one of my favorite vehicles next to the Millennium Falcon, not only because it had a lot of playability and features packed into but also because I recognized the engineering and craftsmanship that went into its design, including retractable skids, extending/dropping plank, and a sideboard action figure launcher.
One of my favorite mid-1990s video games is Star Wars: Dark Forces for PC. In the game, you play as Kyle Katarn, a mercenary employed by the Rebel Alliance, who stumbles on the Dark Trooper project through one of his missions (none of Dark Forces is considered canon, but the Dark Troopers were brought into canon via the second season of The Mandalorian). I played Dark Forces often on my 486DX2/66MHz machine, but I was unable to beat it back then (the video game Force is weak in this one). Thanks to DOSBox, I finally beat it about 25 years after I first played it!
The Star Wars universe created by George Lucas is, like his earlier film American Graffiti (1973), about motion, movement, travel, and vehicles. The importance of movement in Star Wars is what elevates vehicles like Han Solo’s Millennium Falcon to be a character in their own right. The same is true for Katarn’s HWK-290 light freighter named The Moldy Crow. I liked its angular, bird-like appearance. It reminded me also of He-Man’s Talon Fighter from 1983’s Point Dread and Talon Fighter playset. The image of the Moldy Crow stuck with me, and when I was building with LEGO in Atlanta in 2014, I thought of a way to capture the Crow’s design in a LEGO MOC (my own creation).
Rotational Side Views
Top Views
Bottom Views
Crew Compartment
Details
Reflection
Unfortunately, I sold my LEGO Moldy Crow on eBay before Y and I moved to Brooklyn (along with a boatload of other LEGOs). I wonder if the buyer still has it or modified it in some way.
A lot of the bricks that I used in the build were older style dark grey, which I don’t have many of any more. I would like to take another stab at The Moldy Crow with my newer bricks and use techniques that I’ve learned over the years since then. Another project added to an already long list!
Anthropomorphic cat wearing suit and tie, and standing in front of a chalkboard. Image created with Stable Diffusion.
I’ve been spending a lot of time studying and using generative AI technologies and thinking about their pedagogical implications, and over the summer, I invested more energy into taking intensive online classes relating to generative AI on LinkedIn Learning, which I wrote about here and here. The suggestions below are a distillation of some of the important ideas that I have learned and plan to implement after my sabbatical this year concludes. Readings associated with these points can be found on my extensive generative AI pedagogy bibliography. Maybe you will find some of these helpful to your thinking for your own classes as we make our way into the science fictional future together!
Build ethical and legal issues of generative AI into every discussion and assignment. Of course, a separate module or a whole course can be focused on these topics, but students need to see how ethical and legal issues are tightly woven into how these technologies are developed, the challenges that they present, and how to be prepared to avoid, mitigate, or resolve those challenges. By weaving ethical and legal issues into the quotidian, it helps students think critically about these issues throughout the learning process and it avoids the conclusion that ethics and legal concerns are just an afterthought.
Show students how bias in generative AI is real. Since generative AI is trained on datasets of work created by people, the AI systems will reflect the biases inherent in the content of the dataset and the ways different people might be represented in the dataset (e.g., more books by white male authors and fewer by writers of color or women writers). Bias is unfortunately baked in. Help students explore how these biases reveal themselves insidiously, might be discovered through prompting, and how to mitigate them (if possible) in the way they use generative AI as a part of their workflow.
Help students become responsible generative AI users. Students need to be taught how to document, cite, and acknowledge the use of AI in their work at school and later in the workplace. This can refute earlier use of ChatGPT and similar sites that fueled what some might consider plagiarism or cheating. Helping students see how it’s okay to use these tools when allowed and properly documented helps them see how they are a tool to support their work rather than a way to avoid working.
Reveal how generative AI technologies are designed, developed, and operated. By learning how generative AI is built and deployed, students get to see how the sausage is made. They will learn that generative AI isn’t magical or all knowing or perfect. Instead, they will realize that years of research and development in mathematics and computer science led to the current state of the art with these technologies, which is still lacking. They will discover the limitations of what these technologies offer (e.g., text generating AI primarily performs sentence completion and has no understanding of what it is doing, or its training data has gaps, deficiencies, biases, etc. that directly affect the text generated). This can be paired with lessons on how large language models are trained, how they are a black box in terms of how they work, and initiatives to build explainable artificial intelligence (XAI).
Approach generative AI as another layer for students’ digital literacy development. Considering AI’s biases, falsehoods, so-called hallucinations, and off-topic responses, pairing generative AI with instruction on vetting information, using research tools (online and off), and applying one’s own skepticism will combat the notion of AI’s trustworthiness, expertise, and authoritativeness. Also, it gives students another source for comparing, contrasting, and verifying when checking facts and establishing reliability of various sources of information.
Introduce generative AI as a new tool for students to add to writing and creative workflows. Some students might like to think that generative AI is a one-stop shop, but we can reveal to them how it can support different elements within a larger creative framework that depends on their cognition, imagination, and effort to produce deliverables. It can aid with ideation, brainstorming, planning, and outlining, as well as handling less important writing tasks, such as replying to an email or DM. An important corollary to this is the fact that prompt engineering is a skill unto itself that students have to learn and develop. In some cases, figuring out the best prompt might require more time, energy, and collaboration with others to accomplish than had the students done the writing output themselves.
Refocus on editing, revision, and the writing process to incorporate generative AI text into student work. One way to accomplish this is teaching students higher level editing and revision tasks using AI generated text as the material for editing. Another way is to teach students how to use editing tools, such as those built into Microsoft Word, Google Docs, and LibreOffice, to work with the text generated by AI.
Harness generative AI as a learning tool to support student experimentation and discovery by example. Students can ask the generative AI to summarize their writing, rewrite their writing for different audiences, turn outlines into paragraphs, etc. However, for students to gain some benefit from this, there needs to be a reflective writing exercise that gives the student an opportunity to dissect what the AI did to the student’s original composition and then based on what the student learns in reflection, they attempt their own new composition with the same goal as that given to the generative AI. The AI’s output can be combined with the student’s reflection and composition for evaluation by peers or the instructor, depending on how you are providing feedback to students on their work.
Recognize writing students as technical communicators, because they use generative AI technology in their writing processes. I am thinking of part of the Society for Technical Communication’s definition of tech comm: “Communicating by using technology, such as web pages, help files, or social media sites.” Using AI to create outputs or as a part of the writing process means that students are using technology to communicate in a deeper way than how we might have thought of this before. Acknowledging this with students might make more of them aware of this as a career path or how they might leverage their communication skills as they transition into the workplace.
Warn students about the possible jeopardy they face by providing their writing, prompts, questions, and personal identifying information to online-based generative AI tools like ChatGPT. Anything you type into the system is saved and associated with you. This means that your inputs might be used to train and fine tune future versions of the generative AI system, and the data collected about you based on what you type and how you use the system might be utilized by the system provider or sold to third parties (e.g., for advertising, adjusting insurance rates, making loan decisions, etc.). This can be connected to a larger discussion of how to protect one’s self online, practice privacy best practices, employ obfuscation techniques, etc. Teaching students how to use their own locally hosted LLMs, such as Meta’s LLaMA and its derivatives. This gives them more control over how their data, and it gives them the option to fine tune their local model to better fit their needs.
Gradient blend of my most recent desktop computer from before (left) to now (right).
“In nova fert animus mutatas dicere formas / corpora.” “It is my design to speak of forms changed into new bodies.” –Ovid, Metamorphoses: Translated into English Prose, Published by G. And W.B. Whittaker, London, 1822, p. 1.
As much as I wish that I had a hoard of computers in a basement or attic, I don’t. It’s not for a lack of want to keep my old computers. It’s always been a financial consideration–sell the old to help finance the new (or used = new to me). While an errant tree limb destroyed my first practical computer–an Amiga 2000HD, I’ve been selling my old computers to help pay for newer ones and upgrades since I was in high school when I sold my 486 DX2/66MHz system before going off to Georgia Tech in 1995.
For someone who values and enjoys working on vintage computer systems, it’s a bitter pill to swallow that I have to do this. However, it also means that my computers often take on a Frankenstein monster-like existence of becoming–morphing from one system into another via upgrades and reconfigurations.
I wanted to share some background on my most recent desktop computers from the past 10 years or so as a way to reflect on this practice of tinkering and changing that produces more capable and powerful computer over time. Sometimes, a shift in architecture or new work requirements calls for a change. Sometimes, it’s wanting to try something new.
2012: Intel i7-2700K in Corsair Case
I wrote about turning this computer, which I had originally intended to use with Windows 7, into a “Customac” or “Hackintosh,” meaning a PC that ran MacOS X, here and here. I built the computer using on sale gear from the Microcenter in Duluth, GA. The 50 cal. ammo box case by Corsair and green cold cathode light tubes were its two extravagances.
2014: i7-2700K in Retro Sleeper Case
Before moving to Brooklyn to start my job at City Tech, I asked my friend Mark with help finding a beige ATX case that I could transplant my i7-2700K system into. What the kids call a “sleeper case,” or a retro-styled case but sporting contemporary computing kit. By this point, I had jettisoned the video card and relied on the CPU’s built-in graphics as this simplified using it as a Hackintosh.
After moving to Brooklyn, I switched from MacOS X, which was becoming more troublesome with Apple ID-connected software with Hacintoshes, to Linux Mint.
I had a Sapphire video card of some sort, but I can’t recall what it was now.
2016: Intel NUC 6I5SYH with i5-6260U CPU
I carried the i7-2700K sleeper system to City Tech to use in my office space. This left me with only a MacBook to use at home. When I saw the Brooklyn Microcenter offer an i5-based NUC for sale, I thought that would fulfill my computing needs at home and be a new kind of miniature computing experience for me. I wrote about my initial setup of it here. I was surprised by its capabilities, but new computing needs led me to build a new computer.
2017: Homebuilt Computer with i7-7700 CPU
I wrote about building, pricing, and benchmarking the first iteration of this i7-7700 based computer here. There were several needs that prompted me to build this machine: I run my own self-hosted instance of World of Warcraft Vanilla and experience some fan-built 3D experiences based in the Star Wars and Star Trek universes. The i5 NUC didn’t have the horsepower for this, so I sold it and built this new computer.
Later, I wanted to try out virtual reality, so when Best Buy had a sale on the Oculus Rift, I purchased a beefier NVIDIA GTX 1060 video card and VR headset (I’ll write about this more soon).
I wasn’t happy with the Oculus Rift in my small apartment space, so I sold it and the MSI Geforce GTX 1060 video card. Then, when Microcenter ran an insane deal on HP’s Mixed Reality headset, I picked it up and an EVGA Geforce GTX 1060 to try VR again (more on this soon).
Long story short: I struck out with VR again, so I sold the 1060 video card and HP mixed reality headset and settled on the built-in video graphics, which is fine for most things on a day-to-day basis.
2020: Pandemic and Upgrades
Then, the pandemic hit in 2020 and I was doing everything with my computer–lecturing, video editing, running online symposia, etc. So, I used my first pandemic Economic Impact Payment to purchase a Powercolor Red Devil AMD RX5700XT video card and an MSI 32″ curved LCD monitor to support my online, video-focused existence at that time.
My small micro ATX case wasn’t an ideal solution for the thermal needs of the RX5700XT video card, so I transplanted the computer into a more spacious Corsair Carbide Series 100R case.
And, I added a cool 5.25″ drawer insert to keep my flash drives and other on-hand media.
Before selling it, I had swapped out the RX5700XT video card for an MSI AMD RX550 and sold the RX5700XT for a profit due to the beginnings of the video card shortage during the cryptomining boom during the pandemic.
2021, early: Lenovo IdeaCentre 5 with Ryzen 4700G
Even though the RX5700XT video card was great, I ran into some cases where video card processing workflows produced workflows that I wasn’t happy with. I didn’t want to change software, so I figured the easier solution was to shift to tried-and-true CPU-focused workflows on a processor with more horsepower than the i7-7700. I opted for the least expensive Ryzen 7 system that I could find–a Lenovo IdeaCentre 5 with Ryzen 4700G. It was easy to modify and make strategic upgrades to for my needs. I wrote about purchasing this system on sale and upgrading its CPU cooler here and then improving its CPU cooling a few months later here.
2021, late: Asus ROG G15DK with Ryzen 7 5800X
While I enjoyed the Lenovo IdeaCentre 5, I began seeing new 3D demos and games released that I was interested in checking out. Lenovo’s big shortcoming was its proprietary power supply. If I had been able to swap it for a more powerful one, I could have got a video card and made the upgrade. Unfortunately, there are tales across the Internet of a mismatched PSU or adapter killing someone’s Lenovo desktop. Therefore, I began looking for a good deal on a complete system with a similar 8 core/16 thread system with a beefy video card. Granted, this was at the height of the video card shortage, so I remained patient and studied the market while waiting to pounce on this deal when I saw it.
The Asus ROG G15DK came with a motherboard similarly speced to an Asus PRIME B550M-K with an AMD Ryzen 7 5800X 8-Core/16-Thread CPU, 16GB RAM, 512GB NVMe boot drive, WiFi (occupying second NVMe slot), and NVIDIA RTX 3070 8GB video card. I swapped the 32GB of RAM from the Lenovo with the 16GB of RAM in the Asus, pulled out the WiFi card to free up the second NVMe slot, and ripped out the disco lighting that was pre-installed in the case.
Then, the next big upgrade that I made was to change out the inadequate 3-heatpipe cooling tower supplied by Asus for a 5-heatpipe Noctua NH-U9S, which I added an additional fan to for a push-pull configuration.
Later, I transplanted the computer into a less flashy case without a glass side panel–the Thermaltake Versa H17.
As DDR4 RAM prices improved, I upgraded from 32GB to 64GB to 128GB. And, as SSD prices plummeted, I upgraded the system drive from a 512GB nvme drive to a 2TB Samsung 970 EVO Plus drive as I had described earlier here.
2023: Current Form with NVIDIA RTX A6000
As I wrote here, the most significant upgrade to my computer–or any computer that I have ever owned for that matter–has been the NVIDIA RTX A6000 video card for AI and machine learning work that I am doing now.
2023: Free i7-6700K Bonus System
In early 2023, someone in my apartment building left this computer in the lobby with a post-it note that said, “Works! No HD.” I didn’t look the gift horse in the mouth! I carried it up the 4 flights of stairs and got to work cleaning it up and checking it out. It had an i7-6700K CPU, 16GB of DDR4-3000 XMP RAM, and EVGA Geforce RTX 2070 8GB video card on a Gigabyte GA-Z170X-Gaming 5 motherboard. I installed a spare SSD and HDD in it, ran memtest86+, and stress tested the still impressive EVGA Geforce RTX 2070 8GB video card. Everything checked out! I sold the RTX 2070 on eBay to help pay for the A6000 video card in my primary system. And, I kept this computer to serve as a media center PC (the built-in graphics work great after making the fix for screen tearing found here). Thank you to whoever gave away such a wonderful machine!
Reflections
As Ovid shows us, things change form and function and purpose. This is very true in my experience of computers. I would have liked to have held on to my computers longer–changing them further through upgrades and reconfigurations. However, I always thought at the time that I had a good reason to do the things that I did–sell one computer to help pay for a new one, or switch from a larger computer to a smaller one (or vice versa). Nevertheless, I can see that sometimes my reasons might have been motivated more by a desire for change, that perhaps using or learning a new computer might move me forward in my work or curiosity or explorations. I don’t think that’s always been the end result, but it might have played a part in the musical chairs of my computing life.
Another thing that I’ve noticed looking at these photos is how sloppy I have been with cable management. Perhaps this is a manifestation of other aspects of my life. A hurry to use rather than perfect the tools of my work, and a worry that too much tweaking when something is operational bodes well for future stability. I admit that I am nervous when working on computers because of problems with some of my earliest computers–some problems brought on by me and other problems instigated by others. The money that I put into my computers is a lot for my meager salary in an extremely high cost of living environment. Every metamorphosing change that I’ve documented in this post cost me in dollars and time and energy–the latter two involving studying, considering, weighing options, etc. You can ask Y, I don’t rush into things that I buy for myself. I have to know that I’m making the best possible decision at that moment after crushing days and weeks of self-doubt and second guessing.
But, as you can see, I’ve had some adventures building, tinkering, and upgrading computers with this post showing the most recent 10 years or so. I’ll work on another post showing some of my earlier computers, but unfortunately, the record is not nearly as complete due to my not taking as many photos back then as I try to do now. When I do, I’ll write about my Amiga 2000HD, 486DX2/66, Powerbook 145B, PowerMacintosh 8500, Blue and White G3, Dual G4, and more. Stay tuned!
I built this 18 x 18 stud diorama of the Millennium Falcon’s main hold that depicts when Han Solo and Chewbacca get to talk with Rey, Finn, and BB-8 in The Force Awakens (2015). I made it sometime before The Last Jedi (2017) premiered. It isn’t 100% accurate due to my wanting the round passage way to create flow for the model (they should be on perpendicular walls). Nevertheless, I fit in important elements of the scene: the seating for the Dejarik table, the Nav computer, the pipes and tanks, Ben Kenobi’s seat while Luke is training, the in-floor repair access, and other equipment seen in the background of the Falcon in the various Star Wars films.
