linguae

This reminds me of how I learned about Zipf's law. 19 years ago, I spent the summer after my sophomore year in a research lab at UC Santa Cruz as part of an NSF-funded summer research program for undergrads. My project that summer was to investigate index design for the Ceph distributed file system in order to enable faster file search. This was a hot topic at the time, especially with Spotlight being introduced to Mac OS X Tiger, and we wanted to see how to enable similar functionality for a distributed file system. I learned about Zipf's law, which states that there is a power law distribution of word frequencies in many natural languages. I remember downloading the Project Gutenberg corpus and writing a Python script where I stemmed the words and computed the frequencies of the stemmed words. The resulting distribution confirmed Zipf's law.

I would love a tablet running macOS, which I prefer over Windows and desktop Linux. I have a Microsoft Surface Pro 7. It performed fine under Windows 10, though performance suffered when upgrading to Windows 11. The Surface Pro is a nice piece of hardware, but I wish it had macOS instead of Windows. The iPad Pro definitely has enough processing power to run macOS, but it runs iPadOS, which is too restrictive for me as a developer.

If Apple went through the effort making macOS touchscreen-ready for this new MacBook Pro, then perhaps we’ll see a tablet with macOS one day. I’d buy an iPad Pro with macOS in a heartbeat.

On the Windows side, Windows 2000 and XP/Vista/7’s Classic mode, though Aero was quite nice. I’m not a fan of the interfaces from 8 onward, and I didn’t like Luna in XP.

On the Mac side, it’s a toss up between the platinum interface of Mac OS 8/9 and Mac OS X Tiger. With that said, I have a work-issued MacBook Pro running Golden Gate as my daily driver, and Liquid Glass is alright. It’s not what I’d prefer if I had a choice, but it’s not a dramatic departure from previous versions of macOS. A Cheetah or Puma Mac OS X user should be able to navigate Golden Gate with ease, mostly.

I love this quote! When I taught programming language paradigms at San Jose State as an adjunct, I introduced this quote as a motivating factor for learning different ways of programming, particularly introducing functional programming, logic programming, Smalltalk, and the Common Lisp Object System to senior-year students who coded mostly in Java, Python, and C (though this was during the COVID pandemic, right before the advent of vibe coding).

Yup, just like during the bad old days of Internet Explorer's dominance. I remember encountering websites that only worked on the Windows version of Internet Explorer as late as 2006. We had a nice time in the late 2000s and early 2010s when web developers coded against standards instead of against the market-leading web browser. There was competition between Firefox, Opera, Safari, and a revitalized Internet Explorer. I don't remember IE 7 and later being that bad, though by then I had switched to Firefox on Linux/Windows and Safari on Macs.

Then came an upstart web browser from Google named Chrome....and now we're back to the bad old days of web developers coding to the dominant web browser again.

In many ways NeXTSTEP can be thought of as a “pragmatic Smalltalk environment” that traded some of Smalltalk’s dynamism for improved compatibility with the Unix ecosystem. Recall that NeXT’s original target market was higher education, which even in the 1980s started relying on Unix. This was the era of the Unix workstation, and NeXT can be considered a competitor to Sun, SGI, HP, DEC, and other Unix workstation vendors. NeXT’s differentiator was its Smalltalk-inspired object-oriented environment, built on Objective-C.

I wonder, though, what a pure Smalltalk workstation would’ve looked like, and what hardware would’ve been necessary to make it fast. After all, the late 80s were the era of Lisp machines, though Lisp machines were much more expensive than NeXT cubes ever were. If I recall correctly, Smalltalk on the Xerox Alto was slow, but David Patterson (of RISC fame) had a PhD student who worked on a performant version of the Smalltalk VM, and some of that work went to a spiritual successor named Self, which heavily influenced the design of the Java VM. I remember Java feeling slow in the mid-1990s, but that might be due to bad memories of Java applets rather than a fundamental problem with Java VMs.

This is sad news. I was born in 1989 and thus I don’t remember Cringely’s articles, but I remember watching Triumph of the Nerds in the mid-2000s. I love that documentary; it’s a nice capture of the early days of personal computing and of Silicon Valley culture of the era. I wish there were a follow-up that covered the 2000s and beyond, particularly the rise of social media, the gig economy (Uber, Lyft, AirBNB), cloud computing, big data, cryptocurrency, and generative AI.

Amazingly, this doesn’t look like slop to me, unlike the slop articles and images I’m flooded with on the Web these days. The world of Idiocracy actually had some taste, unlike the timeline we’re on today.

I had the same experience; grad school is the best preparation for grad school. I had wonderful experiences participating in NSF Research Experiences for Undergraduate projects during two of my summers as an undergrad, and I also had a wonderful eight-month internship in a research lab at a major Japanese IT company, but grad school was a different beast, even though I was a grad student at the place I did my NSF REUs. The internships felt like the “demo version” of the real thing.

Come to think of it, I had similar whiplash in industry of full-time jobs being far more stressful than my internships, which I now realize were more-or-less “demo versions.”

To make a long story short, after grad school and working as a researcher in industry for nearly a decade before becoming a professor at a community college (where the emphasis is teaching), I learned that I love doing research as a hobby but not as a career, where there are many pressures.

I call it the “it’s not delivery—it’s DiGiorno” construct. I generally tune out when I see this construct, which is so prevalent on LinkedIn these days, which is inundated with clichéd writing.

Unfortunately the price hikes are affecting the entire industry, and it's not just high-end rigs for gaming and local LLMs. Game consoles and even the Raspberry Pi have gone up in price. In fact, Apple was one of the last holdouts; it didn't start raising prices until June.

I paid $96 for 32 GB of DDR5 RAM for my Framework 13 laptop back in December 2023. When I checked a few months ago, the same RAM cost around $400; I don't know what prices are like now.

I agree. I would switch to an open source spiritual successor to even Tiger in a heartbeat if it were available.

The difficult part is replicating the ecosystem of applications. From a technological standpoint I would prefer a modern Linux distribution with KDE or Cinnamon over using 2005-era Mac OS X Tiger, though I’d gladly use a version of Tiger that was retrofitted with a modern Darwin core, modern libraries for security purposes, and an up-to-date web browser. However, Linux does not have Microsoft Office, the Adobe Creative Suite, Preview.app, Keynote, Dictionary.app, and other pleasant Mac apps. The FOSS alternatives are not as polished. Even venerable Office 2008 for Mac feels nicer than LibreOffice, and it’s compatible with the XML-based Office formats.

I guess for now I could run Tiger in an emulator, though admittedly current operating systems serve my needs, even if I prefer the polish of Tiger and Snow Leopard. I get really good performance running PowerPC Tiger inside QEMU on my base M4 Mac Mini and on my Ryzen 9 3900 desktop, definitely not as snappy as running Tiger on actual contemporary PowerPC hardware, but fast enough to actually be productive.

This summer I’ve been investigating agentic coding with local LLMs, and while I’m far from an expert, one thought that has been on my mind is leveraging techniques from “old-school” AI such as heuristic search to guide agents when it comes to planning. The use of Datalog in this article resonates with me, since logic programming was a major part of old-fashioned symbolic AI. I’m very curious about this combination of “old-school” AI and LLMs.

I'd love for Apple to bring back the Mac Pro, but Apple hasn't had an affordable Mac Pro tower since the 2012 model. Apple got rid of the tower in 2013 in favor of the "trash can" model. When the trash can languished for years without updates due to limitations with its design, Apple brought back the tower Mac Pro in 2019, but at a dramatically higher entry MSRP, which priced out many users of tower and trash can Mac Pros (I have a "trash can" and was very disappointed by the 2019 Mac Pro's entry MSRP). The introduction of the Mac Studio revealed a large price gap between similarly-specified Mac Studio and Mac Pro models. Given the lack of expandable RAM in Apple Silicon Mac Pro models, and also given the lack of support for NVIDIA GPUs in macOS, there weren't a lot of customers for Apple Silicon Mac Pros when the Mac Studio was available at a lower price, and thus the Mac Pro got discontinued.

In many ways, the Mac Studio is the spiritual successor to the trash can Mac Pro. Apple Silicon's architecture solved the thermal problems that limited the trash can Mac Pro.