Programming Language Wars are Dumb
Joe's Nerdy Rants #42 - Weekend reads and other stuff
I just returned from Spain, where I visited local friends and gave a workshop with Matt Housley at J on the Beach in Magala. It was an enjoyable conference with a beautiful Mediterranean beach twist.
While standing in line to get my swag bag, a guy asked about my workshop and the tools/language it used. I mentioned Python was used in the workshop, and he said, “Python is too slow.” When people give opinions about programming language flaws, my brain shuts off. So, my only reply was, “Slow…for what use case?”
A can of worms opened (this is why I disengage from these types of discussions). He droned about how Python is a bad programming language because it is easy to write. Yes, easy to write. Huh. I’ve been programming for a long time, and the correlation between code being easy to write and performance is something I’ve never encountered. He claimed that easy-to-program languages mean the software produced from the language has a very short shelf life. His counterexample was COBOL, which is harder to write and still exists in many systems today. Never mind that ripping out COBOL is a horrendous task, and these systems are often brittle and hard to maintain.
Is Python slow? Perhaps, but it depends on what you compare it to and the use case you’re considering. Python wouldn’t be my first choice for bare metal systems programming. But it’s an excellent choice for a lot of things. Slow is relative to the use case, so making a universal claim about speed is a red herring. It’s like saying a Toyota Corolla is a poor choice in cars because it’s slower than a McLaren race car. The Toyota will work fine if you commute from point A to point B on public streets. The argument didn’t make much sense, but it got me thinking about programming language wars, which tend to resurface randomly in my career and travels.
I often quip Python is the “second best language at everything.” It’s not the best language for any particular use case, but it’s super widespread and currently the most popular programming language in the world. Python worked fine at a startup I joined, where the product was written in Django. That startup scaled to a 9 figure exit, so I guess you can say Python “worked.” I’ve seen similar success stories with Ruby on Rails, Java, JavaScript, Go, and many more languages and frameworks. Suppose you’re lucky enough to scale past the limits of Ruby on Rails or Django (Instagram tweaked Django and Python to their needs). Congrats! That’s a great problem to have.
Programming language wars are as old as the dawn of computing. Here’s why language wars bore me to no end. They’re unproductive. In the end, the only thing that matters is whether people are happy using what you created, and ideally paying for it. The choice of programming language is almost always irrelevant to an organization's commercial success. End-users don’t likely care about your programming language choice. You need to upskill your business sense if you’re trying to differentiate your product or service based on the underlying programming language or tech stack. Cool if you’re trying to win brownie points with other nerds. Debate about your tech stack all day long. The rest of the world doesn’t care. Pick the tools that work for your situation.
Hope you have a fun weekend!
Thanks,
Joe
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Cool Weekend Reads
Meet AdVon, the AI-Powered Content Monster Infecting the Media Industry (Futurism)
The enshitification of the Internet is well underway. Such a crazy story…
AI-Voiced Audiobooks Top 40,000 Titles on Audible (Bloomberg)
“Over 40,000 books in Audible are marked as having been created with it, and, in posts online, authors praise the fact that they have saved hundreds or thousands of dollars per title on narration costs. One author, Hassan Osman of the Writer on the Side blog said turning one of his books into an audiobook took only 52 minutes.”
Voiceovers and narration can be tedious AF. I’m doing this right now for a project. On one hand, I think this is awesome and will save a ton of time with voiceovers. On the other hand, there are situations where I’d love to be able to narrate my books. Like that time I discovered Fundamentals of Data Engineeering’s audiobook while browsing Amazon. My co-author and I weren’t informed about the audiobook release, and despite everyone asking us to read it, we were never offered the opportunity by our publisher. That was a gut punch.
AI Copilots Are Changing How Coding Is Taught (IEEE Spectrum)
“Given that large language models are evolving rapidly, we are still learning how to do this.”
I constantly chat with instructors and professors about how LLMs are used in education, specifically in teaching technical skills like coding. There’s no universal answer, and we’re still far from consensus or best practices.
AI-powered fighter jet takes Air Force leader for a historic ride (AP News)
Similar to how the machine gun changed the nature of warfare in WW1, and bombers and atomic bombs changed it in WW2, I think AI will be the big game changer in the next big conflict. Hope that’s a ways off… Speaking of which, if you want to listen to a very scary podcast about AI, check out my interview with Roman Yampolskiy.
Machine Unlearning in 2024 (Ken Ziyu Liu, Stanford Computer Science)
“Machine unlearning can be broadly described as removing the influences of training data from a trained model. At its core, unlearning on a target model seeks to produce an unlearned model that is equivalent to—or at least “behaves like”—a retrained model that is trained on the same data of target model, minus the information to be unlearned.”
This is an interesting approach that will also have unintended consequences.
Introducing the Model Spec (OpenAI)
“We’re sharing a first draft of the Model Spec(opens in a new window), a new document that specifies our approach to shaping desired model behavior and how we evaluate tradeoffs when conflicts arise. It brings together documentation used at OpenAI today, our experience and ongoing research in designing model behavior, and more recent work, including inputs from domain experts, that guides the development of future models. It is not exhaustive, and we expect it to change over time.”
Other cool reads…
How To Price A Data Asset (Pivotal)
The One Where I Lie To The CTO (Grumpy Old Dev)
Turning AirPods into a Fitness Tracker to Fight Cancer (Richard Das)
GitHub - TimesFM (Time Series Foundation Model) (Google Research)
Novel attack against virtually all VPN apps neuters their entire purpose (Ars Technica)
New Content, Events, and Upcoming Stuff
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The Joe Reis Show
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Roman Yampolskiy - AI Safety & The Dangers of General Super Intelligence (Spotify)
5 Minute Friday - 5 Minute Friday - It's Fast Enough, or Why Programming Language Wars are Dumb (Spotify)
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Joe Reis