Agreeing By Disagreeing

While we were working on the podcast this week, Al Williams and I got into a debate about the utility of logic analyzers. (It’s Hackaday, after all.) He said they’re almost useless these days, and I maintained that they’re more useful than ever. When we got down to it, however, we were actually completely in agreement – it turns out that when we said “logic analyzer” we each had different machines, and use cases, in mind.

Al has a serious engineering background and a long career in his pocket. When he says “logic analyzer”, he’s thinking of a beast with a million probes that you could hook up to each and every data and address line in what would now be called a “retrocomputer”, giving you this god-like perspective on the entire system state. (Sounds yummy!) But now that modern CPUs have 64-bits, everything’s high-speed serial, and they’re all deeply integrated on the same chip anyway, such a monster machine is nearly useless.

Meanwhile, I’m a self-taught hacker type. When I say “logic analyzer”, I’m thinking maybe 8 or 16 signals, and I’m thinking of debugging the communications between a microcontroller, an IMU, or maybe a QSPI flash chip. Heck, sometimes I’ll even break out a couple pins on the micro for state. And with the proliferation of easy and cheap modules, plus the need to debug and reverse commodity electronics, these logic analyzers have never been more useful.

So in the end, it was a simple misunderstanding – a result of our different backgrounds. His logic analyzers were extinct or out of my price range, and totally off my radar. And he thinks of my logic analyzer as a “simple serial analyzer”. (Ouch! But since when are 8 signals “serial”?)

And in the end, we both absolutely agreed on the fact that great open-source software has made the modern logic analyzers as useful as they are, and the lack thereof is also partially responsible for the demise of the old beasts. Well, that and he needs a lab cart then to carry around what I can slip in my pocket today. Take that!

To Give Is Better Than To Receive

Better to give a talk at a hacker event, that is. Or in your hackerspace, or even just to a bunch of fellow nerds whenever you can. When you give the talk, don’t be afraid to make it too “easy” to understand. Making a tough topic comprehensible is often the sign that you really understand it, after all, and it’s also a fantastic service to the audience. And also don’t be afraid that your talk isn’t “hard core” enough, because with a diverse enough crowd, there will absolutely be folks for whom it’s still entirely new, and they’ll be thankful.

These were the conclusions I got from talking to a whole range of people at Chaos Communication Camp the weekend before last, and it’s one of the great opportunities when you go to an event like this. At Camp, there were a number of simultaneous stages, and with so many talks that new ones are still being released. That meant that everyone had their chance to say their bit, and many many did.

And that’s great. Because it’s obvious that getting the work done, or diving deep into a particular topic, is part of the hacker experience, but it’s also equally important to share what you’ve gained with the rest of the community. The principle of spreading the knowledge is a cornerstone of our culture, and getting people up to talk about what they’ve learned is the manifestation of this cultural value. If you know something, say something!

Of course, when you’re not at a conference, you could be writing up your hacks and sending them in to the tips line (hint, hint!). That’ll work too.

How Do They Do That?

Last week’s Chaos Communication Camp is kinda a big deal: 6,000 hackers all out in a field all need power, food, drink, networking, and of course, sewage in the middle of nowhere. Oh yeah, plus video services on multiple simultaneous stages, custom phone infrastructure, a postal service, and even a diesel train. How is that even possible to run with only volunteers? How do they even know how to run something this scale?

My wife asked me this question while we were driving up to Berlin, and the answer is of course the same as it is to “Excuse me, can you tell me how to get to Carnegie Hall?” Practice.

But it’s not just practice. It’s also passing down the lessons learned to the next generation, making procedures that are not 100% dependent on the people doing the jobs, but can be passed on to the next volunteer willing to pick up the torch.

And then I was interviewing [Jens Ohlig] and [Mitch Altman] about the early days of the second wave hackerspaces in America for the podcast. (Some great interviews – go check it out!) The central story there is essentially the same: the critical missing ingredient that lead to the blossoming of US hackerspaces was simply a set of instructions and design principles – drawing on the experience of established hackerspaces.

Sharing information is a fundamental cornerstone of the hacker ethic, and it gives the next hacker a leg up. Contributes to the global hive mind. And it makes things possible that would otherwise seem impossible. Pushing the hacker state-of-the-art is what Hackaday is all about, and we’re used to thinking of it in terms of a particular microcontroller library, but seeing how the same sharing makes impossible logistics possible was inspirational. Don’t be afraid to start small and iterate – and take good notes.

Privacy And Photography, We Need To Talk

One of the fun aspects of our global community is that there are plenty of events at which we can meet up, hang out, and do cool stuff together. They may be in a Las Vegas convention center, a slightly muddy field in England, or a bar in Berlin, but those of us with a consuming interest in technology and making things have a habit of finding each other. Our events all have their own cultures which make each one slightly different from others.

The German events, for example, seem very political to my eyes — with earnest blue-haired young women seeking to make their mark as activists, while the British ones are a little more laid-back and full of middle-aged engineers seeking the bar. There are some cultural things which go beyond the superficial though and extend into the way the events are run, and it’s one of these which I think it’s time we had a chat about.

Our Community Takes Privacy Seriously

The relevant section about photography in the SHA2017 code of conduct.
The relevant section about photography in the SHA2017 code of conduct.

The hacker community differs from the general public in many ways, one of which is that we tend to have a much greater understanding of privacy in the online age. The Average Joe will happily sign up to the latest social media craze without a care in the world, while we quickly identify it as a huge data slurp in which the end user is the product rather than the customer.

The work of privacy activists in our community in spotting privacy overreaches may pass unnoticed by outsiders, but over the years it’s scored some big wins that benefit everyone. Part of this interest in privacy appears at our events; it’s very much not done to take a photograph of someone at a hacker event without their consent. This will usually be clearly stated in the code of conduct, and thus if taking a picture featuring someone it’s imperative to make damn sure they’re OK with it. Continue reading “Privacy And Photography, We Need To Talk”

Blinded With Science

So the room-temperature superconductor was a super disappointment, but even though the claims didn’t stand up in the end, the even better news is that real science was done. A paper making extraordinary claims came out, the procedure to make LK-99 was followed in multiple labs around the world, and then it was tested. It didn’t turn out to conduct particularly well at all. After a couple weeks of global superconductor frenzy, everything is back to normal again.

What the heck happened? First of all, the paper itself made extravagant claims about a holy-grail kind of material. There was a very tantalizing image of a black pellet floating in mid air, which certainly seems like magic, even though it’s probably only run-of-the-mill ferromagnetism in the end. But it made for a great photo-op in a news-starved August, and the then-still-Twitterverse took to it by storm. And then the news outlets piled on the hype fest.

If you’re feeling duped by the whole turn of events, you’re not alone. But the warning signs were there from the beginning, if you took the time to look. For me, it was the closing line of the paper: “We believe that our new development will be a brand-new historical event that opens a new era for humankind.”

That’s not the kind of healthy skepticism and cautious conclusion that real science runs best on. Reading the paper, I had almost no understanding of the underlying materials science, but I knew enough about human nature to suspect that the authors had rushed the paper out the door without sufficient scrutiny.

How can we keep from being fooled again? Carl Sagan’s maxim that “extraordinary claims require extraordinary evidence” is a good start. To that, I would add that science moves slowly, and that extraordinary evidence can only accumulate over time. So when you see hype science, simply wait to draw any conclusions. If it is the dawn of a new era, you’ll have a lot of time to figure out what room-temperature superconductivity means to you in the rosy future. And if it’s just a flash in the pan, you won’t have gotten your hopes up.

A Little Bit Of Science History Repeating Itself: Boyle’s List

In a recent blog post, [Benjamin Breen] makes an interesting case that 2023 might go down in history as the start of a scientific revolution, and that’s even if LK-99 turns out to be a dud. He points to several biomedical, quantum computing, and nuclear fusion news items this year as proof.

However, we aren’t as convinced that these things are here to stay. Sure, LK-99 was debunked pretty quickly, but we swim in press releases about new battery technologies, and new computer advances that we never hear about again. He does mention that we aren’t alone in thinking that as [Tyler Cowen] coined the phrase “Great Stagnation” to refer to the decline in disruptive tech since 1945. Still, [Benjamin] argues that people never know when they live through a scientific revolution and that the rate of science isn’t as important as the impact of it.

Continue reading “A Little Bit Of Science History Repeating Itself: Boyle’s List”

The Right Benchmark For GPT

Dan Maloney wanted to design a part for 3D printing. OpenSCAD is a coding language for generating 3D objects. ChatGPT can write code. What could possibly go wrong? You should go read his article because it’s enlightening and hilarious, but the punchline is that it ran afoul of syntax errors, but also gave him enough of a foothold that he could teach himself enough OpenSCAD to get the project done anyway. As with many people who have asked the AI to create some code, Dan finds that it’s not as good as asking someone who knows what they’re doing, but that it’s also better than nothing.

And this is where I start grumbling. When you type your desires into the word-follower machine, your alternative isn’t nothing. Your alternative is to fire up a search engine instead and type “openscad tutorial”. That, for nearly any human endeavor, will get you a few good guides, written by humans who are probably expert in the subject in question, and which are aimed at teaching you the thing that you want to learn. It doesn’t get better than that. You’ll be up and running with your design in no time.

Indeed, if you think about the relevant source material that the LLM was trained on, it’s exactly these tutorials. It can’t possibly do better than the best of them, although the resulting average tutorial might be better than the worst you’ll find. (Some have speculated on what happens when the entire Internet is filled with these generated texts – what will future AIs learn from?)

In Dan’s case, though, he didn’t necessarily want to learn OpenSCAD – he just wanted the latch designed. But in the end, he had to learn enough OpenSCAD to get the AI code compiling without error. He spent an hour learning OpenSCAD and now he’s good to go on his next project too.

So the next time you hear someone say that they got an answer back from a large language model that wasn’t perfect, but it was “better than nothing”, think critically if “nothing” is really the right benchmark.

Do you really want to learn nothing? Do you really have no resources to get started with? I would claim that we have the most amazing set of tutorial resources the world has ever known at our fingertips. Compared to the ability to teach millions of humans to achieve their own goals, that makes the LLM party tricks look kinda weak, in my opinion.