Hackaday Podcast Episode 317: Quantum Diamonds, Citizen Science, And Cobol To AI

When Hackaday editors Elliot Williams and Al Williams need a break from writing posts, they hop on the podcast and talk about their favorite stories of the past week. Want to know what they were talking about? Listen in below and find out!

In an unusual twist, a listener sent in the sound for this week’s What’s This Sound competition, so it turns out Elliot and Al were both stumped for a change. See if you can do better, and you might just score a Hackaday Podcast T-shirt.

On the hacking front, the guys talked about what they hope to see as entries in the pet hacking contest, quantum diamonds (no kidding), spectrometers, and several science projects.

There was talk of a tiny robot, a space mouse—the computer kind, not a flying rodent—and even an old-fashioned photophone that let Alexander Graham Bell use the sun like a string on a paper cup telephone.

Things really heat up at the end, when there is talk about computer programming ranging from COBOL to Vibe programming. In case you’ve missed it, vibe coding is basically delegating your work to the AI, but do you really want to? Maybe, if your job is to convert all that old COBOL code.

Want to read along? The links are below. Be sure to leave your robot plans, COBOL war stories, and AI-generated Vibe limerics in the comments!

As always, the human-generated Hackaday Podcast is available as a DRM-free MP3 download.

Episode 317 Show Notes:

News:

What’s that Sound?

Interesting Hacks of the Week:

Quick Hacks:

Can’t-Miss Articles:

One thought on “Hackaday Podcast Episode 317: Quantum Diamonds, Citizen Science, And Cobol To AI

  1. Nice episode – as always. But this time, I must protest – yep I do. AI (pick your favorite) not good for much programming as implied by your discussion is far from the truth. I have my own little company developing electronic products which involves many hats; hardware, software, firmware, some mechanics, stress testing and more. One of the hardest hurdles to overcome is the start of a new project/product that involves a smorgasbord of new MCU, chips, libraries, languages etc. With AI this has become TREMENDOUSLY better.

    At the start of a project, I can “discuss” with the AI how best to set it up, give it some feature parameters of the MVP and ask what the commonly accepted methods/frameworks are. Then diving in details say setting up freeRTOS on a new MCU, not having had to mess with freeRTOS for a while and happily forgotten all the boring setup stuff, AI helps me out big time. I have a feature set and a preferred chipset and ask it if this could meet my (take your pick) power budget, size, heat budget, process time, you name it. The same applies for software, I only develop iOS and macOS and I could not possibly know everything about every library. I ask it to teach me, even physics, or electronics of elements I know little about.

    OK, I seldom accept the answers on face value and often argue and poke (or try to) holes in the story. And yes it can send me for loops. But with AI I have gotten MUCH more effective, by factors.

    Al, you need to get more creative how you approach AI. You can hold up your age as a “don’t have to” but, I am not very far behind you and have been with electronics for decades and this AI thing has got me zipping!

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