Tony is a Geek

 Thought I'd give it a go and ask it if it could write me some starter code. It did a surprisingly good job from a SIMPLE prompt as a starter and then I understood what it was doing and then took it a stage further, it did indeed get a couple of things incorrect, I hit a bug with the rtlsdr USB driver memory limit and then there was a deadlocking that occurred with the scan and logging, but once over that it seemed to do a pretty good job. All I need this article to do is share the following lines so I can copy & paste them on a different machine: RTL-SDR Frequency Scanner - Build & Test Guide Required External Libraries 1. SoapySDR Core SDR library that provides unified API for software-defined radios. 2. SoapyRTLSDR RTL-SDR driver module for SoapySDR. 3. librtlsdr RTL-SDR USB device driver library. Installation on Ubuntu 24/25 Step 1: Update System sudo apt update sudo apt upgrade -y Step 2: Install Dependencies sudo apt install -y \ build-essential \ cmake \ ...

  Not heard of Piper before, but have built the rest before - nice setup:

Those of us that remember the world before GitHub (it only came onto the internet scene in 2008), yes, it was like a breathe of fresh air at the time and it really did help to cement having a "free" hosted environment accessible from anywhere where you could store your code, share the code, manage the code and collaborate with others with your code.  It was refreshing.  Before then you had tooling, like CVS that, if you were lucky enough, you could install locally inside a company and have 1001 variant modifications that meant no CVS was the same as another, so headaches ensured.  I'm sure there were other tools, I seem to recall doing stuff with Rational Tooling too. ( We'll come back to these people later on! ) So what happened?  Well, as with all good things, they attract attention.  The original creators also tail off & then look for different and other fun things to do and well, usually somebody in a mega-corp then decides they want to buy the system / ...

 ever wondered what goes in INSIDE a Large Language Model (LLM)? Back in the "day" LOL okay, a couple of years ago, this was mapped out and us early adopters had this worked out mostly on paper - but this is so cool to see / zoom in & out and trace through what is happening at each step of the way through an LLM to get from initial prompt through to output: https://bbycroft.net/llm If you press [SPACE] you can step through in a guided tour: This is really useful & potentially helpful for people to understand what happens behind the Wizard of Oz curtain

Well, why not?! This seems to be the current (okay, it's been out for a while) trend, where non-coding people have "an idea" and then just want to describe that to a GPT and then get that to autom-magically create an application for apple / android & web.  Then sit back and rack in the money.  Sounds idyllic & all very cyberpunk.  But, how close is the reality to the expectation? I thought I'd give it an investigation look using RORK.com and BASE44.com Here is what I found out from an initial attempt at just using a prompt description. Now, you may (or may not) notice that I started this at 09:41, it seemed to make a good and quick start, however, I think either I picked a busy time or it was a bit more of a complex tasks than I was led to believe. I got a little bored and started to click around to see what the "logs" were saying: I genuinely thought I had crashed it. I thought I'd have a nosy around at the code it generated. Although it is Reac...