tutorial

Late last year, OpenAI announced Whisper, a new speech-to-text language model that is extremely accurate in translating many spoken languages into text. The whisper repository contains instructions for installation and use.

tl;dr:

# Install whisper and its dependencies.
pip3 install git+https://github.com/openai/whisper.git 

# (When needed) Update whisper.
pip3 install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git

# Make sure ffmpeg is installed.
brew install ffmpeg

# Translate speech into text.
whisper my_audio_file.mp3 --language English

One thing I do quite regularly for my YouTube channel is extract the audio track, convert it to text using an online tool (I used to use Welder until they were bought out by Veed), and then hand-edit the file to fix references to product names, people, etc.

Recently I was doing some benchmarking on my Ubuntu 22.04 PC, and as part of that benchmarking, I tried setting the CPU performance profile to performance. In the old days, this was not an issue, but it seems that modern Ubuntu only 'knows' about balanced and power-saver. Apparently performance is forbidden these days!

$ powerprofilesctl list
* balanced:
    Driver:     placeholder

  power-saver:
    Driver:     placeholder

The problem was, I had set the profile to performance:

$ powerprofilesctl set performance

But suddenly the 'Settings' GUI app would no longer open (at least not after I had opened it and clicked into the 'power' section). A reboot didn't work, and even reinstalling control center (sudo apt-get install --reinstall gnome-control-center) didn't help!

When I tried opening the settings GUI from the command line, I got the following critical error:

According to AI, this is me.

Or at least, what I look like if I deliver the prompt Jeff Geerling, realistic, photograph, sharp focus to Stable Diffusion, a machine learning, text-to-image model. But if you take that same prompt and paste it into the Stable Diffusion Demo, you'll get a different result.

I use yt-dlp to download videos off YouTube quite frequently. I'll use the videos as reference, and I often use it to grab the VOD for one of my livestreams, since there's no simpler way (I'm not going to dig through the bowel's of YouTube's UI to try to download one of my own videos...).

But I also can't handle the default .webm videos in all my video editing tools natively, and transcoding is annoying. So I've settled on the following yt-dlp command to first try to pull a native MP4 version off YouTube, and failing that, transcode to MP4 immediately after downloading:

yt-dlp -S res,ext:mp4:m4a --recode mp4 https://www.youtube.com/watch?v=dQw4w9WgXcQ

And if you weren't aware, yt-dlp does an excellent job pulling video files from other sites as well, should the need arise.

For many packages, like Elasticsearch, Docker, or Jenkins, you need to install a trusted GPG key on your system before you can install from the official package repository.

Traditionally, you'd run a command like:

wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add -

But if you do that in modern versions of Debian or Ubuntu, you get the following warning:

Warning: apt-key is deprecated. Manage keyring files in trusted.gpg.d instead (see apt-key(8)).

This way of adding apt keys still works for now (in mid-2022), but will stop working in the next major releases of Ubuntu and Debian (and derivatives). So it's better to stop the usage now. In Ansible, you would typically use the ansible.builtin.apt_key module, but even that module has the following deprecation warning:

For years, Mac users have dealt with slow filesystem performance for Docker volumes when using Docker for Mac. This is because the virtualized filesystem, which used osxfs for a while and will soon be upgraded to use VirtioFS.

But if you need to do large operations on huge codebases inside a shared directory, even using NFS to share from the Mac into Docker is a lot slower than running a native Docker volume or just using files inside the container's own filesystem.

After upgrading my main workstation to a Mac Studio, I decided to break tradition.

Usually, I sell off my old workstation to offset the cost of the new one. But just last week, Asahi Linux announced their first alpha release.

If you haven't heard of Asahi, it's a Linux distribution based on Arch Linux that aims to bring a polished Linux experience on Apple Silicon Macs (all the current M1 Macs, and any new Apple Silicon Macs that come in the future).

Today I needed to play back an MP3 or WAV file through a USB audio device on a Raspberry Pi, in a Python script. "Should be easy!" I thought!

Well, a couple hours later I decided to write this blog post to document the easiest way to do it, since I had to take quite a journey to get to the point where sound actually plays through the USB audio output.

The problem is most guides, like this simple one from Raspberry Pi's project site, assume two things:

This is a simple guide, part of a series I'll call 'How-To Guide Without Ads'. In it, I'm going to document how I set up bcache on a Raspberry Pi, so I could use an SSD as a cache in front of a RAID array.

Getting bcache

bcache is sometimes used on Linux devices to allow a more efficient SSD cache to run in front of a single or multiple slower hard drives—typically in a storage array.

In my case, I have three SATA hard drives: /dev/sda, /dev/sdb, and /dev/sdc. And I have one NVMe SSD: /dev/nvme0n1.

I created a RAID5 array with mdadm for the three hard drives, and had the raid device /dev/md0.

I then installed bcache-tools:

$ sudo apt-get install bcache-tools

And used make-bcache to create the backing and cache devices:

Recently I built the Seaberry, a Raspberry Pi Compute Module 4 mini ITX motherboard into a PC case (video coming soon...), and got the case power button, power LED, and activity LED all wired up to the Pi:

I used the GPIO and 14-pin header present on the Seaberry (which conveniently are identical to the headers on the official CM4 IO Board), and wound up with a fully functionality power button, power LED, and activity LED!

Here's how I did it:

Power button

To get the power button working, you need to connect the case's front panel 'power switch' connector to pins 12 and 14 (GLOBAL_EN and GND), as seen in the top middle of the above picture.