Tux Machines
Posted by Roy Schestowitz on Jan 28, 2023
=> Open Hardware/Modding Stories | Web Browser Stories
=> ↺ What is Google doing with its open source teams?
=> ↺ LibreOffice’s New App Icons Make a Bold Impression
Yes, LibreOffice has a new set of application icons — and they’re a bold departure from the somewhat “office-y” look most of us are used to.
I’ll state the obvious: icons don’t affect the usability of an app. They do, however, play a psychological role in setting expectations. An app with a low-quality, out-dated icon is more likely to make someone expect a low-quality, out-dated software experience.
Today I hit the “release” button on v1.0.0 of Quamina, a fast open-source pattern-matching library in Go. Gotta keep doing some coding to keep me honest! The purpose of today’s piece is to provide a snapshot status report and record a few technology gripes just to get them off my chest; sharing is caring.
=> ↺ Images considered harmful (sometimes)
The Mastodon dashboards I’ve been developing and describing in this series are backed by a Steampipe plugin that translates SQL queries to Mastodon API calls. Like all Steampipe plugins you can use this one to run those queries in all sorts of ways: from psql or another Postgres CLI (perhaps via cron, perhaps in a CI/CD pipeline); from Metabase or Grafana or any Postgres-compatible BI tool; from Python or JavaScript or any programming language. The Steampipe core is a versatile software component that you can plug into just about any environment.
=> ↺ Open Source Contribution Is… Interesting
I submitted a pull request to an open source project and it didn't get approved.
Obviously I'm making a fork. I don't know what it is about Open Source.
=> ↺ Python Web Conference 2023
The Python Web Conf is the most in-depth Python conference for web developers.
=> ↺ The EU Open Source Policy Summit 2023
The EU Open Source Policy Summit 2023 will explore Europe’s opportunities when leveraging these modes of technological collaboration at scale. Looking at digital policy through this lens, open and collaborative innovation is a source of optimism.
2023 will be the ninth year OpenForum Europe hosts its Open Source policy event right before FOSDEM. While Europe and the EU is our vantage point, this hybrid event welcomes speakers and participants from across the globe.
=> ↺ How to format SQLite BLOB columns as hex
I recently had a small problem: I was using the SQLite CLI and I wanted to see binary data in a BLOB column. When I did a normal SELECT on it, I got unreadable garbage: [...]
=> ↺ Artists file class-action lawsuit against Stability AI, DeviantArt, and Midjourney
I think that the argument in the claim is flawed because it does not accurately represent the technology, so I will attempt to make a very quick explanation of how tools such as Stable Diffusion or Midjourney produce images. What follows is using some excerpts from my forthcoming article, so stay tuned for a lengthier explanation.
I like to classify what happens in AI generative tools in two stages, the input phase and the output phase. The input phase is comprised of the gathering of data to create a dataset, and this is used to train a model. In the case of Stable Diffusion, it uses a dataset called LAION, which has of over 5 billion entries consisting of the pairing of a hyperlink to a web image (not the image itself) with its ALT text description. This dataset then is used to train a model, I will not go into detail into models, suffice it to say that a model is a mathematical representation of a real-world process that is trained using a dataset, this can be used to make predictions or decisions without being explicitly programmed to perform the task. There are various types of models, but Stable Diffusion and Midjourney both use diffusion models (see an explanation in a previous blog post). Long story short, diffusion models take an image, add noise to it, and then put it back together.
The OSI has a parallel undertaking investigating how to improve the tooling that will be used for the license review process and also how to best serve the public in the ways we provide information about Open Source licenses. Although the tooling project and the work of the License Review Working Group are intertwined, the below conclusions of the License Review Working Group are focused on the requirements and policy that will inform the tooling project, but do not include the tooling project itself.
The License Review Working Group was originally scoped to discuss the delisting of licenses, but we did not reach the topic. It is a challenging subject because it means that the OSI first needs to learn who is using the licenses that may be considered for delisting and understand what effect it might have on them if their license undergoes a change in status. We therefore eliminated this topic from the mandate of this working group and recommend that it be taken up by a new working group dedicated to this subject alone.
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