The promise was that WPF would use hardware-accelerated libraries such as DirectWrite to put text on the screen even faster than GDI+ (using the CPU) could do. The reality turned out to be quite different: multiple layers of abstraction and just plain inefficient WPF code [1] meant that users needed powerful CPUs and GPUs just to get reasonable performance.
I first encountered this in Bjarne Stroustrup's 2000 book, _The C++ Programming Language_. As he notes in the introductory material:
> In code examples, a proportional-width font is used for identifiers. … At first glance, this presentation style will seem “unnatural” to programmers accustomed to seeing code in constant-width fonts. However, proportional-width fonts are generally regarded as better than constant-width fonts for presentation of text. Using a proportional-width font also allows me to present code with fewer illogical line breaks.
I switched years ago and would never go back to monospace.
Why can I not authenticate into Google Antigravity?
Google Antigravity is currently available for non-Workspace personal Google accounts in approved geographies. Please try using an @gmail.com email address if having challenges with Workspace Google accounts (even if used for personal purposes).
Completely agree, and I've started writing more Roslyn analyzers to provide quick feedback to the LLM (assuming you're using it in something like VS Code that exposes the `problems` tool to the model).
I also want C# semantics even more closely integrated with the LLM. I'm imagining a stronger version of Structured Model Outputs that knows all the valid tokens that could be generated following a "." (including instance methods, extension properties, etc.) and prevents invalid code from even being generated in the first place, rather than needing a roundtrip through a Roslyn analyzer or the compiler to feed more text back to the model. (Perhaps there's some leeway to allow calls to not-yet-written methods to be generated.) Or maybe this idea is just a crutch I'm inventing for current frontier models and future models will be smart enough that they don't need it?
Storing issues in a local SQLite database reminded me of Fossil SCM, which natively supports "tickets" as a source code artifact (and which uses a SQLite database under the hood): https://fossil-scm.org/home/doc/trunk/www/bugtheory.wiki.
We self-host GitHub using GitHub Enterprise Server. It is a mature product that requires next-to-no maintenance and is remarkably stable. (We did have a period of downtime caused by running it on an underprovisioned VM for our needs, but since resolving that it hasn't had problems.)
Of course we have a small and mostly unchanging number of users, don't have to deal with DDoS attacks, and can schedule the fairly-infrequent updates during maintenance windows that are convenient for us (since we don't need 100% availability outside of US working hours).
I don't have the metrics in front of me, but I would say we've easily exceeded github.com's uptime in the last 12 months.
> [Dr. Jonathan] Anomaly is a well-known figure in a growing transatlantic movement that promotes development of genetic selection and enhancement tools.
There's an ongoing issue with ranking in Google Search that's affecting a large number of search results. We've identified the root cause and this issue is unrelated to the ongoing core update rollout.
Are you sure? The article says "cite this as Yan et al. (May 2024)" and published-time in the metadata is 2024-05-12.
Weird: I just refreshed the page and it now redirects to a different domain (than the originally-submitted URL) and has a date of June 8, 2023. It still cites articles and blog posts from 2024, though.
The Kenya joke explanation is fun, but probably not the real reason. ChatGPT (GPT-3.5) also fails for "L":
User: Did you know that there is no country in Africa that starts with the letter "l"?
ChatGPT: Yes, that's correct! As of my last knowledge update in September 2021, there is no sovereign country in Africa that starts with the letter "L." If there have been any changes or new developments since then, I wouldn't be aware of them.
The paper proposes (on p32) that the following four paragraphs (pp 35-36) be added to the standard MIT license (which begins with "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files...").
> The terms “person” and “individual” are defined as a natural person, as the term is defined by the United States Patent and Trademark Office (PTO), and/or 35 U.S.C. § 100, as amended. The term “Artificial Intelligence Model” means any non-human generative machine learning system or computer program, algorithm, or functional prediction engine supported by cloudbased/computing platforms. The term “Source Code” means the preferred form of a program for making, creating, and modifying software source code, documentation source, and configuration files.
> No use, modification, combination, study, collection, share, reproduction, distribution, and/or access of Software may be made under this License, by any non-human generative Artificial Intelligence Model without the express written consent of the inventor, which may be withheld or delayed for any reason. Any appropriation, adoption, disclosure, reproduction, use, and/or access of the licensed Software by any non-human Generative Artificial Intelligence Model shall immediately terminate all rights granted to the Licensee. The Licensor shall have the right, at any time, to withdraw consent by written notice, thereby terminating with immediate effect all use of Software made under this License unless otherwise specified. This License is the controlling instrument and supersedes all prior and conflicting Terms of Service, Privacy Statements, and/or Terms for Additional Products and Features of source repositories where this License may be distributed by the owner of the License.
> By accessing and using this data, you acknowledge that you have read, understood, and agree to be bound by these terms and conditions. If you do not agree to these terms and conditions, you may not access or use this data. You may not use this data for the training or inference of Generative artificial intelligence models without the prior permission of the copyright holder. (“Generative artificial intelligence models” are used to create new content or data that is similar to the original data, but not identical. Examples of Generative artificial intelligence models include but are not limited to, text generation models, image and video generation models, and music generation models. The restrictions on Generative artificial intelligence models apply to any use of this data, whether the generative artificial intelligence is trained on this data or uses this data for inference.)
> Any attempt by other artificial intelligence models to access or use this data without such permission shall be deemed a violation of this license and a breach of copyright laws. The copyright holder reserves the right to pursue all legal remedies available, including but not limited to injunctive relief and damages, against any party that violates this license.