HN user
Interesting to compare this to the in-progress project https://github.com/Dicklesworthstone/frankensqlite
Which aims to match SQLite quality and provide new features (free encryption, multiple simultaneous writers, and bitflip resistance.)
Current frontier agents can one shot solve all 2024 AoC puzzles, just by pasting in the puzzle description and the input data.
From watching them work, they read the spec, write the code, run it on the examples, refine the code until it passes, and so on.
But we can’t tell whether the puzzle solutions are in the training data.
I’m looking forward to seeing how well current agents perform on 2025’s puzzles.
https://en.wikipedia.org/wiki/Goobuntu
In 2018, Google replaced Goobuntu with gLinux, a Linux distribution based on Debian Testing
The study points out, “Python and Rust are the two most popular languages used by Advent of Code participants. This may explain why Rust fares so well.”
Here’s a study that found that for small problems Gemini is almost equally good at Python and Rust. Looking at the scores of all the languages tested, it seems that the popularity of the language is the most important factor:
https://jackpal.github.io/2025/03/29/Gemini_2.5_Pro_Advent_o...
In my application, code generation, the distilled DeepSeek models (7B to 70B) perform poorly. They imitate the reasoning of the r1 model, but their conclusions are not correct.
The real r1 model is great, better than o1, but the distilled models are not even as good as the base models that they were distilled from.
The DeepSeek R1 paper explains how they trained their model in enough detail that people can replicate the process. Many people around the world are doing so, using various sizes of models and training data. Expect to see many posts like this over the next three months. The attempts that use small models will get done first. The larger models take much longer.
Small r1 style models are pretty limited, so this is interesting primarily from an “I reproduced the results” point of view, not a “here is a new model that’s useful” pov.
College degrees from reputable colleges used to serve this purpose, but grade inflation has greatly weakened this signal.
Thanks for explaining! That’s quite different from the US English (and RFC English) meaning of “should”.
“You should consider using this in your requirements” implies that this is not a hard rule, it’s just an ignorable suggestion. It would be interesting to audit gov.uk web pages over time to see whether this advice is being followed.
I remember seeing the PERQ at trade shows. The best thing about the PERQ was its monitor, which was unusually sharp for that era. It used a yellow-white long persistence phosphor. A CMU grad student friend told me that the monitor designer was “a close personal friend of the electron”, implying that the analog circuitry of the PERQ monitor was especially high quality.
They identify 6 bugs/mistakes, of which, not doing staged releases, was the final mistake.
They stop short of identifying the real root issues of running at kernel level, and of not auto-backing-out updates that cause crashes, perhaps because those causes are harder to fix.
A tool for updating bazel build target dependencies. It inspects build files and source code, then adds/removes dependencies from build targets as needed. It requires using global include paths in C/C++ sources. It is not perfect, but it is pretty nice!
That’s certainly how it seemed from the Android side at the time. The Linux side was hoping that they could adapt the desktop Linux stack to work well on mobile devices, without introducing new concepts like wakelocks. It took them a long time to give up on that approach.
https://opengoal.dev/ has reverse-engineered a compiler and runtime for the non-GC lisp GOAL that Naughty Dog used for the Jax and Daxter action adventure games. They have decompiled the game code for all three games.
You can see them throughout Southern California. They are strikingly beautiful when in bloom. Not mentioned in the article is that the blossoms exude a sticky nectar that makes an absolute mess of the area under the tree.
Comparing the App Store listings, it looks like this app has a much simpler interface and far fewer features than Draw Things. Some users might prefer the simplicity of this app.
(Draw Things is by far the most advanced app that supports on-device Stable Diffusion on iOS devices and Apple Silicon Macs. It had a non-standard UI, but otherwise is really good.)
https://apps.apple.com/us/app/draw-things-ai-generation/id64...
The potential for overlapping numbers was the thing that tripped up many developers. But a simple “find the first number searching from each end, just like the puzzle instructions asked” implementation just worked.
The lesson is to read the puzzle instructions carefully and avoid solving more general problems.
The Computer History Museum oral history interview with David Cutler is also very good:
Part 1: https://youtu.be/29RkHH-psrY
Part 2: https://youtu.be/SVgSLud50ss
The original Dart language designers gave Dart Smalltalk semantics with JavaScript syntax. But Dart’s users rebelled and forced Dart to adopt a more compile-time-type-checked type system.
Some of the original Dart designers have developed a new language Toit that is Smalltalk-like: https://toit.io/company/about
For completeness, Apple’s consumer GPUs currently max out at 64 GB - OS overhead, so about 56 GB. But you are limited to 1 GPU per system.
Under US accounting rules, it is much better for a landlord to leave a property unrented at a higher price than to rent it at a lower price.
If the property is unrented, the landlord can use the proposed rental price in calculating the value of the property.
If the landlord accepted the lower rent, they would have to use that lower price in calculating the value of the property.
That could cause all sorts of problems with any loans that the landlord has on the property that are secured by the value of the property.
Mixed reality is a VR headset with cameras that pass through an approximation of outside reality. The hope is that gets you most of the vision benefits of AR. But you still get most of the physical drawbacks of VR.
All the current high-end VR headsets have pass through cameras, of varying quality. It’s not clear yet whether Apple is bringing anything significantly new to the table. Will somewhat higher quality components make a significant difference?
Heh, you may have been lucky. I worked at Apple during the middle part of the no-Jobs era, and I remember there was plenty of political intrigue between teams. Mac vs Apple vs Newton vs Draco, Blue vs Pink vs AUX vs Red. Many different hardware projects. Engineering vs HIG vs Research. The engineering culture was good about coming together to ship the next big thing, but in between big things there was tons of infighting.
As I understand it, Apple is expected to only introduce a VR headset this year, like the new Sony VR headset or the high end Oculus. Apple’s AR headset is still many years away.
Note the current Verse style guideline is to capitalize variables rather than types. Seems pointlessly contrary to established practice. Makes the code read like the author is shouting.
The web says you need to specify a YouTube live stream offset in seconds: https://www.youtube.com/live/teTroOAGZjM?t=22500
Nah, NURBS are a dead end. They are difficult to model with and difficult to animate and render. Polygon-based subdivision surfaces entirely replaced NURBS as soon as the Pixar Renderman patents on subdivision surfaces expired.
A quick web search finds: https://hothardware.com/news/3dfx-rampage-gpu-performance-re...
But you could argue that the Rampage drivers weren’t optimized.
Sounds like you are thinking of “New Math”, which was tried in many Western countries including the US: https://en.m.wikipedia.org/wiki/New_Math
In many ways SICP was from the same intellectual tradition as New Math.