bmc7505
Joined 12 years ago
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Recent submissions
Comment · 20 days ago
“breakthrough” is nothing more than an artifact of mathematicians not being able to properly specify the rules of their games in natural language… the theory of computer science has a culture that actively discourages running algorithms on a computer.
Comment · 3 months ago
Cool to think this demo would have been possible over fifty years ago. I wonder what someone from 1975 would have said if you had shown this to them back then.
Comment · 5 months ago
This topic recently came up at the FLANN workshop [1], and seems to periodically be rediscovered [2,3,4] in different contexts. While some have speculated about the biological role it plays (e.g., Pearlmutter & Houghton [5]), we still lack a conclusive theory of sleep, but the convergent evolution of this specific phenomenon across the animal kingdom and the fact that deprivation is inevitably fatal seems like an important clue.
[1]: https://flann.cs.yale.edu
[2]: https://www.cs.toronto.edu/~hinton/csc2535/readings/ws.pdf
[3]: https://arxiv.org/abs/1711.02282
[4]: https://arxiv.org/abs/2006.08381
[5]: https://mural.maynoothuniversity.ie/id/eprint/1653/1/Hamilto...
Comment · 6 months ago
I've recently been using this plugin [1], which is still under development but is an adequate stopgap until a better solution comes along.
[1]: https://plugins.jetbrains.com/plugin/22150-noctule-the-swift...
Comment · 8 months ago
As foretold six years ago. [1]
[1]: https://breandan.net/2020/06/30/graph-computation#roadmap
Comment · 8 months ago
Fast matrix multiplication would be a more useful benchmark: https://fmm.univ-lille.fr/
Comment · 8 months ago
17k TPS is slow compared to other probabilistic models. It was possible to hit ~10-20 million TPS decades ago with n-gram and PDFA models, without custom silicon. A more informative KPI would be Pass@k on a downstream reasoning task - for many such benchmarks, increasing token throughput by several orders of magnitude does not even move the needle on sample efficiency.
Comment · 9 months ago
There are a few approaches if you want to write a new language. One, as the author argues, is to write a library in an existing language, which may require sacrificing ergonomics to fit inside the syntax of the host language, but is safe, modular and reusable.
Many DSLs can be bolted onto an existing language with support for compiler extensions. This approach offers more flexibility, but often leads to fragmentation and poor interoperability in the language ecosystem.
There is third approach, established by a group in Minnesota [1], which is to design languages and tools which are modular and extensible from the get-go, so that extensions are more interoperable. They do research on how to make this work using attribute grammars.
If the host language has a sufficiently expressive type system, you can often get away with writing a fluent API [2] or type safe embedded DSL. But designing languages and type systems with good support for meta-programming is also an active area of research. [3, 4]
If none of these options work, the last resort is to start from tabula rasa and write your own parser, compiler, and developer tools. This offers the most flexibility, but requires an enormous amount of engineering, and generally is not recommended in 2026.
[2]: https://arxiv.org/pdf/2211.01473
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