Started: 2026-05-06
Commit: 455bebc2c7 (master)
Scope: 178k LoC C, lib/ + src/
Code links: https://github.com/curl/curl/tree/455bebc2c76223a1be26042f6d2393715c0df0cd (all line refs below pin to this commit)
curl is one of the most fuzzed and audited C codebases in existence (OSS-Fuzz, Coverity, CodeQL, multiple paid audits). Finding anything in the hot paths (HTTP/1, TLS, URL parsing core) is unlikely. Focus instead on:
| [ | |
| { | |
| "context": "Editor && (edit_prediction && showing_completions)", | |
| "bindings": { | |
| "tab": "editor::AcceptEditPrediction" | |
| } | |
| }, | |
| // Terminal | |
| { | |
| "context": "Workspace", |
I am investigating how to use Bend (a parallel language) to accelerate Symbolic AI; in special, Discrete Program Search. Basically, think of it as an alternative to LLMs, GPTs, NNs, that is also capable of generating code, but by entirely different means. This kind of approach was never scaled with mass compute before - it wasn't possible! - but Bend changes this. So, my idea was to do it, and see where it goes.
Now, while I was implementing some candidate algorithms on Bend, I realized that, rather than mass parallelism, I could use an entirely different mechanism to speed things up: SUP Nodes. Basically, it is a feature that Bend inherited from its underlying model ("Interaction Combinators") that, in simple terms, allows us to combine multiple functions into a single superposed one, and apply them all to an argument "at the same time". In short, it allows us to call N functions at a fraction of the expected cost. Or, in simple terms: why parallelize when we can share?
A
| /* --------------compact tabs--------------------*/ | |
| .workspace .mod-root .workspace-tab-header { | |
| width: unset; | |
| max-width: var(--tab-width); | |
| border: 1px solid var(--color-base-50); | |
| } | |
| /*.workspace-tab-header-inner { | |
| width: unset; | |
| }*/ |
| --- | |
| tags: | |
| - software/obsidian | |
| - software/markdownload | |
| - what/post | |
| - status/wip | |
| - what/my_setup | |
| --- | |
| > [!Notes] |
| @media print { | |
| /* set your preferred fonts here. */ | |
| :root { | |
| --body-font-family: "Newsreader Text", TimesNewRoman, "Times New Roman", Times, Baskerville, Georgia, serif; | |
| --header-font-family: "Century Gothic", CenturyGothic, AppleGothic, sans-serif; | |
| --code-font-family: MonoLisa, Menlo, SFMono-Regular, Consolas, "Roboto Mono", monospace; | |
| } |
| Overall, the listed strategies are helpful for learning and retaining new information. | |
| However, some improvements can be made for clarity and effectiveness. | |
| - Leverage the Pareto Principle for learning | |
| Improved Prompt: "Identify the 20% of [topic or skill] that will yield 80% of the desired results and provide a step-by-step learning plan to master it." | |
| - Utilize the Feynman Technique for deeper understanding | |
| Improved Prompt: "Explain [topic or skill] in the simplest terms possible, as if teaching it to a complete beginner. Identify gaps in my understanding and recommend resources to fill them." | |
| - Optimize learning through interleaving |
| /* Obsidian snippet to style output of pdf exports | |
| */ | |
| @media print { | |
| /* set your preferred fonts here. | |
| */ | |
| :root { | |
| --body-font-family: "Newsreader Text", TimesNewRoman, "Times New Roman", Times, Baskerville, Georgia, serif; |
| const carriageReturnIndicator = "⏭️"; //WARNING: There is a regexp replace that uses this literal value. | |
| const spaceReplacerChar = " "; // ◽ | |
| const pluginClassName = "speedReadingPlugin"; | |
| function updateReadTimeEstimate(phrases, speedWPM) { | |
| var readTimeEstimateEl = document.getElementById("readTimeEstimate"); | |
| readTimeEstimateEl.innerText = | |
| "Expected time to read the whole document at current speed: " + | |
| ((phrases.length * 60000) / speedWPM / 1000 / 60).toFixed(1) + | |
| "min."; |
