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@@ -33,7 +33,7 @@ Why do I want this? Because human memory is very, very bad. My (declarative) mem
Throughout human history, even before writing, the solution to this has been externalization of cognitive processing: other tiers in the memory hierarchy with more capacity and worse performance. While it would obviously be [advantageous](/rote/) to be able to remember everything directly, just as it would be great to have arbitrarily large amounts of fast SRAM to feed our CPUs, tradeoffs are forced by reality. Oral tradition and culture were the first implementations, shifting information from one unreliable human mind to several so that there was at least some redundancy. Writing made for greater robustness, but the slowness of writing and copying (and for a long time expense of hardware) was limiting. Printing allowed mass dissemination of media but didn't make recording much easier for the individual. Now, the ridiculous and mostly underexploited power of contemporary computers makes it possible to literally record (and search) everything you ever read at trivial cost, as well as making lookups fast enough to integrate them more tightly into workflows. Roam Research popularized the idea of notes as a "second brain"[^2], but it's usually the case that the things you want to know are not ones you thought to explicitly write down and organize.
More concretely, I frequently read interesting papers or blog posts or articles which I later remember in some other context - perhaps they came up in a conversation and I wanted to send someone a link, or a new project needs a technology I recall there being good content on. Without good archiving, I would have to remember exactly where I saw it (implausible) or use a standard, public search engine and hope it will actually pull the document I need. Maghammer (mostly) stores these and allows me to find them in a few seconds (fast enough for interactive online conversations, and not that much slower than Firefox's omnibox history search) as long as I can remember enough keywords. It's also nice to be able to conveniently find old shell commands for strange things I had to do in the past, or look up sections in books (though my current implementation isn't ideal for this).
More concretely, I frequently read papers or blog posts or articles which I later remember and want to retrieve - perhaps they came up in a conversation and I wanted to send someone a link, or a new project needs a technology I recall there being good content on. Without good archiving, I would have to remember exactly where I saw it (implausible) or use a standard, public search engine and hope it will actually pull the document I need. Maghammer (mostly) stores these and allows me to find them in a few seconds (fast enough for interactive online conversations, and not that much slower than Firefox's omnibox history search) as long as I can remember enough keywords. It's also nice to be able to conveniently find old shell commands for strange things I had to do in the past, or look up sections in books (though my current implementation isn't ideal for this).
## How?
@@ -86,7 +86,7 @@ It is actually somewhat more complex than that for various reasons. I had to mod
The system is obviously not perfect. As well as some minor gaps (browser history isn't actually put in a full-text table, for instance, due to technical limitations), many data sources (often ones with a lot of important content!) aren't covered, such as conversation history on e.g. Discord. I also want to make better use of ML - for instance, integrating things like Meme Search Engine better, ~~local Whisper autotranscription of videos rather than having no subtitles or relying on awful YouTube ones, semantic search to augment the default [SQLite FTS](https://www.sqlite.org/fts5.html) (which uses term-based ranking - specifically, BM25),~~ and OCR of screenshots. I still haven't found local/open-source OCR which is both good, generalizable and usable[^3]. Some of the trendier, newer projects in this space use LLMs to do retrieval-augmented generation, but I don't think this is a promising direction right now - available models are either too dumb or too slow/intensive, even on GPU compute, and in any case prone to hallucination. After some time in use use, it seems like the most critical thing to change is how chunks for embedding are generated and organized: a chunk from midway through a document retains no context about the title or other metadata, the ranker doesn't aggregate multiple chunks from within the document properly, and in my laziness (not wanting to bring in a tokenizer) they're way shorter than they have to be.
Another interesting possibility for a redesign I have is a timeline mode. Since my integration plugin (mostly) knows what columns are timestamps, I could plausibly have a page display all relevant logs from a day and present them neatly.
Another possible redesign feature is a timeline mode. Since my integration plugin (mostly) knows what columns are timestamps, I could plausibly have a page display all relevant logs from a day and present them neatly.
If you have related good ideas or correct opinions, you may tell me them below. The code for this is somewhat messy and environment-specific, but I may clean it up somewhat and release it if there's interest in its specifics.