Search engine backend specs are almost final & now open source (AquilaDB), we love to make more and more of it on the way. This is because we're still discovering a market-fit & final product shape - open source development need a finalized spec & consistency over time.
Just wait until cheap to write GPT3 articles learn SEO techniques inherently and bombard the internet suppressing human writers in the spam ocean. At https://aquila.network we’re always thinking of this scenario.
Just wait until cheap to write GPT3 articles learn SEO techniques inherently and bombard the internet suppressing human writers in the spam ocean.
At https://aquila.network we’re always thinking of this scenario.
BotMark: A Telegram bot for quick bookmarking & powerful search (works in groups as well)
For Individuals:
When you find an interesting website/article on your mobile phone, press the share button and select "botmark"—nothing more, nothing less.
For Groups:
Add "botmark" to a group and keep track of all the links in your group in one place—easy peasy.
Thanks for sharing. I have been working on vector search engines (IR) for a while (Aquila Network). And I believe works such as this as well as the "differential neural computers" (couple of them from Deepmind) will be the next breakthrough in IR. I can't see the direct path yet. We're eagerly waiting to see somewhat a usable architecture yet. I believe current vector indexes will eventually get modified into hierarchical random access memories that stores compressed information in higher dimensions (static & replicated part of the distributed system). On top of this, an application specific information decoder (that's the dynamic part of the system, UX) will use the underlying information accordingly.