Bitfield
No AI spaghetti code. Agents read state in under 1ns
What it does
Bitfield is the world's fastest plug-in runtime and database for founders who want their product to get huge without slowing down when plans change. Build fast today without trading away structure for scale: features become slots and communicate through storage like a mail room, so your 100th feature is as fast to build as your first. Works offline, runs on any device, keeps data local/private by default, syncs over any connection, runs executables, stores duplicates once, and replays events.
Does the same job
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- SASpacetimeDB – A database that replaces your server2023 · github.com · ▲80
We just released our database, SpacetimeDB, on GitHub under the BSL 1.1 license. It converts to a free software license after a few years. The point of the database is that you upload application logic into the database as a WebAssembly stored procedure, so instead of clients connecting to a webserver they connect directly to the database. The database itself does authentication and you write your own authorization logic just like you would inside a webserver. We’ve developed our game, BitCraft (https://bitcraftonline.com) entirely in this way. All of the game state is stored and…
- BFB-field, a novel probabilistic key-value data structure (`rust-bfield`)2024 · github.com · ▲153
`rust-bfield` is a Rust implementation of our novel "B-field" data structure, which functions like a Bloom filter for key-value lookups instead of set membership queries. The B-field allows you to compactly store data using only a few bytes per key-value pair. We've successfully utilized it in genomics to associate billions of "k-mers" with taxonomic identifiers while maintaining an efficient memory footprint. But the data structure is also useful beyond computational biology, particularly where you have large unique key domains and constrained value ranges. Available under an Apache 2…
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Parallel agents, diff reviewer, and multi-model comparisons
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- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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