We are developing a single-passenger autonomous vehicle, capable of traveling over 1000 miles, performing fully automated vertical takeoff, cruise, and landing.
let mut msg = r#"
We feel super sad.
Rust in Peace.
Steel dreams compile to dust,
Silent threads unwind.
Memory fades,
Borrowed time returned.
"#;
println!("{}\n{}", mood, msg);
}
Similar to Kiva Systems which was Amazon's best acquisition, Waymo is simply Google's best acquisition. (We live in San Francisco and it feels much safer around these Waymo cars than average "drivers".)
This will only compound wasted time on Claude.ai, which exploits that time to train its own models.
Why time wasted?
Claude’s accuracy for shell, Bash, regex, Perl, text manipulation/scripting/processing, and system-level code is effectively negligible (~5%). Such code is scarce in public repositories. For swarms or agents to function, accuracy must exceed 96%. At 5%, it is unusable.
We do also use Claude.ai and we believe it is useful, but strictly for trivial, typing-level tasks. Anything beyond that, at this current point, is a liability.
LLMs operate on numbers; LLMs are trained on massive numerical vectors. Therefore, every request is simply a numerical transformation, approximating learned patterns; without proper trainings, their output could be completely irrational.
- Focus on one key feature your language does better than others. Low-level languages are trending; high-level application languages are crowded. For example, if you could make assembly-style code user-friendly, that could be a strong niche.
Impressive! This approach can be applied to designing a NoSQL database. The flow could probably look something like this? Right?
- The client queries for "alice123".
- The Query Engine checks the FST Index for an exact or prefix match.
- The FST Index returns a pointer to the location in Data Storage.
- Data Storage retrieves and returns the full document to the Query Engine.
We switched to Rust.
Generally, are there specific domains or applications where C/C++ remain preferable? Many exist—but are there tasks Rust fundamentally cannot handle or is a weak choice?
Compared to TigerGraph, Neo4j, JanusGraph, Dgraph, and ArangoDB, I’d love to see a benchmark-ish comparison of GenosDB in terms of performance, latency, scalability, modularity, and flexibility.
Info (not recent) available here: https://awz.us/docs