VivaTechnics

We are developing a single-passenger autonomous vehicle, capable of traveling over 1000 miles, performing fully automated vertical takeoff, cruise, and landing.

Info (not recent) available here: https://awz.us/docs

fn main() { let mood = "awful";

    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".)

AI doesn’t eliminate deep thinking; mediocre companies and minds do. Don't blame everything to AI and find a true company and find a way to join them.

OPINION:

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.

Python won because simplicity scales. Like English—26 letters, minimal grammar—it became the default. Python mirrors that trajectory.

It is trivially learnable, absurdly flexible, and unmatched in ecosystem leverage. No simpler language delivers comparable reach.

Python may not be so suitable for systems, real-time, or performance-critical work—that’s Rust, C, and C++.

Nevertheless, every serious engineer must know Python, just as they must know shell/bash scripting. Non-negotiable.

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.

100% agreed. Awesome!

Here is our 501(c)(3) tech non-profit. All corporate profits are directed to children. Clear and transparent.

https://aid.aideo.us/

Good work! `type<T>` (generic types) can mimic dependent types for this?

- Maybe, design your language first, then name it.

- Single-letter names are mostly taken (e.g., B: https://en.wikipedia.org/wiki/B_(programming_language)

- 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.

Something short, simple, fundamental, low-level and deeply techie:

Xor, XORY

------

These are all excellent names: C, C++, Rust, Ada, Julia, Shell, Bash, etc.

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?

Extremely insightful and detailed. Thank you! Could you create a concise YouTube explainer on this?

Also, what are the best strategies to rigorously validate inputs while minimizing latency?

Is this the best for Rust: https://github.com/modelcontextprotocol/rust-sdk

Impressive! This is awesome! Let's go Rust! Rustworthy!

Awesome!

Technically, we could say?

(1) Single-loop: fixes actions within fixed rules, like Reinforcement Learning.

(2) Double-loop: questions and adapts the rules, somewhat like Meta-Reinforcement Learning.

This is pretty awesome! Ladybug!

Especially for Rust: https://rust-for-linux.com/coccinelle-for-rust

Thanks for sharing!

Awesome! Is there a video demo for this? Link it, if there is? Thanks!

Looks promising! Excellent!

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.

This is really cool. Thanks for sharing!

Try this: https://chat.z.ai/

It's pretty cheap!

Thanks!

No, only 99.999%.

Welcome to the real world!

Looks good. Do you have an online demo or something?

Holy cow! 8 is super high.

That's super cool. But do young devs/engineers even touch PHP these days? I haven't coded in it seriously for over a decade. But keep it up!

By accident

Why bother with this at all? There are infinitely more compelling problems worth solving out there. Pivot!?! :)

I never claimed Stack Exchange should’ve pioneered LLMs. But it’s not merely a web forum company—just as Google isn’t just a search company. Stack Exchange is a 15-year-old tech firm that has stagnated. Innovation has been virtually nonexistent; their idea of progress has long been superficial UI tweaks on a legacy platform.

Even now, Stack Exchange resists adaptation. This very post highlights their `robots.txt` policy, which actively blocks crawlers—a clear signal of protectionism over transparency. They market themselves as community-driven, but the reality is far more corporate and insular.

Stack Overflow’s situation is telling: while search traffic is down a modest –5% to –14% (per their own data), engagement metrics are in freefall. Weekly posts have dropped 16%; monthly questions are down as much as 66% from their peak. That’s not a dip—it’s systemic decay.

Understood. Twilio, despite its scale, isn’t really a good name—uninformative and clunky. Starting with “dev” would be an option. I'd prefer `.io` for credibility, but `.host` and others can work depending on positioning.

I just checked, these are available domains:

devote.host: Memorable; blends “developer” and “vote” (community-driven).

devios.io: Sounds sleek, futuristic. deviz.io or dewiz.io: Snappy, suggests tools or wizardry.

Dig deeper, you will find simpler names.

- `devop.tech` is also available. - `oz.dev` is also available, if you want a premium domain.

Start with “A” if possible to ensure top-of-list visibility. Use “AI” as a prefix when relevant to anchor the identity in AI/infra/dev tooling. Keep it short—4 to 5 letters ideal, max 6. It must be memorable: phonetically crisp, simple, and sticky. The name should be brandable—distinct, clean, with no generics or clutter. Prioritize domain availability under .dev, .io, .tech, .host, or .xyz. Don’t obsess early; names evolve and rebranding is easy. Examples like “Aidev” balance AI-focus and clarity well. Currently, devo.host and aidev.host are available.