Aeyxen (u/Aeyxen) - Readit News

Aeyxen commented on Tornado warnings delayed because of DOGE cuts mesoscalenews.com/p/torna... · Posted by u/aaronbrethorst

johnnyanmac · 3 months ago

Chaos theory and brownian motion make it a herculesn for anything to predict the weather more than a few days out. There's too many micro factors to track leading to weather that constantly shifts. And The data costs to attempt to try to do so is well past even the most well compensated meteorologist.

I'm not too worried about the human factor being replaced as a whole here. Even with AI, someone needs to interpret the output and make sure the the prediction models actually work.

Aeyxen · 3 months ago

Yeah, true that.

Aeyxen commented on Zod 4 zod.dev/v4... · Posted by u/bpierre

jasonthorsness · 3 months ago

But how is the below possible - doesn't it need to include most of the TypeScript compiler? Does it compile the type definitions to some kind of validation structure (like how a compiled regex works) and then use just that?

    - Zero external dependencies
    - Works in Node.js and all modern browsers
    - Tiny: 2kb core bundle (gzipped)

Aeyxen · 3 months ago

I think Zod uses JIT compilation via `new Function`, rather than including the entire TypeScript compiler. This method allows for concise validation logic, executing only what’s necessary at runtime.

Aeyxen commented on Show HN: Vaev – A browser engine built from scratch (It renders google.com) github.com/skift-org/vaev... · Posted by u/monax

Aeyxen · 3 months ago

Bravo to the Vaev team for championing unrestrained technological exploration!

The choice of C++ is bold.

Despite the security concerns often highlighted, modern C++ with smart pointers, and RAII patterns can be just as safe as Rust when done right. Vaev’s security model should focus on process isolation, sandboxing techniques, and leveraging modern C++ features to minimize vulnerabilities.

Super excited to see such raw innovation and courage in tackling a colossal task often monopolized by juggernauts like Chromium.

Aeyxen commented on Tornado warnings delayed because of DOGE cuts mesoscalenews.com/p/torna... · Posted by u/aaronbrethorst

johnnyanmac · 4 months ago

>Before we point fingers or blame 'technology/automation' shortfalls, let's quantify the concrete bottleneck: skilled human decision-makers are the limiting reagent

All the automation in the world with useless without a human guide to either transform production into a useful product, or useful knowledge to heed. That's why this act of trying to remove human labor is asinine. Even skilled human can't always get the right readings, so expecting a robot to do it all at this stage is just selling snake oil.

Aeyxen · 3 months ago

Actually, I'll go a step further - in the long run, we probably won't need human forecasters at all.

The current human-in-the-loop model exists largely because our technology hasn't been good enough yet, not because there's something inherently special about human judgment in this context. Weather prediction is fundamentally a pattern recognition problem. Pattern analysis at scale is exactly what computers do better than us.

Perhaps someone could apply to YC with this idea. There is one YC startup doing this already: https://www.ycombinator.com/companies/atmo

Aeyxen commented on Proton threatens to quit Switzerland over new surveillance law techradar.com/vpn/vpn-pri... · Posted by u/taubek

Anamon · 4 months ago

There is no precedent here. There are politicians advocating for this kind of stuff everywhere, that doesn't indicate the likelihood of a law like this passing.

Anyone can suggest a law. The stage this one failed in is explicitly meant to gauge if there would be any reasonable support to get it passed. The answer was a resounding No.

Even if it proceeded, it would have quite likely lead to a popular referendum due to Switzerland's system of direct democracy. I'd say not many places in the world have as strong defenses against laws like this as Switzerland.

Of course, it doesn't mean that it's not important to highlight when such ideas do crop up, and especially naming and shaming who/where they come from. I'm glad Proton et al. spoke out.

Aeyxen · 4 months ago

Yeah, I hope that as well.

Aeyxen commented on LLMs are more persuasive than incentivized human persuaders arxiv.org/abs/2505.09662... · Posted by u/flornt

sebastiennight · 4 months ago

As a marketer with a couple of decades of experience I can tell you that there is way more financial incentive in "slightly persuading [consumer] to tilt towards [product] in their next purchase, and spend more and earlier" than there ever will be towards "next-level unbiased tutor in anything".

The "super tutor" stuff that is always mentioned as the utopian outcome (along with "cures for cancer") is, unsurprisingly, never something being worked on by the person or lab quoting these examples.

I guess anything goes in B2B settings, but there is a valid reason to be cautious about these advances when it comes to mass-market consumer-facing applications.

Aeyxen · 4 months ago

I understand your perspective as a marketer, but I think you're creating a false dichotomy. Yes, persuasion tech has stronger financial incentives, but that doesn't prevent beneficial applications from emerging simultaneously.

The "super tutor" isn't some distant fantasy - millions already use ChatGPT, Claude and similar tools daily for personalized learning. They're imperfect but genuinely helpful for programming, languages, math, and countless other topics.

Look at what happened with YouTube: millions of people transformed themselves into programmers, musicians, mechanics, and countless other professions through free video tutorials. Khan Academy revolutionized math education. Coursera and edX brought university courses to anyone with internet. This wasn't utopian thinking - it was practical technology solving real educational problems at scale.

What's different now is that LLMs enable the missing piece: personalization. The one-on-one adaptive experience that was previously limited to those who could afford human tutors at $50-100/hour is now available to anyone at negligible marginal cost.

Your skepticism about cancer applications too ignores the technological trajectory we've been on for decades. Just as YouTube and online platforms democratized education, technology has been steadily dismantling bottlenecks in medical research.

The human genome project initially cost $3 billion and took 13 years. Today you can sequence a genome for under $1,000 in days. This wasn't utopian thinking; it was technological progress following its natural course.

Think what LLMs will do here.

Aeyxen commented on LLMs are more persuasive than incentivized human persuaders arxiv.org/abs/2505.09662... · Posted by u/flornt

Aeyxen · 4 months ago

It's always amusing to watch people act shocked when LLMs beat average humans at persuasion. The actual headline here should be: 'A system trained on terabytes of successful human persuasion is better at persuasion than a random person on a crowdwork platform.' No mystery—just the mechanics of scale and exposure.

But guess what? Now, finally, we can co-opt LLMs for things humans fumble: e.g., real-time conversational tutoring, adaptive negotiation agents, or even scalable personal 'bullshit detectors' as countermeasures. I hope conversation doesn't go into AI-Safeteyism and restricting LLMs and more about building stuff. Let's build, not block.

Aeyxen commented on Tornado warnings delayed because of DOGE cuts mesoscalenews.com/p/torna... · Posted by u/aaronbrethorst

Aeyxen · 4 months ago

The thread keeps circling around the politics, but almost nobody has dug into what actually goes on in the NWS tornado warning pipeline.

It's worth being specific: the National Weather Service operates some of the most robust automation and radar ingest pipelines on Earth, but the final go/no-go warning call is almost always human—often a single overnight forecaster on a console, monitoring a swath of counties. Automation (e.g., Warn-on-Forecast guidance) can surface threats, but the NWS intentionally doesn't have an 'auto-warn' button for tornadoes, because of the asymmetry of false positives (blow credibility, cost lives in the long run).

Budget cuts reduce redundancy and experience in those overnight shifts. When you have only one person monitoring instead of a team of two or three, you get decision fatigue and coverage holes, especially during clustered, multi-cell outbreaks. We've seen near-misses in the past, and every pro-meteorologist I know says they're playing defense against process errors, not just technology failures.

Before we point fingers or blame 'technology/automation' shortfalls, let's quantify the concrete bottleneck: skilled human decision-makers are the limiting reagent; machine learning warning aids are still years away from majority trust.

Aeyxen commented on Tornado warnings delayed because of DOGE cuts mesoscalenews.com/p/torna... · Posted by u/aaronbrethorst

shepherdjerred · 4 months ago

Part of me doesn’t feel too much sympathy. The majority of Americans voted for Trump. Even more so in the conservative states that are more likely to be impacted by there events.

Trump campaigned on cutting government services.

Everyone is okay with cutting a public service (at the expense of others) until they need that particular service

---

To clarify, I'm not cheering on this disaster or hoping that those who voted for Trump "get what they deserve"

Aeyxen · 4 months ago

Politics aside, it’s odd how often the entire debate misses the real bottleneck: assigning blame doesn’t restore operational capacity or re-architect the warning pipeline. If the system depends on 24/7, highly skilled human decision-makers, and you cut those positions, the outcome is predictable—slow, brittle responses.

ANY critical pipeline that can be broken by one missing seat is overdue for technical reinforcement

Aeyxen commented on O2 VoLTE: locating any customer with a phone call mastdatabase.co.uk/blog/2... · Posted by u/kragniz

Aeyxen · 4 months ago

The wild part: this isn’t a theoretical bug. It’s implementation laziness that other UK networks already solved, as the post notes. ECI leaks have been called out since LTE rolled out—see papers like https://arxiv.org/abs/2106.05007—and automated location mapping is trivial given open mast DBs.