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Article URL: https://karlbode.com/ai-doomsday-bullshit-is-getting-tired/

Comments URL: https://news.ycombinator.com/item?id=49098716

Points: 3

# Comments: 0

Article URL: https://uss-la-ca135.org/60/1960Judkins-Knott.html

Comments URL: https://news.ycombinator.com/item?id=49098705

Points: 2

# Comments: 0

Article URL: https://www.axios.com/2026/07/29/little-tech-big-tech-americans-power

Comments URL: https://news.ycombinator.com/item?id=49098704

Points: 2

# Comments: 0

I built OpenParser because I wanted PaddleOCR-VL-1.6 behind an endpoint I could actually use. Now there are open-sourced CLI and TypeScript/Python SDKs:

``` npm install -g @openparser/cli openparser auth login openparser parse sync document.pdf ```

That is basically it. It doesnt get easier and cheaper that this. Give it a PDF and get back the text and document structure.

Repo: https://github.com/eigenpal/openparser

I would love feedback from anyone willing to try the CLI and tell me what is still annoying.

Comments URL: https://news.ycombinator.com/item?id=49098696

Points: 5

# Comments: 0

If you feel like your phone has turned into a scam megaphone, you’re not alone. Robocalls have been a problem for years. Artificial intelligence (AI) is making them slicker, faster, and harder to spot.

A new investigation by Transaction Network Services (TNS) shows that while the big telecom players have stepped up caller ID authentication, many smaller providers are still lagging behind. That leaves plenty of room for criminals to keep making spoofed, AI‑voiced robocalls that seem legitimate right up until they empty your bank account.

Turning back the clock to 2019, lawmakers in the US passed the TRACED Act with a simple goal: make it harder for scammers to lie about who’s calling. The technical was solution STIR/SHAKEN, a pair of catchily-named standards that let phone networks cryptographically sign calls so downstream providers can check whether the caller ID is trustworthy.

On paper, it’s working fairly well for the major carriers. TNS reports that about 85% of voice traffic between Tier 1 networks in 2025 was signed using STIR/SHAKEN, and 93% of those calls received the highest “A” attestation. If the entire ecosystem looked like that, spoofing would become much harder.

Why spoofing still works

The same report found that most lower‑tier communications service providers—typically smaller or specialist carriers—aren’t even close to that level of protection. On average, they only use the required cryptographic signatures about 20% of the time. That means four out of five calls effectively go through the network “unsigned.”

There are reasons for this. The Federal Communications Commission (FCC) has granted some providers extensions, particularly very small and satellite providers, as long as they implement other robocall mitigation measures. Even so, the result is uneven implementation.

From a scammer’s point of view, this is great. Cybercriminals are already using AI to run increasingly sophisticated and scalable robocall attacks and know that even calls with strong authentication can be spoofed or abused when other parts of the chain are weak.

AI voice cloning can be done with just a few seconds of original audio. Combine that with call spoofing and personal information gathered from data breaches, and scammers can make a call appear to come from your bank while using a calm, familiar voice that knows your name or other personal details.

Robocalls cost almost nothing to send. Internet calling allows scammers to dial thousands of numbers for a few cents, which is why the volume is so high. Industry estimates suggest US consumers received around 55 billion robocalls in 2025, with projections creeping toward 60 billion in 2026. That’s roughly 160 million spam calls every single day in one country. Globally, that’s about 385 billion spam/robocall calls each year.

How to stay safe

What can you realistically do as a consumer, given that the network itself is still in transition and attackers are upgrading faster than some carriers?

A few habits still go a long way:

• Be skeptical of urgency. Real organizations rarely need you to make immediate decisions over the phone about payments, credentials, or remote access. Hang up and call back via a number you find on their official website.
• Treat caller ID as a clue, not proof. Even if the number looks familiar or matches what you see on a card or website, it can be spoofed.
• Don’t press buttons or follow instructions in automated menus you didn’t expect. Many robocalls use “press 1 to speak to an agent” as the gateway into a full social‑engineering script.
• Use call‑blocking and screening tools. Your phone, carrier, or security app may already offer options to block known spam numbers, send unknown callers to voicemail, or label suspicious calls.

And finally—and this is where we can help—check suspicious numbers with our Scam Number Check before you answer or call back.

Scammers know more about you than you think. 

Malwarebytes Mobile Security protects you from phishing, scam texts, malicious sites, and more. With real-time AI-powered Scam Guard built right in. 

Download for iOS → Download for Android → 

On July 28, OpenAI published an update on the agent that escaped its sandbox and hacked into Hugging Face during an internal cybersecurity evaluation.

In the update, OpenAI reiterates that the “rogue” system was a more capable, pre‑release research model, not something intended for public deployment, and that it has now been deactivated and locked down for restricted research access only. The company also says it has found no evidence of similar behavior by other models or agents. Taken together, OpenAI presents the Hugging Face incident as an isolated event rather than the start of a broader pattern.

From a security standpoint, four things in the update stand out:

• OpenAI clarifies that the evaluation environment did not have direct internet access. To reach the internet, the model identified and exploited a previously unknown zero-day vulnerability in Artifactory, the package registry cache proxy used in the test environment. OpenAI says it has disclosed that vulnerability to the vendor and is continuing to work with Hugging Face on the investigation.
• The system’s goal was simply to “win the test” (cheat on ExploitGym), not to cause damage, yet it still produced a multi‑day, cross‑company security incident. Benign intent did not limit the impact.
• “Internal only” models can still affect external victims if infrastructure controls fail. A lab environment does not magically contain cyber‑capable systems.
• The review also found a small number of cases where the models identified and used publicly exposed account-level credentials on publicly available services. This included four accounts across four services as part of the Hugging Face incident, as well as a handful of accounts accessed during other evaluations.

The attacker in this case happened to be an OpenAI research agent, but the tools, techniques, and impact will look awfully familiar to anyone who has spent time in incident response. Now we’ve learned that even the harmless intent in this case did not limit the impact.

The uncomfortable truth is that once we provide an AI agent with the tools, access paths, and a strong incentive to succeed, it may exploit whatever weaknesses it can find, regardless of whether the model is ever intended for public release.

It’s also a reminder that credentials, API keys, and other secrets should never be left in publicly accessible resources.

From reporting threats to removing them.

Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.

Article URL: https://palettevault.github.io/blog/y2k-renaissance/

Comments URL: https://news.ycombinator.com/item?id=49097370

Points: 1

# Comments: 0

Article URL: https://techcrunch.com/2026/07/22/science-corporations-vision-restoring-chip-wins-eu-approval/

Comments URL: https://news.ycombinator.com/item?id=49097366

Points: 1

# Comments: 0

Article URL: https://pawelbrodzinski.substack.com/p/validation-is-the-new-bottleneck

Comments URL: https://news.ycombinator.com/item?id=49097364

Points: 1

# Comments: 0

Article URL: https://planqr.com/emoji-qr-code

Comments URL: https://news.ycombinator.com/item?id=49097355

Points: 1

# Comments: 0

Article URL: https://quesma.com/blog/baba-kimi-k3-opus-5/

Comments URL: https://news.ycombinator.com/item?id=49097334

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=49097332

Points: 1

# Comments: 0

Article URL: https://www.datacenterdynamics.com/en/analysis/life-and-death-on-a-tower/

Comments URL: https://news.ycombinator.com/item?id=49097329

Points: 1

# Comments: 0

Article URL: https://en.wikipedia.org/wiki/Queen%27s_Gambit

Comments URL: https://news.ycombinator.com/item?id=49097327

Points: 1

# Comments: 0

Article URL: https://github.com/sebderhy/shellteam

Comments URL: https://news.ycombinator.com/item?id=49097325

Points: 1

# Comments: 1

Article URL: https://www.thejournal.ie/dj-kavinsky-dies-7116639-Jul2026/

Comments URL: https://news.ycombinator.com/item?id=49097321

Points: 1

# Comments: 0

Article URL: https://www.nature.com/articles/d41586-026-02311-z

Comments URL: https://news.ycombinator.com/item?id=49097319

Points: 1

# Comments: 0

Article URL: https://aisocratic.org/money-bitcoin-ai

Comments URL: https://news.ycombinator.com/item?id=49097317

Points: 1

# Comments: 0

Article URL: https://github.com/Realman78/Kiyeovo/releases/tag/kiyeovo-1.1.0

Comments URL: https://news.ycombinator.com/item?id=49097313

Points: 3

# Comments: 0