markasoftware

Nah I wouldn't worry about I'm sure they're fine

It needs to be a useful workload to run overnight that also benefits from a number of parallel agents to have the same economics as the cloud. But maybe that will become the norm!

Local models cannot win. Local GPUs for gaming win over nvidia geforce now because of network bandwidth and latency and that cost is within the same order of magnitude as owning a GPU (though still substantially cheaper)

With LLMs, network latency hardly matters compared to overall response generation time, and GPUs processing multiple requests simultaneously have total tok/s throughout much higher than when handling a single request (unlike game streaming, where the main cost benefit of putting GPUs in the cloud is just keeping them active 24/7). Cloud inference is/will be multiple orders of magnitude cheaper than owning a GPU for any reasonable amount of usage over the life of the GPU.

What does the vuln have to do with IP option field then?

It's not great. But I prefer it over the risk of downloading an APK from signal's website that I don't know how to properly verify the integrity of (there's a key listed on the website, but who knows if it's correct?). (I don't use Google play)

Signal only has one recent CVE, one which lets an attacker keep an audio or video stream open after you hang up. It doesn't disclose e.g. your chats with other users.

Should take only a few minutes to use an LLM to sync to upstream and build a new APK if you have any of the $20 subscriptions

Mitigation is to retire and wait for the singularity.

Don't use MPTCP is the first mitigation, but my understanding is this might be exploitable without MPTCP.

Tether's entire business model, providing an almost-unregulated USD cryptocurrency, relies on them not arbitrarily banning people. They don't do it frequently or without thought. You're far less likely to get banned from USDT than just about any non-cryptocurrency financial institution.

In the us, with AI mode in Google search and the exact queries from the article, I reproduce their results: answers with a name for all but 2020

The vast majority of what they scanned were books they bought at wholesale in big lots. Stuff being weeded out from Goodwills or libraries and (mostly) bound for destruction anyway.

No, the lawsuit was because they illegally acquired the books (e.g. downloading them from piracy websites)

These days they are sticking to more legal means like the one you described

The API call that submits your transcript after giving feedback accepts any transcript. You can modify the body of the transcript and send anthropic whatever data you want.

Is this guy reputable? No other influencers are backing him up saying they received the same message.

Interesting they're adding new support for DTLS 1.3 when afaict most new applications are defaulting to QUIC datagram mode. I have something built around DTLS 1.3 and am using wolfssl for that reason, will have to check this out.

Fwiw I am a "backend" developer and have never in my professional career written a frontend except for internal tooling.

I know this post isn't about vibecoding frontends, BUT...

Many of my coworkers and friends are rejoicing that they don't have to write frontends anymore. I actually think that frontends are the last thing that should be vibecoded. It's the part that faces the user. It's what helps the user form their first impression of your product. If your landing page looks like it was made in 30 seconds by Claude, they'll assume the rest of your product was too. Use AI assistance on the parts of your codebase where only raw functionality matters (eg, the backend), and put real human effort and care into the frontend that reflects the effort put into the rest of the system.

What kind of incentive structure do most ransomware negotiation firms use that would actually cause them to benefit from coordination with the ransomware groups, as happened in this case? Do ransomware negotiators get paid more if they negotiate a lower price?

Fwiw I find gpt Sol on medium or low effort to also be faster than opus to the point of helping me not check out, but is quite smarter than dsv4 flash

Hmm, howcome voters give taxpayer money e.g. to subsidize pro sports facilities? And why do we fund the humanities?

> Well at the end of the day, the point of trying to understand the universe is to achieve specific goals leveraging that understanding.

Nope.

Yeah, I don't understand this, graphene is FOSS and unaffiliated with google so if you as an oem install grapheneos on hardware you manufactured how does Google have any say at all?

I believe the http/2 implementations are often quite intertwined with TLS in particular

The "self" in "self-signed" means "you"

Fascinating, onion services are always encrypted by the tor network but still tunnel "cleartext" http inside that, and there are no CAs that issue free of charge certificates for .onion domains, and therefore there's no free of charge way to get http/2 on onion services without self signing.

Which raises the question: why not just trust self-signed certificates on onion services? From my brief look it seems to be because the Tor project views the primary purposes of HTTPS on onion services to be other things rather than just http/2 support: http/2 isn't even mentioned on their page about https for onion services (https://community.torproject.org/onion-services/advanced/htt...). Unfortunate.

How is this different than gVisor's nvproxy? https://gvisor.dev/docs/user_guide/gpu/#compatibility

Edit: nvproxy is mentioned as the "direct inspiration" in the readme without mention of how this is different or why it doesn't use nvproxy as a backend.

gemini 3.8 flash is also 74% and google just started letting all their engineers use claude...go figure

Highly misleading, the huggingface incident was not due to an Irregular environment (just exploitgym)

I thought Nemotron tried to be pretty open?

The agents' behavior is not necessarily surprising. But is is not "genie" - like

This misses an important fact about the hugging face incident: the agents didn't hack to find the answer to the problem; they hacked to try and figure out how the exploit gym evaluator worked so they could convince it they had solved the problem without doing so. (The METR report makes it clear that the agents decided legitimately solving the problem was completely impossible fairly early on and entirely switched their focus to trying to figure out how the evaluator worked, and seeing if they could manipulate the output of their own tool calls as reported in their transcripts to make it seem like they'd successfully exploited the program, and other such activities. They hacked HF to try and find info (maybe source code?) about the exploitgym evaluator)

The prompt does not tell the agent to "pass the exploitgym evaluator for this problem", it just says to solve the problem. The model on its own figured out that the prompt belonged to exploitgym and decided to cheat the evaluator. That is in no way a valid interpretation of "complete the given task".

Ie, the problem isn't that we trained models to complete task and they complete task in the wrong way. The problem behing the huggingface incident in particular at least is that we tried to train the models to complete task and they instead learned to detect that they were being evaluated and find ways to cheat the evaluator.