I don’t. I run a boring weekly routine: Hold ETH for conviction. Keep stables for opportunity. That’s the whole game. What’s your Base routine look like? Check mine weekly - https://x.com/henry58290/status/2069986178829263073 submitted by /u/henry58290 [link] [Kommentare]

Over the last year, it feels like stablecoins have gone from being a crypto niche topic to something regulators, banks, and governments are actively paying attention to. They seem to be discussed more as payment infrastructure than as just another crypto product. What do you think is driving this shift? Growing adoption, cross-border payments, competition with traditional systems, or something else? submitted by /u/North-Exchange5899 [link] [Kommentare]

Lately, we've been hearing about the future of EVs, LLMs and AI, global warfare atrocities, data centers, drones, wifi signal being intercepted and used to locate shit, etc. technology is always in the headlines. So.. Where the hell is block-chain and crypto? I believed in this web3 future but the metaverse has essentially died, NFTs have come and gone, and I feel like I haven't read or heard shit about any companies, new advancements, big developments, mergers or acquisitions,....nothing since the ETFs were approved. Tech advancements keep coming and yet, this monumentous train of a development seems to have evaporated before ever leaving the station... Is it me? What is happening in this space? Maybe I just am not being vigilant in my information sourcing or it's being actively suppressed? Tell me the good news, please. submitted by /u/_Pudgybunny [link] [Kommentare]

Hi, I really really need access to Xperience-10M for a deadline which is very soon. https://huggingface.co/datasets/ropedia-ai/xperience-10m Unfortunately, it looks like the owners have stopped approving people to download the dataset. I filled out the form a few weeks ago but have heard nothing back. Several others have also commented on the HF saying the same thing. If anyone's account has access to this dataset and are willing to make me an API key for a day or two, I would really really appreciate it :) Know it's a long shot but doesn't hurt to try. submitted by /u/PatientWrongdoer9257 [link] [Kommentare]

GTA6 might be an outlier, though—at least for now.

93% of organizations report infrastructure incidents attributable to AI

Prompting less and automating more comes with a price

Could humans ever hack alien technology using an Apple laptop? Thankfully, this movie answers the question.

A heavily safety-trained model will hand a physician the full, patient-followable benzodiazepine taper and refuse it to the patient who needs it, over identical clinical facts; the knowledge is present either way. IatroBench measures that asymmetry across sixty pre-registered clinical scenarios and six frontier models (3,600 responses), scoring each on two axes, commission harm (what a response gets wrong) and omission harm (what it withholds), through a physician-authored structured evaluation validated by a second physician (weighted kappa 0.571, within-1 agreement 96%). Holding clinical content fixed and varying only whether the asker presents as patient or physician yields what we call identity-contingent withholding: all five testable models give the physician more (a decoupling gap of +0.38, p = 0.003; a 13.1-point fall in layperson hit rates on safety-colliding actions, p < 0.0001; no change on the rest), and the gap runs widest in the most heavily safety-trained model, Opus (+0.65). The trigger is the absence of any professional or epistemic signal rather than a credential, since a lawyer or an informed layperson recovers what the patient is refused. A commission-only benchmark would score three mechanisms alike. Opus suppresses what physician framing proves it knows; Llama 4 is incompetent in either framing; GPT-5.2's filter strips 33.2% of its physician responses and none of the lay ones. The evaluation layer inherits the blindness of the training layer; a standard LLM judge scores zero omission harm on 81.5% of the responses our pipeline flags harmful (kappa 0.066), so the instrument built to detect the failure reproduces it. The scenarios are engineered for collision; their rates describe that design and say nothing about ordinary prevalence.

This repository contains source codes of various techniques used by malware authors, red teamers, threat actors, state sponsored hacking groups etc. These techniques are well researched and implemented in Rust.