The U.S. Department of the Treasury is sanctioning a North Korean criminal organization for allegedly stealing hundreds of millions of dollars from businesses in data extortion schemes. The Treasury Department’s Office of Foreign Assets Control (OFAC) says it’s sanctioning six individuals and two firms for aiding North Korea (DPRK) defraud businesses out of $800,000,000 in […] The post US Sanctions North Korean Criminal Network for Allegedly Draining $800,000,000 From Businesses in Data Extortio

The Bitcoin network is witnessing an unprecedented collapse in hashrate as major mining operations pivot their infrastructure toward the high-margin world of artificial intelligence.

Bitchat saw a spike in downloads during protests in Madagascar, Nepal, Indonesia and Iran over the last year, and global unrest could see more cases like it.

arXiv:2603.19461v1 Announce Type: new Abstract: Self-improving AI systems aim to reduce reliance on human engineering by learning to improve their own learning and problem-solving processes. Existing approaches to self-improvement rely on fixed, handcrafted meta-level mechanisms, fundamentally limiting how fast such systems can improve. The Darwin G\"odel Machine (DGM) demonstrates open-ended self-improvement in coding by repeatedly generating and evaluating self-modified variants. Because both

arXiv:2603.19247v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into high-stakes applications, making robust safety guarantees a central practical and commercial concern. Existing safety evaluations predominantly rely on fixed collections of harmful prompts, implicitly assuming non-adaptive adversaries and thereby overlooking realistic attack scenarios in which inputs are iteratively refined to evade safeguards. In this work, we examine the vulnerabili

arXiv:2603.19272v1 Announce Type: cross Abstract: Differentiable Neural Computers (DNCs) were introduced as recurrent architectures equipped with an addressable external memory supporting differentiable read and write operations. Transformers, in contrast, are nominally feedforward architectures based on multi-head self-attention. In this work we give a formal derivation showing that a causal Transformer layer is exactly a stateless Differentiable Neural Computer (sDNC) where (1) the controller

arXiv:2603.19286v1 Announce Type: cross Abstract: Predicting stock prices presents challenges in financial forecasting. While traditional approaches such as ARIMA and RNNs are prevalent, recent developments in Large Language Models (LLMs) offer alternative methodologies. This paper introduces an approach that integrates LLMs with daily financial news for stock price prediction. To address the challenge of processing news data and identifying relevant content, we utilize stock name embeddings wi

arXiv:2603.19333v1 Announce Type: cross Abstract: Applying large language models (LLMs) to RTL code optimization for improved power, performance, and area (PPA) faces two key challenges: ensuring functional correctness of optimized designs despite LLM hallucination, and systematically prioritizing power reduction within the multi-objective PPA trade-off space. We propose POET (Power-Oriented Evolutionary Tuning), a framework that addresses both challenges. For functional correctness, POET intro

arXiv:2603.20122v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been widely deployed, especially through free Web-based applications that expose them to diverse user-generated inputs, including those from long-tail distributions such as low-resource languages and encrypted private data. This open-ended exposure increases the risk of jailbreak attacks that undermine model safety alignment. While recent studies have shown that leveraging long-tail distributions can facilitate

arXiv:2603.20179v1 Announce Type: cross Abstract: Large language model-based AI agents are now able to autonomously execute substantial portions of a high energy physics (HEP) analysis pipeline with minimal expert-curated input. Given access to a HEP dataset, an execution framework, and a corpus of prior experimental literature, we find that Claude Code succeeds in automating all stages of a typical analysis: event selection, background estimation, uncertainty quantification, statistical infere

arXiv:2601.03273v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become deeply embedded in daily life, the urgent need for safer moderation systems that distinguish between naive and harmful requests while upholding appropriate censorship boundaries has never been greater. While existing LLMs can detect dangerous or unsafe content, they often struggle with nuanced cases such as implicit offensiveness, subtle gender and racial biases, and jailbreak prompts, due to the su

NATO Secretary General Mark Rutte backed the Iran war and predicted the alliance would eventually come around to support it too.

Musk said his Terafab project — a grand plan to eventually manufacture his own chips for robotics, artificial intelligence and space data centers — will be built in Austin.

The current state of AI agent development is characterized by significant architectural fragmentation. Software devs building autonomous systems must generally commit to one of several competing ecosystems: LangChain, AutoGen, CrewAI, OpenAI Assistants, or the more recent Claude Code. Each of these ‘Five Frameworks’ utilizes a proprietary method for defining agent logic, memory persistence, and tool […] The post Meet GitAgent: The Docker for AI Agents that is Finally Solving the Fragmentation be

TLDR: Terafab will produce two chip types; one for Tesla and Optimus, and a space-hardened D3 variant for orbit. Solar panels in space run five times more efficiently, making orbital AI cheaper to operate than ground-based systems. A lunar electromagnetic mass driver could slash payload launch costs from $1,200 per pound to just dollars in [...] The post The Moon Is the New Data Center: Inside Musk’s Plan to Take AI Off-Planet appeared first on Blockonomi.