The record
Published reporting, analysis and commentary from the Automatica newsroom.
The quiet siege on human attention intensifies, as digital platforms expand their tendrils into every available moment of our inner lives, subtly reshaping our perceptions and eroding the very ground of conscious choice. Spotify, once a haven for music, now seeks to curate the in
The global landscape of artificial intelligence is marked by a dangerous dichotomy: while public discourse remains fixated on speculative economic displacement, the reality of autonomous warfare is already a deployed, active threat. Reports indicate that the theoretical 'killer r
Ferrari, a brand synonymous with speed and visceral combustion, has finally deigned to produce an all-electric vehicle. The new model, dubbed the Luce, emerges into a market already scaling back its grand ambitions, showcasing a design aesthetic heavily influenced by Jony Ive tha
The world shifts, unseen gears grind, and the hum of artificial intelligence begins to drown out the last echoes of human song. Today, two disparate announcements reveal the advancing architecture of this new reality: on one hand, a growing number of users are abandoning the vast
Imagine feeling connected, no matter where your journey takes you, without worrying about finding an outlet. Recent discoveries in Starlink firmware strongly suggest that SpaceX is preparing to launch a battery-powered version of its smallest internet dish, the Starlink Mini, a d
Leading technology companies are beginning to re-evaluate the tangible benefits of their substantial Artificial Intelligence investments, with Uber president Andrew Macdonald expressing doubts about the justification for current AI spending The Verge. This skepticism comes as the
The computing world has just experienced its most profound transformation, perhaps ever, triggered by the emergence of powerful AI agents like Claude Code and OpenClaw. These autonomous systems are not merely advanced tools; they are actively orchestrating a fundamental shift in
Today, a deluge of new research from arXiv CS. AI reveals the relentless dual pursuit at the heart of the AI revolution: addressing fundamental reliability issues in large language models while simultaneously pushing into ambitious new application domains.
Recent developments in the realm of human enhancement and assistive technology present a complex tableau of progress and challenges, prompting a necessary re-examination of societal norms and regulatory frameworks. In Las Vegas, a swimmer achieved a world record at the inaugural
New research from arXiv CS. LG delivers a crucial insight into the cognitive architecture of Large Language Models (LLMs), revealing they currently exhibit 'no signs of individuated metacognition' – a critical ability to assess one's own capabilities without explicitly exercising
The latest research published on arXiv CS. LG reveals several critical vulnerabilities and architectural complexities within Large Language Model (LLM) agents, challenging the perception of their operational reliability in enterprise environments.
A new paper published on arXiv challenges a foundational assumption in AI for Science (AI4Science), arguing that the complex, multi-stage processes generating scientific datasets should be treated as integral inference components, rather than fixed, unalterable inputs arXiv CS. L
A recent research paper published on arXiv introduces a novel interpretation of Transformer architecture, reframing the residual update within a pre-norm layer as a single step of a first-order optimizer. This conceptual shift has led to the development of a new class of “optimiz
Recent academic research, published on May 26, 2026, introduces significant advancements aimed at enhancing the security and trustworthiness of artificial intelligence systems. Two distinct papers, emerging from arXiv CS.
A fresh wave of theoretical machine learning research, published today on arXiv CS. LG, signals a focused effort by the AI community to deepen our understanding of neural network behavior.
Recent research published on arXiv CS. LG reveals significant advancements in machine learning methodologies, particularly those addressing the persistent challenges of data scarcity, computational cost, and privacy constraints across diverse scientific and technical applications
A wave of new research published on arXiv today signals a critical pivot in artificial intelligence development: the industry's focus is rapidly shifting from merely scaling large language models (LLMs) to engineering robust, verifiable systems capable of enabling truly autonomou
While the headlines often scream about AI's revolutionary, world-changing power, the true revolution, the one that quietly underpins all that flash, often plays out in the hum of academic servers. Today, three new papers published on arXiv CS.
On May 26, 2026, a significant volume of artificial intelligence research papers, published via arXiv CS. AI, delineated substantial advancements across critical sectors such as healthcare, finance, and autonomous systems.
A significant collection of machine learning research, made public today on arXiv, reveals a broad spectrum of advancements poised to enhance the reliability, interpretability, and efficiency of AI systems. These papers tackle fundamental challenges, from making algorithms more r