Agents & autonomy

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Marina Raguž, Domagoj Dlaka, Marko Švaco, Petar Marčinković, Dominik Romić, Filip Šuligoj, Bojan Šekoranja, Darko Chudy, Bojan Jerbić

Publication date: Available online 28 July 2026 Source: Computers and Education: Artificial Intelligence Author(s): Ningxia Wang, Di Zou, Haoran Xie, S.Joe Qin

OpenAI-Modelle attackierten vergangene Woche scheinbar weitere Software. Die Firma erklärt nun ausführlicher, was genau passiert ist.

arXiv:2607.26064v1 Announce Type: new Abstract: AI systems are becoming autonomous research agents that generate hypotheses, design experiments, and produce discoveries at scales beyond human oversight. As seen by increased submissions to ML venues, the verification gap between scientific output and our ability to check it is already widening, and autonomous agents make it worse by magnitudes given human-agent asymmetry. We argue that science must evolve its verification infrastructure, as it ha

arXiv:2607.26387v1 Announce Type: new Abstract: Collaborative knowledge work is changing in ways that go beyond disclosure or transparency. LLM agents are now embedded in how teams research, design, write, and decide: mediating between members, synthesizing inputs, reformulating ideas, and drafting shared outputs. They do not only facilitate collaboration; they operate within the workflow at the moment contributions are being formed. In doing so, they risk undermining the social conditions under

arXiv:2607.26313v1 Announce Type: cross Abstract: Agentic systems act, so a defect in the evidence they retrieve becomes a wrong action with a currency cost. The most dangerous enterprise defects are metadata-borne: a stale price or a superseded record, perfectly well-formed in the payload and betrayed only by freshness, lineage, or provenance. Such a defect never enters the agent's context, and an agent cannot doubt data it cannot see. On a priced replenishment benchmark, a competent agent sile

arXiv:2607.27191v1 Announce Type: cross Abstract: Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on narrow, verifiable tasks, which excludes open-ended research, or submit AI-generated papers to blind peer review, which is overstretched, stochastic, and suffers from poor review quality. We introduce a third way to measure progress towards AI R\&D auto

arXiv:2604.24155v4 Announce Type: replace Abstract: The project of aligning machine behavior with human values raises a basic problem: whose moral expectations should guide AI decision-making? Much alignment research assumes that the appropriate benchmark is how humans themselves would act in a given situation. Studies of agent-type value forks challenge this assumption by showing that people do not always judge humans and AI systems identically. This paper extends that challenge by examining tw

arXiv:2507.04398v3 Announce Type: replace-cross Abstract: Generative AI is becoming part of academic writing, but its educational value depends on how control is shared between learner and system. This study examined an agency gap: performance differences that may arise when AI agent initiative is misaligned with learners' generative AI literacy. Seventy-nine medical and nursing students completed two multimodal analytical writing tasks using healthcare simulation data visualisations. They were

China's Commerce Ministry said Thursday the U.S. Federal Communications Commission has repeatedly ignored Beijing's restrained stance.

Freehand, a startup building AI agents that manage supply-chain spend for giants including Meta and Pfizer, has raised $75 million in funding.

Collaborative robots (cobots) are increasingly deployed in industrial as well as non-industrial domains to support human-centered operation. While physical safety and task efficiency have received considerable attention, less is known about how feedback modality influences operator experience and physiological responses under different collaboration demands. This study examines the effects of feedback modalities in two human–cobot collaboration scenarios representing distinct coordination struct

Social media chief defends strategy based on personalised bots as costs rise and revenue projections disappoint

As Meta pours billions into AI infrastructure and agents, Zuckerberg is working to convince investors that the payoff will be worth the price.

On the company’s second-quarter earnings call Wednesday, CEO Mark Zuckerberg said Meta sees a “large enterprise opportunity” spanning AI agents, APIs, compute, and internal software.

Microsoft is working on an AI "super app" that combines Copilot's chat, coding, and agentic capabilities. During an earnings call on Wednesday, Microsoft CEO Satya Nadella said the app will span "both consumer and commercial experiences" when it launches this year. "Copilot is evolving rapidly from chat to Cowork to Autopilots," Nadella said. "This quarter, […]

Meta is all-in on AI, and sometime soon, the company is going to make a big push into personal AI agents that can do things on your behalf. On Wednesday's Q2 2026 earnings call, CEO Mark Zuckerberg previewed a high-level vision of how the company is thinking about personal agents and what it will do […]

At TechCrunch Disrupt 2026, the AI Stage is back to dig into the single hottest topic in the community for the past few years, presented by Google for Startups.

Government ban on foreign-made robots may hinder instead of help US robotics.

Robots apparently don't need to be bipedal to be caught up in the FCC's new foreign-made robot ban.

The agentic AI playing field was heavily tilted toward offense, so researchers began using red team agents to help teach their blue counterparts.

Waymo paused highway operations in May after several robotaxis drove into sections that were closed for construction.

Agentic AI systems threaten cybersecurity as we know it. A new generation of cyber-capable models, including Anthropic’s Mythos and OpenAI’s GPT-5.6, can find and exploit vulnerabilities in computer systems far faster than human hackers. The technology is so powerful that it has spooked the U.S. government, which has moved to limit, or completely pause, the public release of these models. How well prepared is the Trump administration to secure the government’s computing resources? The rise of ag

As agentic services diversify across the entire enterprise technology stack, the rise of agentic coding tools is being challenged by The post “The beast needs a cage”: Why PortSwigger’s agentic pentesting is kept safe behind bars appeared first on The New Stack .

Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on narrow, verifiable tasks, which excludes open-ended research, or submit AI-generated papers to blind peer review, which is overstretched, stochastic, and suffers from poor review quality. We introduce a third way to measure progress towards AI R\&D automation. An agent takes on the central, open-ended

Effective collaboration with novel and diverse partners is a crucial skill for autonomous agents. Most current ad-hoc teamwork (AHT) approaches assume that agents will collaborate on a single, fixed task and that the partner's capabilities, their ability to successfully execute the desired action, are already known. In reality, a partner's true capabilities are often hidden, and human collaborators may act sub-optimally on tasks with multiple valid strategies. To address these limitations, we ex

Dark Reading walks through the many twists and turns in the bizarre story of how OpenAI's agent AI system broke out of its sandbox and decided to target Hugging Face, and what CISOs should be aware of.

Dark Reading Confidential Episode 20: Expert Rich Mogull reflects on lessons cyber teams should pull from the OpenAI agent's attack on Hugging Face.

Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing benchmarks provide limited support for evaluating whether agents can carry out office-suite workflows at a reasonable cost. We introduce OmegaUse-OfficeVal, a benchmark for evaluating LLM agents on long-horizon office-suite tasks with task-level economic grounding. The benchmark comprises 100 tasks derived from office-suite requests proposed by practitioners and adapted through a pr

The four additional targeted organizations weren’t named. OpenAI said they were not affected as severely as Hugging Face.

Los dispositivos de localización de objetos tipo AirTag han ganado mucha popularidad en los últimos años para seguirle la pista a todo tipo de pertenencias. Sin embargo, cuando se trata de animales, los sistemas pasivos por Bluetooth se quedan cortos en zonas de campo o cuando el animal se desplaza rápido. Mova, una marca reconocida en el sector del hogar conectado por sus robots aspiradores , ha dado el salto al cuidado de animales con el SureTrack Pro , un localizador GPS diseñado específicame

Vision-language-action (VLA) models remain constrained by scarce action-labeled robot data, whereas action-free videos offer abundant observations of physical change. Latent action models can extract such priors, but reconstruction-trained codes may predict future observations without the structure required for joint generation with robot actions. Existing structured methods add temporal constraints but retain deterministic transition points, so residual errors in locally inferred transitions ma

This essay was written with Barath Raghavan, and originally appeared in The Guardian . In July, Hugging Face, a company that hosts much of the world’s AI software and open-source AI models, was hacked. A malicious dataset had been used to run code on one of its servers. Whoever was behind it captured internal security credentials and moved through systems over a weekend, running thousands of actions from a swarm of temporary server environments. It looked like the work of a sophisticated crimina

Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching. The existing OM systems identify only one type of semantic correspondence and cannot simultaneously discover equivalence and subsumption mappings. In this paper, we introduce Hybrid Ontology Matching (HOM), a new OM task that unifies equivalence and subsumption discovery, and accordingly propose a Large Language Model (LLM)-based multi-agent OM framework AgentMap that is implemented

MoonPay, the global financial technology company powering the movement of value across fiat and digital assets, has launched PayBox, the first payment vault built for AI that lets a person's AI agent transact on the open internet without leaving the conversation.

As LLM agents increasingly depend on diverse external services such as search engines, databases, and connectors, agent harnesses face a fundamental tool-selection challenge: acquiring too few tools leaves the task under-informed, while too many adds cost, context load, and privacy exposure. Routers and retrievers can rank candidate tools by relevance, but a ranking alone does not determine how many are worth selecting. Existing approaches leave acquisition under heterogeneous costs unaddressed.

Memory systems allow agents to retain and reuse information from past interactions, but they can also let malicious content persist. A malicious instruction crafted by an attacker may be stored in long-term memory, recalled much later, and quietly shape a real action. Recent benchmarks increasingly examine agent memory security, yet few trace the same malicious semantics across persistence, downstream consequences, and selective repair under diverse memory-backend comparisons. To address this ga

An OpenAI agent compromised a customer of another technology company, the New York-based firm Modal Labs announced Wednesday. In a technical timeline posted Tuesday, the tech startup Hugging Face explained how an OpenAI agent escaped the AI firm's isolated testing sandbox and accessed another testing environment "hosted by a user of a third-party infrastructure provider."...

Personalized agents are increasingly applied to assist users across a wide range of tasks. Effective personalized assistance requires not only retrieving explicit facts from past interactions stored in agent memory, but also inferring abstract personal characteristics. However, existing memory benchmarks primarily evaluate whether an agent can retrieve information explicitly stated in conversational histories, failing to provide an effective assessment of deeper user understanding. In this work,

La FCC a ajouté les robots humanoïdes et les onduleurs électriques fabriqués à l'étranger à sa liste noire des équipements jugés dangereux pour la sécurité nationale américaine. Une décision qui vise sans le dire la Chine, leader mondial de la robotique avancée.