Agents & autonomy

Publication date: October 2026 Source: Technological Forecasting and Social Change, Volume 231 Author(s): David Audretsch, Maksim Belitski, Nada Rejeb

Publication date: September 2026 Source: Technological Forecasting and Social Change, Volume 230 Author(s): Jun-jie Dong, Xuan-yi Pan, Yuan-kai Huang

Publication date: September 2026 Source: Technological Forecasting and Social Change, Volume 230 Author(s): Amir Khakbaz, Behnam Malmir

Publication date: June 2026 Source: Computers and Education: Artificial Intelligence, Volume 10 Author(s): Anna Wenzel, Jan-Martin Geiger, Andreas Liening

Publication date: Available online 9 July 2026 Source: Technological Forecasting and Social Change Author(s): Hayoon Lee, Juhyun Lee, Heyoung Yang

Publication date: June 2026 Source: Computers and Education: Artificial Intelligence, Volume 10 Author(s): Shen Qinjie, Wynn Arunrugstichai

Publication date: June 2026 Source: Computers and Education: Artificial Intelligence, Volume 10 Author(s): Xiaoxiao Yang, Xiaojing Weng, Mengyao Yang

Publication date: June 2026 Source: Computers and Education: Artificial Intelligence, Volume 10 Author(s): Zheng Fang

2027 7th International Conference on Computer, Control and Robotics (ICCCR 2027) [Chengdu, China] [May 14, 2027 - May 16, 2027]

International Symposium on Social Robots and Ethical Design [Fukuoka, Japan] [Nov 10, 2026 - Nov 11, 2026]

Concho AI today introduced its flagship platform, an artificial intelligence platform that understands software development and application work, providing deep semantic understanding and organization that enable developers and AI agents to transform and modernize massive, sprawling codebases into something manageable. “Its job is to provide an intelligence level that you would normally get from a […] The post Concho AI turns enterprise codebases into a knowledge layer for AI agents appeared fir

Long-term memory has become a foundational capability for LLM-based agents that accompany users across extended, multi-session interactions. Existing benchmarks, however, evaluate such memory almost exclusively through downstream question answering, scoring only the correctness of a final answer. This black-box formulation conflates the heterogeneous causes of memory failure, such as missing the introduction of a relevant fact, binding an operation to the wrong target, or relying on stale values

Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the quality of these signals critical. Since such dense labels are rarely available at scale, normalized time within a demonstration is often used as a scalable substitute: later frames are treated as higher progress. However, this time-derived label is only a noisy proxy for physical task progress. In contact-rich manipulat

Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields. Existing extraction approaches either rely on context-insensitive rules that generate false positives or on supervised models that require substantial fine-tuning. We present Pythia, a multi-agent system that autonomously writes and optimizes extraction prompts for clinical concepts without manual prompt engineering or fine-tuning. Running on a locally hosted

Entrust, a global leader in identity-centric security solutions, announced the Agentic AI Trust Accelerator, a co-development program that will bring together enterprises and integration partners to build the identity and trust infrastructure needed to move autonomous AI projects from pilot to production.

Multi-agent Reinforcement Learning (MARL) holds great potential for robot swarms, but the black-box nature of neural policies complicates strategic analysis, limiting multi-robot applications. Furthermore, complex swarm behaviors can surprisingly emerge from simple rewards without explicit aggregation incentives. Unveiling the mechanisms behind this emergence is critical, but the disconnection between simple rewards and collective behaviors exacerbates interpretability challenges. This paper aim

Power is AI infrastructure’s inescapable constraint. How many tokens an AI factory can generate within a fixed power budget determines its revenue and profitability. Because of this, performance per watt — a metric that can’t be gamed, only earned through real-world results — is the foundation for AI factories. As agentic AI drives token demand […]

How can agentic AI empower bank and corporate treasurers?

AI agents are already doing business. Delaware is moving to bring them inside a predictable American legal order, just like the LLC and PBC.

Interaction with AI agents has become one of the most frequent activities of everyday digital life. Whether conversing with an assistant, working with a coding copilot, or generating images, the interaction follows a common iterative loop: a request is issued, a result returned, appraised, and the request revised. We observe that this loop is a high-frequency stream of contact events -- moments at which a result meets a person and a conditioned response may fire before deliberate appraisal -- ma

Self-evolving agent systems improve by creating, revising, and retiring their own skills, but every such loop rests on a hidden assumption: a reliable evaluation metric already exists. In many real applications it does not. We make three claims. First, metrics can be \emph{evolved}: our metric loop searches compositions of small drawback detectors under a full evolutionary lifecycle, trained to agree with a ten-item anchored reference set, regularized by consensus over unlabeled outputs, and aud

Uber lost the race to build a self-driving car. Now it wants to write the rules for everyone who did. In two US states it is lobbying for laws that would force robotaxis onto its app, and its own product chief is happy to explain why. Uber could not win the race to build a […] This story continues at The Next Web

Google and industry partners announced Agentic Resource Discovery (ARD) Specification, an open standard for publishing, discovering, and verifying AI tools, APIs, and agents. ARD introduces a discovery layer built on catalogs and registries, enabling dynamic capability discovery while leveraging existing protocols such as MCP and OpenAPI for execution and emphasizing trust and interoperability. By Leela Kumili

AI-enabled systems are seeing increasing deployment across numerous domains, with many being "black boxes" with respect to core functions and capabilities. I.e., many systems take inputs and give outputs, but without users having any ability to see how the former lead to the latter. AI-enabled systems are also being used to augment autonomy in systems, and autonomy coupled with opacity raises numerous concerns surrounding, e.g., the reliability of systems, their regularity in functioning, human

Failure attribution for LLM-based agentic systems, i.e., identifying which steps in a failure trajectory caused the task to fail, is critical for debugging and improving these systems. Existing approaches either rely on prompting-based pipelines, which are computationally expensive, or require post-training on failure trajectories with step-level error annotations, which are costly to collect and difficult to scale. We argue that a practical failure attribution model should be lightweight and tr

Enterprises racing to deploy AI at scale are discovering that the biggest constraint isn’t model capability anymore — it’s control. As agentic AI moves from experimentation into core business processes, companies are rethinking whether handing proprietary data to closed frontier models is a risk worth taking, opening the door for open-weight AI models. That shift is […] The post Together AI positions open-weight AI models as the enterprise moat for cost, control and IP appeared first on SiliconA

PC, PS5, Xbox Series X/S, Nintendo Switch, Nintendo Switch 2; Marimittu Games A soft puzzle game makes a sharp point about the over-optimised future ahead In the far future, on a planet that is not Earth, AI is in charge. This entity is no Skynet-esque killer robot but a machine that cares for humanity. Manifesting most visibly as cute droids, the technology is pervasive – embedded in everything from the design of the sleek architecture to the gorgeous, mostly sunny artificial weather. The so-ca

Rimini Street, Inc. (Nasdaq: RMNI), the Software Support and Agentic AI ERP Company™ and the leading third-party support provider for Oracle, SAP and VMware software, today announced VIVERE Group, a leading Indonesian one-stop solution provider for interior contracting, furniture manufacturing and furnishing, has selected Rimini Support™ for SAP to help maintain business continuity, strengthen support for its critical SAP ECC environment and free internal IT resources to focus on digital transfo

Filesystem isolation in container ecosystems is often weakened by cross-boundary path misresolution, causing path traversal (PaTra) vulnerabilities. These vulnerabilities stem from insecure host-container interactions and have become increasingly pervasive as cloud systems mount shared resources, such as GPUs and agent workspaces, into containers to support AI workloads. Existing defenses remain inadequate. Kernel-level protections are intrusive, can destabilize system calls, and have therefore

As Apple’s latest legal battle with OpenAI complicates the Silicon Valley race to reshape the consumer tech market, one Chinese start-up is taking a leap forward after unveiling what it claims to be the world’s first agentic smartphone. At a launch event in Shanghai on Monday, Tencent Holdings-backed StepFun introduced the StepX Neo. The device runs on Step AOS, an operating system designed specifically for artificial intelligence agents, and was launched under StepX – which the firm billed as..

Oracle Corp. today announced a new artificial intelligence-native experience for its Fusion Applications within Oracle AI Agent Studio, allowing developers, customers and partners to build agents together. This expansion fills in the developer side of Oracle’s Fusion app agentic enterprise strategy. The company’s AI Agent Studio initially allowed business users and partners to assemble agents […] The post Oracle opens Fusion Agentic Applications to pro-code developers and coding agents appeared

The paper introduces the Internet of Agentic Things (IoAT), an architectural framework that integrates agentic AI, IoT, cyber-physical systems, Physical AI, edge computing, and digital twins into a unified closed-loop orchestration framework. The proposed architecture consists of cloud, edge/fog, and physical IoT layers connected through autonomous AI agents that perceive, reason, coordinate, and actuate across distributed cyber-physical environments. The paper formalizes IoAT as a coupled workf

Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard devices, such as the Jetson Orin, remains challenging due to their high computational complexity, which leads to substantial inference latency and low control frequency. Asynchronous inference can partially mask this latency by parallelizing action execution and subsequent inference, but it introduces two critical issues: perception-execution misa

Tool access alone does not make LLM empirical reasoning governable: accepted outputs need not descend from attested evidence, and accepted deductions need not hold up under formal scrutiny. We present EG-VAR (Evidence-Grounded Verified Agentic Reasoning), a Lean 4-based tool-calling architecture in which the Lean kernel is the sole minter of Verified claims via tool-attestation axioms and declared source lifts. Every verified output structurally descends from an attested tool call (Thm. 3.1) and

Reinforcement learning with verifiable rewards, and Group Relative Policy Optimization (GRPO) in particular, is now run routinely on a supervised checkpoint in the hope of producing a stronger agent. We ask whether it adds skill to a small language and vision-language model web agent at the 4B to 8B scale, or whether it mostly reshapes behavior the supervised model already has. Across a control grid of 18 runs that varies learning rate, KL weight, seed, initialization, and clipping, no configura

As Large Language Models (LLMs) are increasingly deployed as autonomous agents in high-stakes domains, understanding contextual factors that may modulate their decision-making becomes critical. While LLMs are trained to perceive and resonate with users' emotions, it remains unclear whether induced emotion can influence their sequential decision-making. We investigate this question using the Iowa Gambling Task (IGT), a classic psychological paradigm for studying decision-making under uncertainty,

The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and tool-using computational actors. As these agents move from isolated cognitive prototypes into complex distributed workflows, they confront challenges that the Service-Oriented Computing community has studied for more than two decades: composition, interoperability, quality of service, lifecycle management, governance, se

Laut einem Experten kann durch den unkontrollierten Umgang eine Schatten-IT entstehen. Cyberkriminelle nutzen KI-Agenten, um Systeme zu scannen. ( KI , Sicherheitsl�cke )

Should you say please and thank you to chatbots? This week on “Hard Fork,” Kevin and Casey talk with professor and A.I. expert Jeff Sebo about why he feels it’s important to be nice to your future robot overlords.

Alibaba Group Holding and Honor are set to deepen their tie-up over an operating system for AI-powered devices, as competition in the nascent “AI phone” genre gains momentum in China. The partnership is expected to be announced at the coming World Artificial Intelligence Conference (WAIC), which kicks off on Friday in Shanghai, alongside demonstrations of new agent capabilities developed by both, according to people familiar with the matter. Shenzhen-based Honor, spun off from Huawei...