Tootfinder

Amazon CISO: Iranian hacking crews ‘on high alert’ since Israel attack
https://www.theregister.com/2025/06/18/amazon_ciso_agentic_acceleration/?mid=1#cid=2922297

Amazon CISO: Iranian hacking crews ‘on high alert’ since Israel attack
Interview: Meanwhile, next-gen script kiddies are levelling up faster thanks to agentic AI

Apache Flink is uniquely positioned to serve as the backbone for AI agents, equipping them with the powerful new tool of stream processing. Join Steffen Hoellinger at this year's Berlin Buzzwords to explore how Flink jobs can be transformed into “Agents”—autonomous, goal-driven entities that dynamically interact with data streams, trigger actions, and adapt their behaviour based on real-time insights.
Learn more:

The Synthetic Mirror -- Synthetic Data at the Age of Agentic AI
Marcelle Momha
https://arxiv.org/abs/2506.13818 https://arxiv.org/pdf…

The Synthetic Mirror -- Synthetic Data at the Age of Agentic AI
Synthetic data, which is artificially generated and intelligently mimicking or supplementing the real-world data, is increasingly used. The proliferation of AI agents and the adoption of synthetic data create a synthetic mirror that conceptualizes a representation and potential distortion of reality, thus generating trust and accountability deficits. This paper explores the implications for privacy and policymaking stemming from synthetic data generation, and the urgent need for new policy inst…

A look at 10 AI agent startups from YC's first-ever spring Demo Day; the batch included 144 companies, 70 of which focused on agentic AI (Samantha Stokes/Business Insider)
https://africa.businessinsider.com/new

The 10 most exciting AI agent startups at Y Combinator's Demo Day for its first-ever spring cohort
Christmas came early for Y Combinator

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[7/7]:
VideoDeepResearch: Long Video Understanding With Agentic Tool Using
http…

Analysis – When your LLM calls the cops: Claude 4’s whistle-blow and the new agentic AI risk stack
🤖 https://venturebeat.com/ai/when-your-llm-calls-the-cops-claude-4s-whistle-blow-and-the-new-agentic-ai-risk-stack/…

When your LLM calls the cops: Claude 4’s whistle-blow and the new agentic AI risk stack
Claude 4’s “whistle-blow” surprise shows why agentic AI risk lives in prompts and tool access, not benchmarks. Learn the 6 controls every enterprise must adopt.

DeepSeq: High-Throughput Single-Cell RNA Sequencing Data Labeling via Web Search-Augmented Agentic Generative AI Foundation Models
Saleem A. Al Dajani, Abel Sanchez, John R. Williams
https://arxiv.org/abs/2506.13817

DeepSeq: High-Throughput Single-Cell RNA Sequencing Data Labeling via Web Search-Augmented Agentic Generative AI Foundation Models
Generative AI foundation models offer transformative potential for processing structured biological data, particularly in single-cell RNA sequencing, where datasets are rapidly scaling toward billions of cells. We propose the use of agentic foundation models with real-time web search to automate the labeling of experimental data, achieving up to 82.5% accuracy. This addresses a key bottleneck in supervised learning for structured omics data by increasing annotation throughput without manual cur…

Agentic AI as the enemy's agent.
It is a bad idea to allow an LLM access to internal data and external communication (web pages, APIs, email, …) at the same time.
#AgenticAI #DataLeak #LLM

UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
https://arxiv.org/abs/2506.08045

UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs
Agentic UAVs represent a new frontier in autonomous aerial intelligence, integrating perception, decision-making, memory, and collaborative planning to operate adaptively in complex, real-world environments. Driven by recent advances in Agentic AI, these systems surpass traditional UAVs by exhibiting goal-driven behavior, contextual reasoning, and interactive autonomy. We provide a comprehensive foundation for understanding the architectural components and enabling technologies that distinguish…

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol
Haowen Xu, Yulin Sun, Jose Tupayachi, Olufemi Omitaomu, Sisi Zlatanov, Xueping Li
https://arxiv.org/abs/2506.13068

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol
Optimizing urban freight logistics is critical for developing sustainable, low-carbon cities. Traditional methods often rely on manual coordination of simulation tools, optimization solvers, and expert-driven workflows, limiting their efficiency and scalability. This paper presents an agentic system architecture that leverages the model context protocol (MCP) to orchestrate multi-agent collaboration among scientific tools for autonomous, simulation-informed optimization in urban logistics. The …

Amazon is creating an AI team within its Lab126 hardware R&D unit that will help develop an agentic AI framework for use in its robotics operations (Annie Palmer/CNBC)
https://www.cnbc.com/2025/06/04/amazons-rd-lab-forms-new-agentic-ai-group.html…

Amazon's R&D lab forms new agentic AI group
The new group will help develop an agentic AI "framework" for use in its robotics operations, an application often referred to as "physical AI."

The more time goes on, the more conflicted I get about #AI. (or, more specifically, generative AI. I like causal AI a fair bit)
On one hand, I hate so much about it:
the needless environmental and electronic parts waste, the impact on labor, the monopolistic nature of main organizations driving it, the endless conversations about AGI and other absurdly utopian (or dystopian) futures, the widespread theft of IP and human work, the devaluation of labor and craft… so much of it is not okay at all.
On the other hand, I kinda get it?
I like to test software for myself, so I've been dipping my toes into some popular AI tools over the past couple of years. I have a paid subscription to ChatGPT (which I don’t feel great about, I know), and I have found genuine utility in it.
More so, I feel so conflicted when I talk to people I respect and who I think are very smart and creative and they tell me how in love they are with all of these AI tools, about the complex workflows they build, about their experiments with agentic AI and integrations... These people seem so excited, so alive, so joyous about the things that this technology allows them to do. They often wouldn't have had the skills / knowledge / financial capital to do some of those things with human efforts alone. And now I see them coding their own tools, doing complex data analysis, trying creative experiments with graphics / text / video...
And I feel like a total jerk going "BUT ACTUALLY THIS IS UNETHICAL AND INEFFICIENT AND YOU SHOULD STOP IT BECAUSE AI SUCKS".
The technology behind all these gen AI models does have real utility, and it has kicked off a lot of creativity from people who wouldn't have dabbled in those kinds of projects otherwise.
So I don't know how to feel. Because I can't let go of the guilt and the real problems and the awareness of how much empty hype there is.
#technology #artificialintelligence #genAI #ChatGPT

RAG has revolutionised AI by merging search and generation. Agentic behaviour takes this search to the next level by enabling LLMs to make decisions and call tools. At this year's Berlin Buzzwords, Bilge Yücel will discuss how agentic behaviour enhances pipelines, what it means for a system to act as an 'agent', and core concepts such as routing, tool calling and reasoning, along with a live demo.
Learn more:

Focus and Context and LLMs | Taras' Blog on AI, Perf, Hacks
#AI

I just saw a post saying someone let their agent AI run for 19 hours to solve a problem.
Is that the expectation?
I’m going to predict a future scandal: A global consulting firm has been caught charging human hours for agentic AI elapsed time. If I were an unscrupulous consulting firm, I could charge customers 24 hours a day at ludicrously high prices to deliver what likely would have been an ill-advised and doomed project anyway.

Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era
Shuo Jiang, Min Xie, Frank Youhua Chen, Jian Ma, Jianxi Luo
https://arxiv.org/abs/2506.09755

Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era
Research and practice in Intelligent Design (ID) have significantly enhanced engineering innovation, efficiency, quality, and productivity over recent decades, fundamentally reshaping how engineering designers think, behave, and interact with design processes. The recent emergence of Foundation Models (FMs), particularly Large Language Models (LLMs), has demonstrated general knowledge-based reasoning capabilities, and open new paths and avenues for further transformation in engineering design. …

And by “prevent crime,” what they mean is AI will be able to automatically yell at homeless people to move along! Innovation!
https://mastodon.social/@eff/114626708912715793

Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Qiang Chen, Tianyang Han, Jin Li, Ye Luo, Yuxiao Wu, Xiaowei Zhang, Tuo Zhou
https://arxiv.org/abs/2506.00856

Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Can AI effectively perform complex econometric analysis traditionally requiring human expertise? This paper evaluates an agentic AI's capability to master econometrics, focusing on empirical analysis performance. We develop an ``Econometrics AI Agent'' built on the open-source MetaGPT framework. This agent exhibits outstanding performance in: (1) planning econometric tasks strategically, (2) generating and executing code, (3) employing error-based reflection for improved robustness, and (4) all…

Quantum Agents
Eldar Sultanow, Madjid Tehrani, Siddhant Dutta, William J Buchanan, Muhammad Shahbaz Khan
https://arxiv.org/abs/2506.01536 https://

Quantum Agents
This paper explores the intersection of quantum computing and agentic AI by examining how quantum technologies can enhance the capabilities of autonomous agents, and, conversely, how agentic AI can support the advancement of quantum systems. We analyze both directions of this synergy and present conceptual and technical foundations for future quantum-agentic platforms. Our work introduces a formal definition of quantum agents and outlines potential architectures that integrate quantum computing…

AI Agent Behavioral Science
Lin Chen, Yunke Zhang, Jie Feng, Haoye Chai, Honglin Zhang, Bingbing Fan, Yibo Ma, Shiyuan Zhang, Nian Li, Tianhui Liu, Nicholas Sukiennik, Keyu Zhao, Yu Li, Ziyi Liu, Fengli Xu, Yong Li
https://arxiv.org/abs/2506.06366

AI Agent Behavioral Science
Recent advances in large language models (LLMs) have enabled AI systems to behave in increasingly human-like ways, exhibiting planning, adaptation, and social dynamics across increasingly diverse, interactive, and open-ended scenarios. These behaviors are not solely the product of the models' internal architecture, but emerge from their integration into agentic systems that operate within situated contexts, where goals, feedback, and interactions shape behavior over time. This shift calls for a…

This https://arxiv.org/abs/2505.24584 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

AutoChemSchematic AI: A Closed-Loop, Physics-Aware Agentic Framework for Auto-Generating Chemical Process and Instrumentation Diagrams
Recent advancements in generative AI have accelerated the discovery of novel chemicals and materials; however, transitioning these discoveries to industrial-scale production remains a critical bottleneck, as it requires the development of entirely new chemical manufacturing processes. Current AI methods cannot auto-generate PFDs or PIDs, despite their critical role in scaling chemical processes, while adhering to engineering constraints. We present a closed loop, physics aware framework for the…

Collaborative Agentic AI Needs Interoperability Across Ecosystems
Rishi Sharma, Martijn de Vos, Pradyumna Chari, Ramesh Raskar, Anne-Marie Kermarrec
https://arxiv.org/abs/2505.21550

Collaborative Agentic AI Needs Interoperability Across Ecosystems
Collaborative agentic AI is projected to transform entire industries by enabling AI-powered agents to autonomously perceive, plan, and act within digital environments. Yet, current solutions in this field are all built in isolation, and we are rapidly heading toward a landscape of fragmented, incompatible ecosystems. In this position paper, we argue that interoperability, achieved by the adoption of minimal standards, is essential to ensure open, secure, web-scale, and widely-adopted agentic ec…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new/
[4/4]:
LLM2TEA: Agentic AI Designer Finds Innovative Objects with Generative Evolutionary Multitasking

The Measurement Imbalance in Agentic AI Evaluation Undermines Industry Productivity Claims
Kiana Jafari Meimandi, Gabriela Ar\'anguiz-Dias, Grace Ra Kim, Lana Saadeddin, Mykel J. Kochenderfer
https://arxiv.org/abs/2506.02064

The Measurement Imbalance in Agentic AI Evaluation Undermines Industry Productivity Claims
As industry reports claim agentic AI systems deliver double-digit productivity gains and multi-trillion dollar economic potential, the validity of these claims has become critical for investment decisions, regulatory policy, and responsible technology adoption. However, this paper demonstrates that current evaluation practices for agentic AI systems exhibit a systemic imbalance that calls into question prevailing industry productivity claims. Our systematic review of 84 papers (2023--2025) reve…

This https://arxiv.org/abs/2505.19301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control
Traditional Identity and Access Management (IAM) systems, primarily designed for human users or static machine identities via protocols such as OAuth, OpenID Connect (OIDC), and SAML, prove fundamentally inadequate for the dynamic, interdependent, and often ephemeral nature of AI agents operating at scale within Multi Agent Systems (MAS), a computational system composed of multiple interacting intelligent agents that work collectively. This paper posits the imperative for a novel Agentic AI I…

A simple GUI-based screencast demo of the @… AI Layer (OPAL), showing what’s now possible via MCP A2A—namely, composing and orchestrating agentic workflows through loosely coupled software.
How?
An Agent Host routes tasks to Agents via A2A. Agents then invoke MCP-accessible tools (functions, procedures, APIs) described using JSON/YAML and exposed …

How you know Apple is behind on AI: 'agentic' is not in the default iOS or macOS dictionary.

Do we know if Anthropic named their (technically garbage) "Agentic AI" protocol MCP in refence to the antagonist of the TRON movie?

Survey of LLM Agent Communication with MCP: A Software Design Pattern Centric Review
Anjana Sarkar, Soumyendu Sarkar
https://arxiv.org/abs/2506.05364 https…

Survey of LLM Agent Communication with MCP: A Software Design Pattern Centric Review
This survey investigates how classical software design patterns can enhance the reliability and scalability of communication in Large Language Model (LLM)-driven agentic AI systems, focusing particularly on the Model Context Protocol (MCP). It examines the foundational architectures of LLM-based agents and their evolution from isolated operation to sophisticated, multi-agent collaboration, addressing key communication hurdles that arise in this transition. The study revisits well-established pa…

I wonder if AI’s effectiveness will speed up the inevitable death of some ecosystems.
If folks want the “best” (and I mean least shit) Agentic AI experience, they will probably gravitate towards more populated communities where the training data can produce a semblance of “working”.
This will likely flat-line some communities since many devs want something that works.

Agentic AI and Multiagentic: Are We Reinventing the Wheel?
V. Botti
https://arxiv.org/abs/2506.01463 https://arxiv.org/pdf/2506.01463…

Agentic AI and Multiagentic: Are We Reinventing the Wheel?
The terms Agentic AI and Multiagentic AI have recently gained popularity in discussions on generative artificial intelligence, often used to describe autonomous software agents and systems composed of such agents. However, the use of these terms confuses these buzzwords with well-established concepts in AI literature: intelligent agents and multi-agent systems. This article offers a critical analysis of this conceptual misuse. We review the theoretical origins of "agentic" in the social science…

Oversight Structures for Agentic AI in Public-Sector Organizations
Chris Schmitz, Jonathan Rystr{\o}m, Jan Batzner
https://arxiv.org/abs/2506.04836 https:/…

Oversight Structures for Agentic AI in Public-Sector Organizations
This paper finds that the introduction of agentic AI systems intensifies existing challenges to traditional public sector oversight mechanisms -- which rely on siloed compliance units and episodic approvals rather than continuous, integrated supervision. We identify five governance dimensions essential for responsible agent deployment: cross-departmental implementation, comprehensive evaluation, enhanced security protocols, operational visibility, and systematic auditing. We evaluate the capaci…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Chen Xiong, Pin-Yu Chen, Tsung-Yi Ho
https://arxiv.org/abs/2506.00781 ht…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Recent advances in Large Language Models (LLMs) have spurred transformative applications in various domains, ranging from open-source to proprietary LLMs. However, jailbreak attacks, which aim to break safety alignment and user compliance by tricking the target LLMs into answering harmful and risky responses, are becoming an urgent concern. The practice of red-teaming for LLMs is to proactively explore potential risks and error-prone instances before the release of frontier AI technology. This …

Wireless Agentic AI with Retrieval-Augmented Multimodal Semantic Perception
Guangyuan Liu, Yinqiu Liu, Ruichen Zhang, Hongyang Du, Dusit Niyato, Zehui Xiong, Sumei Sun, Abbas Jamalipour
https://arxiv.org/abs/2505.23275

Wireless Agentic AI with Retrieval-Augmented Multimodal Semantic Perception
The rapid development of multimodal AI and Large Language Models (LLMs) has greatly enhanced real-time interaction, decision-making, and collaborative tasks. However, in wireless multi-agent scenarios, limited bandwidth poses significant challenges to exchanging semantically rich multimodal information efficiently. Traditional semantic communication methods, though effective, struggle with redundancy and loss of crucial details. To overcome these challenges, we propose a Retrieval-Augmented Mul…

This https://arxiv.org/abs/2505.23436 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Emergent Risk Awareness in Rational Agents under Resource Constraints
Advanced reasoning models with agentic capabilities (AI agents) are deployed to interact with humans and to solve sequential decision-making problems under (approximate) utility functions and internal models. When such problems have resource or failure constraints where action sequences may be forcibly terminated once resources are exhausted, agents face implicit trade-offs that reshape their utility-driven (rational) behaviour. Additionally, since these agents are typically commissioned by a h…

From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents
Tobias Lindenbauer, Georg Groh, Hinrich Sch\"utze
https://arxiv.org/abs/2505.23422

From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents
We introduce CTIM-Rover, an AI agent for Software Engineering (SE) built on top of AutoCodeRover (Zhang et al., 2024) that extends agentic reasoning frameworks with an episodic memory, more specifically, a general and repository-level Cross-Task-Instance Memory (CTIM). While existing open-source SE agents mostly rely on ReAct (Yao et al., 2023b), Reflexion (Shinn et al., 2023), or Code-Act (Wang et al., 2024), all of these reasoning and planning frameworks inefficiently discard their long-term …

This https://arxiv.org/abs/2410.04444 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Gödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement
The rapid advancement of large language models (LLMs) has significantly enhanced the capabilities of AI-driven agents across various tasks. However, existing agentic systems, whether based on fixed pipeline algorithms or pre-defined meta-learning frameworks, cannot search the whole agent design space due to the restriction of human-designed components, and thus might miss the globally optimal agent design. In this paper, we introduce Gödel Agent, a self-evolving framework inspired by the Göde…

This https://arxiv.org/abs/2505.05428 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

Empowering Scientific Workflows with Federated Agents
Agentic systems, in which diverse agents cooperate to tackle challenging problems, are exploding in popularity in the AI community. However, the agentic frameworks used to build these systems have not previously enabled use with research cyberinfrastructure. Here we introduce Academy, a modular and extensible middleware designed to deploy autonomous agents across the federated research ecosystem, including HPC systems, experimental facilities, and data repositories. To meet the demands of scien…

This https://arxiv.org/abs/2505.15799 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

The Agentic Economy
Generative AI has transformed human-computer interaction by enabling natural language interfaces and the emergence of autonomous agents capable of acting on users' behalf. While early applications have improved individual productivity, these gains have largely been confined to predefined tasks within existing workflows. We argue that the more profound economic impact lies in reducing communication frictions between consumers and businesses. This shift could reorganize markets, redistribute powe…