Agentic Machine Intelligence
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Causal Mirage Equilibrium in Agentic Machine Intelligence
arXiv:2606.03636v1 Announce Type: new Abstract: Classical game-theoretic solution concepts assume that agents' internal representations remain causally linked to external states. In generative machine intelligence, this assumption fails: semantic representations can decouple from physical reality, stabilizing into self-reinforcing, operationally robust configurations. This paper introduces the risk-sensitive mean-field-type \emph{Causal Mirage Equilibrium} (CME), a solution refined concept...
A Geometric Theory of Cognition for Machine Intelligence
Announce Type: replace Abstract: Developing artificial agents that unify representation, memory, adaptation, and prediction remains a fundamental challenge in artificial intelligence. Here we introduce a geometric framework in which cognitive computation emerges from Riemannian gradient flow on a learned latent manifold. The learned metric encodes representational constraints and computational preferences, while anisotropies in the geometry naturally generate multiple timescales of...
Russian spies are going after Western technology – they care less about being caught
Russian spies are going after Western technology – they care less about being caught Russia needs sanctioned computer technology and software updates for machine tools - Bookmark Russian intelligence agencies have grown more aggressive in their efforts to steal Western technology and defence secrets, as sanctions squeeze the country's wartime economy, three senior European intelligence officials have told The Associated Press. Moscow's agents are reportedly establishing shell companies,...
A Reliable Self-Organized Distributed Complex Network for Communication of Smart Agents
arXiv:2503.07702v3 Announce Type: replace Abstract: Collaboration among distributed agents is fundamental to many complex systems, particularly in communication networks where connectivity must be maintained under energy constraints. In this study, we utilize intelligent agents (nodes) trained through reinforcement learning techniques to establish connections with their neighbors, ultimately leading to the emergence of a large-scale communication cluster. Notably, there is no centralized...
The Last Evolution, by John W Campbell Jr. (1932)
The Project Gutenberg EBook of The Last Evolution, by John Wood Campbell This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org
Gemma 4 12B: A unified, encoder-free multimodal model
Introducing Gemma 4 12B: a unified, encoder-free multimodal model Today, we are introducing Gemma 4 12B, our latest model designed to bring agentic multimodal intelligence directly to laptops. Bridging the gap between our edge-friendly E4B and our more advanced 26B Mixture of Experts (MoE), Gemma 4 12B packages powerful capabilities inside a reduced memory footprint. It is also our first mid-sized model to feature native audio inputs.
Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification
Announce Type: new Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability benchmarking and production deployment. Post-deployment monitoring, human-in-the-loop controls, and prompt-level guardrails offer limited assurance once an agent is operating in production. We propose an ontology-grounded verification framework combining three components: an Agent Operational Envelope formalizing the...
Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification
arXiv:2606.04037v2 Announce Type: replace Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability benchmarking and production deployment. Post-deployment monitoring, human-in-the-loop controls, and prompt-level guardrails offer limited assurance once an agent is operating in production. We present an ontology-grounded verification framework -- to our knowledge the first to combine three...
Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery
arXiv:2606.08728v1 Announce Type: new Abstract: Mathematical reasoning has long served as a stringent test of machine intelligence; over the past decade, it has moved from a niche problem within NLP to one of the most consequential AI frontiers. This survey provides a unified account of the field's evolution, from early rule-based math word problem (MWP) solvers and template-driven geometry systems, through neural expression generation and LLM prompting, to contemporary reasoning models,...
AI Agents Enable Adaptive Computer Worms
arXiv:2606.03811v1 Announce Type: new Abstract: A computer worm is malware that spreads on a network by replicating itself from one machine to another. Traditional worms, like WannaCry, exploited predetermined vulnerabilities, and their spread can be halted by patching those vulnerabilities. Here we show that artificial intelligence (AI) agents enable a fundamentally new threat: a worm that generates tailored attack strategies to each target it encounters.