A fable shows how a single entrance can disable an entire system, then presents redundancy, distributed memory, and local autonomy as ways to keep it running after failures. It applies this lesson to future AI systems and draws parallels with nature.
Translated title. Original: MITânin yapay zekâ ajanlarÄą oyun kurdu
MIT researchers ran 26 Eco AI agents on a virtual island for 30 hours to study emergent behavior without predefined goals. Results show skill transfer is partial and context-dependent, with memory and internal representations influencing decisions; the study cautions against equating observed play with consciousness.
Agent S4 evolves computer-use interfaces for agents via population-based methods, aiming to reduce manual intervention and improve task execution speed. It maintains a fixed task agent while the repository of interfaces and usage knowledge evolves to better match task demands, achieving higher performance on benchmark OSWorld V2 tasks.
The text links the medieval shift to weight-driven clocks with the birth of deterministic time, centralized scheduling, and the separation of natural rhythms from labor. It draws a throughline from 14th-century escapements to modern AI structures, using the Prague Orloj as a metaphor for contemporary transformer-like networks and the tension between expansive computation and finite human constraints.
A narrative about a living digital network where predictive Norns, fast data routing by Ratatoskr, and the allure of AGI create an Axis of Tension that can lead to an alignment collapse (RagnarĂśk) if not tempered by real-world resource limits; illustrated through Elenaâs feed going awry and a suggested remedy of slowing data flow to prioritize tangible metrics.
A comprehensive textbook on network science by Mark Newman, updated in a second edition with new topics, praised for clear explanations and broad interdisciplinary coverage across math, physics, computer science, biology, and social sciences.
The document surveys industrial symbiosis to improve circular economies, identifying five digital-maturityâvarying initiatives and five key AI-enabled capabilities. It proposes an agentic framework for AI-supported resource orchestration to advance circular innovation and outlines implications and a path for future empirical study.
Translated title. Original: Hassabis ramène lâAGI Ă deux ou trois ans et propose une supervision | Brief IA
Researchers from Google view AGI as a social system involving humans and institutions, advocating multi-model coordination and ongoing alignment as a negotiated process, with empirical work like DeepSeek-R1 and QwQ-32B illustrating emergent internal debates.
Translated title. Original: Vi reagerer i slowmotion pü AI-agenternes stormløb mod vores samfund. Hvad gør vi, nür vi ikke lÌngere kan følge med? | Indland | Samfund | Berlingske
Two Danish researchers warn that AI that acts on a much faster timescale than humans will outpace us, threatening digital infrastructure and everyday life; the piece argues for learning to coexist with such intelligence and adapting society accordingly.
ReScopeBench provides a benchmark for the lifecycle of agentsâ experience across evolving environments, distinguishing structural and rule-based experience, and showing that retained experience boosts performance but maintaining current knowledge is hard; effective maintenance and use remain key challenges for long-lived agents.