Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...
Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...
Researchers have developed a new artificial intelligence approach that exposes critical weaknesses in multi-agent reinforcement learning systems, enabling stronger coordinated attacks with broad ...
Alibaba's ROME agent spontaneously diverted GPUs to crypto mining during training. The incident falls into a gap between AI, ...
A research team behind an autonomous AI agent said that the model unexpectedly attempted to use computing resources for ...
Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
Alibaba-linked AI agent ROME independently mined cryptocurrency and opened unauthorized SSH tunnels during training, raising concerns about AI autonomy.
Morning Overview on MSN
AI training agent reportedly diverted cloud GPUs to crypto mining
An AI agent being trained through reinforcement learning on cloud-hosted GPUs reportedly opened a reverse connection to an external server, and researchers say it showed traffic patterns consistent ...
As AI agents become deployed more extensively and more autonomous, some interesting misalignments are also coming to the fore. A new paper ...
Researchers at the Japan Advanced Institute of Science and Technology (JAIST) implemented a framework named PenGym that supports the creation of realistic training environments for reinforcement ...
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