“AI is at best a functional mimic, not a conscious experiencing subject. …. The real moral issue lies not in making AI conscious …. but in avoiding transforming humans into zombies”
RESEARCH
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AI Outperforms Elite Runners: Controlled Conditions Reality Check
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AiScientist: Long-Horizon AI Research Agent for ML Tasks
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/5 Long-horizon AI research agents are mostly a state-management problem. Reasoning well for the next turn is not enough when ML research demands task setup, implementation, experiments, debugging, and evidence tracking over hours or days. This paper introduces AiScientist, a
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Anthropic Research Reveals Subliminal Learning in AI Model Training
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/4 Anthropic demonstrates subliminal learning where models inherit behavior from seemingly unrelated training data. Anthropic co-authors new research on subliminal learning, published in Nature. You train models on outputs from other models, assuming only visible content
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Cursor and NVIDIA Build Multi-Agent System Optimizing CUDA Kernels 38%
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/3 Cursor builds multi-agent system that optimizes CUDA kernels with 38% average speedup. Cursor, working with NVIDIA, develops a multi-agent system that writes and optimizes CUDA kernels automatically. In a three-week run across 235 real problems, the system improves
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Google Proposes Memory Caching to Extend RNN Long-Context Handling
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/2 Google gives RNNs growing memory so they can handle longer inputs without large compute increases. Google Research proposes Memory Caching (MC), a method that extends RNNs with memory that grows over time. Transformers solve long-context tasks using KV-cache but require
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TDM-R1: Fast AI Image Generator Learning from Human Feedback
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What if fast AI image generators could learn from simple human likes and object counts as easily as they learn from complex math? Researchers from HKUST, CUHK Shenzhen, and Xiaohongshu present TDM-R1 to do just that. Most lightning-fast AI models struggle to use real-world
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Strix GitHub and Shared Academic Paper
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Strix GitHub:
https://github.com/usestrix/strix Paper:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6372438
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Google DeepMind Reveals AI Agent Traps Framework
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Google DeepMind dropped a paper that should scare every agent builder. It's the first systematic framework for a threat that barely existed two years ago: adversarial content engineered to hijack AI agents browsing the web. They call them AI Agent Traps. The paper maps six
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Knowledge Graphs Empowering Business Decision Making
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Empowering #Business Decisions with a Knowledge Graphs by @antgrasso #EmergingTech #Innovation #Technology