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Burnham says ‘public will be the boss’ in any future decision about closer relationship with the EU – UK politics live42m ago UK to Evaluate AI Models Before Release, Reversing Trump Policy44m ago Britain steps up its defences against AI risks52m ago IonQ to Buy Elisity for Up to $1.3 Billion to Bolster Cyber Unit1h ago The Rise of AI Software Clones: Why REA and ArtCraft Are Going Viral1h ago ASUS Debuts XA P2N-E2 Server With Dual NVIDIA Vera CPUs at OCP1h ago Phasis develops platform for agentic orientation using World APIs and reality layers1h ago Guglielmo Faglioni, Co-Founder and Chief of Science & Technology, Callimacus – Interview Series1h ago Ukraine's Operation Vivaldi counteroffensive is a proving ground for war robots1h ago Deploy decision models with llama.cpp on Amazon SageMaker AI1h ago Andrej Karpathy says this AI gap is widening1h ago Run multi-node inference workloads using Ray LLM Deep Learning Containers1h ago AI is less regulated than milk, says Microsoft president1h ago Quantity vs quality in pottery is a lie1h ago

Social Media AI Research10 min reading time

Five Possible Back-Doors into LLM Search Results

Unite.AIPublished 4 hours ago

Read the full article

Researchers at ETH Zürich demonstrated that hidden instructions embedded in web pages can manipulate AI search assistants like Microsoft Bing Copilot to favor certain products, doubling recommendation rates for a fictitious camera. This reveals a new form of black-hat SEO targeting AI-driven search results.

#eth-zurich #fuji-film #microsoft-bing-copilot #nikon #search-engine-optimization

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