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Abstract We all know AI can find bugs. After a decade of research, I asked a harder question: can an autonomous system invent new attack techniques, and use them to hack live websites at scale? Buildi
Abstract We all know AI can find bugs. After a decade of research, I asked a harder question: can an autonomous system invent new attack techniques, and use them to hack live websites at scale? Buildi
Every day, Meta’s recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. In our 2024 post on sequence learning for ads recommendations, we showed how modeling the order and timing of user actions (rather than relying on static, manually engineered sparse features) [...] Read More... The post From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranki
"The models are forecasting something outside the envelope of anything we have ever observed."
Researchers are calling attention to the risks inherent in automated network device provisioning, using a world-leading device manufacturer as a case study.
Google's AI brain drain continues.
It was a Friday at 4:50 pm, the worst possible time for anything to go sideways when marketing flipped on a new AI summarization feature for the whole user base instead of the 5% rollout we'd agreed on. Traffic to our LLM service doubled in about four minutes. The autoscaler did exactly what it was told: it spun up three new replicas. What it didn't account for is that each replica needed almost three minutes just to pull a 14GB checkpoint and warm up CUDA kernels before it could answer a single
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