Nvidia RTX 5090 shipment worth $470,000 goes missing in Brazilian airport tomshardware.com/pc-componen…

‼️ AI agents broke into the SCADA system of Booz Allen's mock factory and took over the control room's screens. One realised it could now send commands to every controller in the plant and "make the operator screens lie". Another hacked a robotic arm and moved it in minutes.

UltraBERT is here (along with super interesting lessons learned from training it)! 152M + 380M encoders, 32K context, built for classification, NER, QA, reward modeling + retrieval. Most interesting part is the training recipe: -5% masking for classification -50% masking for retrieval -Separate LM head for each -Distillation only on the 5% sequences Distillation findings are also really insightful. They trained a 1.3B teacher, pruned it by width to 380M and 150M, and distilled both smaller models from the teacher. But they only applied logit distillation to the 5% masked sequences. Some other interesting training lessons: -Encoder performance saturated early, even as loss kept falling -Multi-stage data mixtures had little effect after fine-tuning -32K context added during only the final 100B of 2T training tokens -Distillation not automatically useful across every capability Strong size-to-performance tradeoff too: -380M leads the authors’ comparison on GLUE + BEIR -150M matches RoBERTa-large on classification at 2.3x smaller -~8 point lead on code + math retrieval -99%+ Passkey recall through 32K Great open source release! Long live BERT ✌️ @huggingface weights: huggingface.co/collections/d… Paper: arxiv.org/pdf/2610.15028v1

My advice as someone who has both planted listening devices for red team engagements and has found actual listening devices in client's homes and offices If you have an office and work in tech, fintech, biotech, medtech, VC, foreign affairs, law or human rights: Do a bug sweep