as in the title, my goal is to predicting failure and RUL of machine, dataset is timestamp and when machine is failure it will labeled with 1 that only have 56 https://preview.redd.it/plbydmenmm6h1.png?width=1205&format=png&auto=webp&s=2fefe3cc2e3fe554b81c9e0b4012c5345e73ec3f From this data im ditching operating hours and humidity because it didnt show correlation for machine failure, what algorithm or deeplearning suit for it? submitted by /u/False-Seesaw-1899 [link] [Kommentare]
A researcher claims he has already bypassed Claude Fable 5’s safety filters, exposing flaws in Anthropic’s guardrail system using multi-step AI prompts.
The panel awarded the Debt Algorand Standard Application (D-ASA) project for doing something the tokenized debt space has largely only promised: end-to-end execution of ACTUS contract logic directly on the Algorand Virtual Machine. Issuance, lifecycle events, settlement, transfers, and cashflows, all handled as verifiable, on-chain operations. Running. Judges specifically called out the asynchronous settlement design, role-based institutional controls, and native atomic transactions. The open-source SDK/framework packaging was highlighted as something banks and issuers could actually build on. They’ll have a credible, standards-aligned foundation for debt tokenization, ready to deploy. submitted by /u/semanticweb [link] [Kommentare]
