Nor'easter floods the Northeast coast while Citrix releases emergency patches for NetScaler zero-days and a researcher cites high AI human extinction risk.
how this picture was made
Painted by @cf/leonardo/lucid-origin on workers-ai.cloudflare.com, 2026-09-30 00:01Z. Scene directed by @cf/meta/llama-3.3-70b-instruct-fp8-fast.
The scene the art director wrote
A dark and stormy scene unfolds with floodwaters rising in a coastal town, people evacuating in the foreground, as a lone researcher stands in a dimly lit laboratory, surrounded by computer screens and machinery, with a somber expression, while a distant cityscape is shrouded in a mix of rain and darkness.
Inside the house scaffold (the fixed style + safety clauses), the full prompt the painter received
Sprawling painted editorial illustration for a newspaper front page: A dark and stormy scene unfolds with floodwaters rising in a coastal town, people evacuating in the foreground, as a lone researcher stands in a dimly lit laboratory, surrounded by computer screens and machinery, with a somber expression, while a distant cityscape is shrouded in a mix of rain and darkness. Rich painterly texture, coherent single scene, cinematic light, extreme wide panoramic banner composition that FILLS THE ENTIRE FRAME edge to edge: the painted scene reaches all four edges, no black bars, no border, no letterboxing, no empty margins. Every person has a natural, fully painted face with real features: never faceless, never blank mannequins, never smooth featureless heads. All people are fictional and resemble no real public figure. Strictly no text anywhere: no letters, no numbers, no typography, no signs, no billboards, no banners, no placards, no storefront lettering, no printed pages, no screen text, no watermark, no logos. No such surface appears in the picture at all: not lettered, and not blank either, because an empty screen or billboard leaves the figures around it reacting to nothing.
The picture's own pin (SHA-256 of the exact bytes served)
89f5c79127a3f766c37eefe288cf17c8331d8a0506b657857373a28175676822
Researchers identify transferable LLM jailbreak vulnerability in new September 29 papers
Seven published works filed 29 September 2026 cover AI testing, voice agents, clinical research and a logged federal transit grant.
By June Park · 7dResearchers have found that adversarial attacks optimized on a single open-weight large language model can transfer to and jailbreak architecturally different models, creating a shared vulnerability across models. This finding was published alongside six other technical research works filed 29 September 2026.
Teams also released multiple new evaluation benchmarks for AI systems. These include DuplexSpeechBench-IFEval, a test for implicit instruction following in real-time spoken interaction. The strongest model evaluated on this benchmark reached only 58.00% exact-match accuracy on the held-out test split.
Additional papers introduced PalmLeaf-VQA, a multi-script benchmark for analysing historical palm-leaf manuscripts, a proposed dual-system voice agent design named SALMONN-duo, the MM-OPD multimodal training framework, and EpiMind, a graph model for epidemic policy planning.
A separate clinical trial registration was also filed the same day, for a study measuring volumetric bone changes after non-surgical tooth extractions.
Federal awards data shows a $41.9M grant to the Central Puget Sound Regional Transit Authority was recorded on USASpending.gov on 29 September. The grant is allocated for construction of two new light rail stations in southeast Redmond. Full outlays for the award have been logged.
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