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Early outputs of Muse Video model from Meta (3 minute read)
Meta's Muse Video model is now in closed beta. The model has native audio, and early outputs show strong detail and temporal consistency. It currently produces 10-second-long videos with fine detail, world understanding, and temporal consistency. Samples of videos generated by the model are available in the article.
Jun 12 | Blog
I Tried to Build a Context Layer for My Agent in a Weekend. Reader, I Did Not Build a Context Layer for My Agent in a Weekend.
A "simple" weekend project turns into real infrastructure, and why agent context deserves a boring, reliable foundation.
SponsoredAug 20 | Tech
Introducing the Half-Day: 0-Day in the Age of AI (12 minute read)
AI introduces a tremendous amount of volatility and uncertainty to a marketplace where all parties already assume significant risk. The number of exploits discovered by AI is growing fast. The introduction of models like Mythos has enabled the production of work at a rate that far outstrips that of any human researcher. However, this doesn't mean security researchers are out of a job. The role of a researcher can and should change with a changing landscape.
Aug 20 | Infosec
Breaking Secure Boot Without Breaking the Crypto (57 minute read)
A signature check alone doesn't prove a device is safe. This post breaks secure boot into four failure buckets: did the check run, did it cover the right bytes, was the signer authorized, and do those bytes still run at execution time? It walks through Qualcomm's PBL/XBL-SC/TME chain, Android Verified Boot, DICE key derivation, and RATS attestation roles. Real CVEs illustrate each bucket: CVE-2019-2278 let a rejected keystore still verify a boot image, CVE-2023-48425 chains an AVB failure into a full bypass on a retail Chromecast, and CVE-2021-1931 lets one signed image authorize a different one.
Aug 20 | Dev
Munder Difflin (GitHub Repo)
Munder Difflin is a desktop application that functions as a multi-agent harness, enabling users to run terminal-agent CLIs as self-coordinating entities, all managed by a central supervising agent named Michael. It has a visual interface where agents are represented as avatars within an office environment, with collaborative task management and memory retention across sessions.













































































































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