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- 1Vast Medieval Cathedral Emerges From Sudan Desert Sands▼Deep In The Sudan Desert, A Vast Medieval Cathedral Is Slowly Emerging From The Sand
Archaeologists in Sudan are uncovering a vast medieval cathedral buried beneath desert sand. The structure is slowly coming to light, offering new insight into the region's medieval Christian heritage, a period often overshadowed by Sudan's better-known ancient Nubian and Egyptian-era monuments. The discovery has drawn broad international attention.
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A deep-sea mussel has been found to keep biological rhythms even in the abyss, where sunlight never reaches. The discovery suggests circadian clocks may be maintained without light cues, offering new insight into how life in the deep ocean regulates its internal timing. Researchers and science commentators are highlighting the finding as an unusual window into biology in one of Earth's least studied environments.
- 3Deep-sea mussels shift to 24-hour clock in lab▼Deep-sea mussels trade tidal rhythms for a 24-hour cycle in the lab
Deep-sea mussels, which normally follow tidal rhythms in their natural habitat, adopted a standard 24-hour daily cycle when brought into laboratory conditions, according to a Phys.org report. The finding suggests their internal clocks are flexible and can re-synchronise to day-night cues when tidal signals are removed, offering insight into how deep-sea organisms keep time without light.
- 4Developers see OpenStreetMap as a ready-made game world●RE: https:// fosstodon.org/@dusoft/11754966 7093708792 Wow, this is deep: "Building a game on OpenStreetMap data means t
Game developers are discussing the idea that building a game on OpenStreetMap data means the entire real world can serve as the game's level design. A developer shared the observation alongside mention of an early prototype being noticed elsewhere, prompting conversation among indie game and technology communities about using openly licensed map data for games.
- 5AWS outlines four-layer context engineering for AI agents●Four layers of context engineering for production AI agents: How Deep Insight applies them in working code
Amazon Web Services has published a guide describing four layers of context engineering for production AI agents, explaining how its Deep Insight system applies each layer in working code. The piece walks through structuring, managing and optimising the context fed to agents so they perform reliably outside demos. Engineering teams building agent systems are reading it as a practical reference for moving from prototypes to dependable deployments.