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SAHAR

@sahar_music_official

3 months ago

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Posted On: August 14th 2026, 05:36 pm

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A little flashback to the dancefloor at Frau Holle @club.frauholle back in May. 🖤✨

Next stop → SAHAR @ DJANGO & FRIENDS at DEEP 2.0 🔥 @deep2.0_magdeburg

Melodic House → Tech House → Melodic Techno → Techno

Behind the decks:
DJANGO × CFAMER_CF @cfamer_cf × SAHAR (Destination Rec. | HH) @destinationrecordings

📅 Saturday, 15.08.2026 | 23:00
📍 DEEP 2.0 | Breiter Weg 231 | Magdeburg

See you on the dancefloor. 🖤

#MelodicTechno #MelodicHouse #techno #Magdeburg #club

Comments (2)

3 months ago

peterbunkrad

3 months ago

euphoria_dnb

Nice 👏🔥👏

Pyaar ( love) da hi duja naam punjab sajna ❤️

#lovegill #lovegillkalakar #lovekelovelies #lovegillbiggboss20
Outfit from @vedhanacreation
Jewellery from @orionjewels__

باز هم تاکید میکنم نگذارید سرتون کلاه بگذارند این توهین ها چه در انزلی و چه در تبریز کلاه گذاشتنه
#تبریز #تراکتور #انزل #شمال

Across the shaking, shrapnel-torn cargo bay, Snake Eyes doesn’t even blink. He stands over the smoking, mangled carcass of a second drone, his movements fluid, silent, and utterly lethal. His dark tactical suit is stained with the crimson of his own resurrected blood, but his focus is locked entirely onto the final intruder creeping up the cargo ramp. On his left wrist, the matte-black GSD 5 watch has stopped glowing its miraculous golden light, returning to its true form: a heavy, unreflective weapon of pure, cold-blooded stealth. The dark PVD coating completely absorbs the chaotic red emergency strobes, looking like a black hole strapped to his arm.
The surviving Vehicon sentry raises a high-caliber plasma rifle, aiming it squarely at the target. Snake moves like a shadow. Before the machine can pull the trigger, the commando is inside its guard. He drives his left fist forward in a brutal, short-range piston punch. The massive, PVD-coated steel case of the GSD connects directly with the side of the drone’s primary optic sensor.
SHATTER.
The sheer structural density of the GSD acts exactly like a knuckle-duster. The armored glass of the drone’s eye explodes inward in a spray of pressurized blue fluid. The machine lets out a high-pitched, digitized shriek of structural agony, its weapon firing blindly into the ceiling. Snake loops his left arm around the drone’s neck casing, the heavy, rugged tactical strap of the watch biting deep into the synthetic neck cables to give him a vice-like grip. With his right hand free, he draws his heavy trench knife and drives the thick blade upward, straight through the soft under-armor of the drone’s jaw, twisting it with force until the internal logic boards short-circuit in a shower of sparks.

With one final shove, he kicks the deactivated hulk backward. The metal corpse tumbles off the open cargo ramp, falling thousands of feet into the swirling whe abyss of the blizzard. The cargo door finally groans shut, sealing the area in pitch darkness, save for the faint, reassuring glow of the Super-LumiNova markers on Snake Eyes’ GSD. Survival achieved. For now.
#watchaddict #watchcollector #watchuseek #luxurywatches #instawatch

Linköping University professor Peter Jonsson is set to have his work presented in two weeks’ time at one of the most prestigious conferences in theoretical computer science. As of Monday, much of that work is “dead,” he says, after AI showed that a 27-year-old hypothesis underpinning it is wrong.

Both OpenAI and Anthropic claimed this week to have disproved the exponential time hypothesis (ETH). Vast swaths of theoretical computer science research on complexity and algorithm design have been built on the premise that the effort it takes to solve certain problems increases exponentially with the size of the problem.

Jonsson expects his predicament will be “very common” at the IEEE Symposium on Foundations of Computer Science, where his work will be presented by one of his coauthors. “People will start the talks: ‘ETH is false, half of my paper does not work,’” he says. It’s a vexing problem, Jonsson says, “but at the same time, we learn a lot from it. And this is what science is about.”

Researchers haven’t independently verified, let alone had time to fully understand, the AI-produced proofs, which both firms have published on GitHub in both natural language and its machine-checkable Lean format. OpenAI has asked the UC Santa Barbara computer scientists who originally proposed the hypothesis, plus an MIT academic who has refuted a version of ETH, to rally researchers to unpack the proofs. So far, this effort includes a Google form asking for volunteers and feedback, and a commitment from OpenAI to fund a conference on the topic.

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oldie but goodie 🫰🏼✨

@induremgmt x @sonderinc1

SAHAR

@sahar_music_official

peterbunkrad

euphoria_dnb

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