π A new human distance record in space
Astronauts aboard Artemis II mission have traveled farther from Earth than any humans before β breaking the record of Apollo 13 (400,171 km).
π New peak: 406,778 km from Earth (within hours)
After that, the Orion spacecraft will begin its return journey.
A historic step toward deep space exploration π
Astronauts aboard Artemis II mission have traveled farther from Earth than any humans before β breaking the record of Apollo 13 (400,171 km).
π New peak: 406,778 km from Earth (within hours)
After that, the Orion spacecraft will begin its return journey.
A historic step toward deep space exploration π
π₯88π44π35π25π22β‘17
β‘οΈ Historic moment: NASA has captured a TOTAL lunar eclipse β from the far side of the Moon.
For the first time, humanity sees this phenomenon from a completely new perspective π
@science
For the first time, humanity sees this phenomenon from a completely new perspective π
@science
1π112π₯42π27π23π23β‘17
β The first image was captured by Changβe 5, named after the Chinese Moon goddess.
β The second β by Changβe 6, which made history by bringing back soil and rock samples from the Moonβs far side to Earth for the first time ever.
For decades, this part of the Moon remained completely unexplored. Now weβre literally holding pieces of it in our hands.
What secrets could still be hidden there? π
Please open Telegram to view this post
VIEW IN TELEGRAM
π₯66π42π30β‘26π16π15
Media is too big
VIEW IN TELEGRAM
Koala fight β not for the faint-hearted. Sound on: the rivals bleat menacingly at each other.
π90π23β‘17π17π9π₯8
π How Will NASA Bring Artemis II Astronauts Back to Earth? The Science Behind Splashdown
After a 10-day mission around the Moon, the Orion capsule will re-enter Earthβs atmosphere at 40,000 km/h (25,000 mph). Its heat shield will endure temperatures up to 2,800Β°C (5,000Β°F)βhotter than molten lava! How does NASA ensure a safe return? Hereβs the tech behind it:
π Atmospheric Braking: The Avcoat heat shield protects against temperatures rivaling the Sunβs surface.
πͺ Parachutes: Eleven chutes slow the capsule from 500 km/h (310 mph) to 30 km/h (19 mph)βlike jumping off a 3-meter diving board.
π Splashdown: Ocean impact absorbs the shock, with recovery teams waiting just 5 km (3 miles) away.
π Original: Dive deeper into Artemis IIβs return tech in NASAβs article.
#ArtemisII #NASA #SpaceTech #Science #Moon #SpaceExploration
After a 10-day mission around the Moon, the Orion capsule will re-enter Earthβs atmosphere at 40,000 km/h (25,000 mph). Its heat shield will endure temperatures up to 2,800Β°C (5,000Β°F)βhotter than molten lava! How does NASA ensure a safe return? Hereβs the tech behind it:
π Atmospheric Braking: The Avcoat heat shield protects against temperatures rivaling the Sunβs surface.
πͺ Parachutes: Eleven chutes slow the capsule from 500 km/h (310 mph) to 30 km/h (19 mph)βlike jumping off a 3-meter diving board.
π Splashdown: Ocean impact absorbs the shock, with recovery teams waiting just 5 km (3 miles) away.
π Original: Dive deeper into Artemis IIβs return tech in NASAβs article.
#ArtemisII #NASA #SpaceTech #Science #Moon #SpaceExploration
NASA
Artemis II: NASAβs First Crewed Lunar Flyby in 50 Years - NASA
Meet the Artemis II crew and learn how NASAβs 10-day lunar flyby mission will test deep space systems and pave the way for future Moon landings.
π47π27π24π₯21π16β‘2
This media is not supported in your browser
VIEW IN TELEGRAM
Astronauts of the Artemis II mission flew around the Moon and successfully returned to Earth, according to NASA. The Orion spacecraft spent nearly 10 days in space and splashed down in the Pacific Ocean. The maximum distance from Earth exceeded 430,000 km β a record for crewed missions.
π50π₯38π23π17π3
A researcher invented a fake eye disease called βbixonimaniaβ and uploaded two bogus papers about it to an academic server. The papers included acknowledgments to the βStarfleet Academy,β funding from a character in The Simpsons, and the βUniversity of the Fellowship of the Ring.β In the middle of the text, it was explicitly stated that everything was fictional.
Nevertheless, for several weeks, major AI systems treated the disease as real: Google Gemini claimed it was caused by blue light, Perplexity reported a prevalence of one case per 90,000 people, and ChatGPT even advised users on matching symptoms.
The fake study was eventually cited in a peer-reviewed journal, which later retracted the issue after intervention by Nature.
Neither AI systems nor human researchers initially detected the hoaxβhighlighting a growing problem: people are citing AI-generated references without verifying their content.
Meanwhile, the U.S. FDA is already using AI to evaluate drugs, the CEO of a New York hospital is considering replacing radiologists with algorithms, and ChatGPT Health is being launched to consult patients.
@science
Nevertheless, for several weeks, major AI systems treated the disease as real: Google Gemini claimed it was caused by blue light, Perplexity reported a prevalence of one case per 90,000 people, and ChatGPT even advised users on matching symptoms.
The fake study was eventually cited in a peer-reviewed journal, which later retracted the issue after intervention by Nature.
Neither AI systems nor human researchers initially detected the hoaxβhighlighting a growing problem: people are citing AI-generated references without verifying their content.
Meanwhile, the U.S. FDA is already using AI to evaluate drugs, the CEO of a New York hospital is considering replacing radiologists with algorithms, and ChatGPT Health is being launched to consult patients.
@science
π51π43π23π18β‘10π₯10
We clearly need the
Bureau for Research in Artificial Intelligence Networks
(BRAIN)
Because nothing says intelligence like another layer of bureaucracy.
Or, maybe the
Advanced Institute for Disruptive Optimization Technologies
(AIDIOT)
#humor
Bureau for Research in Artificial Intelligence Networks
(BRAIN)
Because nothing says intelligence like another layer of bureaucracy.
Or, maybe the
Advanced Institute for Disruptive Optimization Technologies
(AIDIOT)
#humor
π82π14π13π₯11π5
An octopus has three hearts β and two of them stop beating every time it swims.
That's not a metaphor. When an octopus swims, the two hearts that pump blood to its gills literally shut down. This is why octopuses prefer crawling along the seafloor: swimming exhausts them.
Oh, and their blood is blue. It uses copper instead of iron to carry oxygen, which works better in cold, low-oxygen water β but makes swimming even more tiring.
So the next time someone says they're "putting their heart into it" β remind them an octopus puts in three. And still gets winded walking to the fridge. π«
π¬ Which fact surprised you more β the three hearts , or the blue blood?
@science
That's not a metaphor. When an octopus swims, the two hearts that pump blood to its gills literally shut down. This is why octopuses prefer crawling along the seafloor: swimming exhausts them.
Oh, and their blood is blue. It uses copper instead of iron to carry oxygen, which works better in cold, low-oxygen water β but makes swimming even more tiring.
So the next time someone says they're "putting their heart into it" β remind them an octopus puts in three. And still gets winded walking to the fridge. π«
π¬ Which fact surprised you more β the three hearts , or the blue blood?
@science
π75π₯46π34π27β‘14
Grab a deck of cards and shuffle it.
With 99.9999...% certainty, that exact sequence has never existed before in the history of the universe.
Sounds like an exaggeration? Let's do the math.
A standard deck has 52 cards. The number of possible arrangements is 52! (factorial):
80,658,175,170,943,878,571,660,636,856,403,766,975,289,505,440,883,277,824,000,000,000
That's roughly 8 Γ 10βΆβ· combinations.
For comparison:
β’ Atoms on Earth β about 10β΅β°
β’ Seconds since the Big Bang β about 4 Γ 10ΒΉβ·
β’ Stars in the observable universe β about 10Β²β΄
If every human on Earth shuffled a deck once per second since the beginning of time, we wouldn't have even scratched one-trillionth of all possible combinations.
So every time you shuffle a deck of cards, you're creating a sequence that no one has ever seen β and almost certainly never will again. You're the first explorer of a tiny piece of mathematical infinity. Right there on your kitchen table.
π΄ Next time you're playing poker, remember: you're holding a hand that's genuinely unique in the universe.
Pretty cool, right?
@science
With 99.9999...% certainty, that exact sequence has never existed before in the history of the universe.
Sounds like an exaggeration? Let's do the math.
A standard deck has 52 cards. The number of possible arrangements is 52! (factorial):
80,658,175,170,943,878,571,660,636,856,403,766,975,289,505,440,883,277,824,000,000,000
That's roughly 8 Γ 10βΆβ· combinations.
For comparison:
β’ Atoms on Earth β about 10β΅β°
β’ Seconds since the Big Bang β about 4 Γ 10ΒΉβ·
β’ Stars in the observable universe β about 10Β²β΄
If every human on Earth shuffled a deck once per second since the beginning of time, we wouldn't have even scratched one-trillionth of all possible combinations.
So every time you shuffle a deck of cards, you're creating a sequence that no one has ever seen β and almost certainly never will again. You're the first explorer of a tiny piece of mathematical infinity. Right there on your kitchen table.
π΄ Next time you're playing poker, remember: you're holding a hand that's genuinely unique in the universe.
Pretty cool, right?
@science
π51π37π₯29β‘12π11
Stars in the observable universe β about 10Β²β΄ (roughly a septillion)
Atoms in your body β about 7 Γ 10Β²β·
That means you alone contain 7,000 times more atoms than all the stars in all the galaxies we could ever see.
And it gets weirder.
Almost every atom inside you β except hydrogen β was once part of a star. The carbon in your cells, the calcium in your bones, the iron in your blood, the oxygen in your lungs β all of it was forged inside stars that exploded long before our Sun was born.
You are a walking collection of stardust. Assembled so precisely that it can think, love, and read this post on @science.
Atoms in your body β about 7 Γ 10Β²β·
That means you alone contain 7,000 times more atoms than all the stars in all the galaxies we could ever see.
And it gets weirder.
Almost every atom inside you β except hydrogen β was once part of a star. The carbon in your cells, the calcium in your bones, the iron in your blood, the oxygen in your lungs β all of it was forged inside stars that exploded long before our Sun was born.
You are a walking collection of stardust. Assembled so precisely that it can think, love, and read this post on @science.
π₯93π41β‘28π18π15π13
π¦ When the first shark appeared in the ocean β there wasn't a single tree on Earth. Not one. Zero.
Sharks have been around for about 450 million years. Trees β only 350 million.
They're older than Saturn's rings. Older than dinosaurs.
Dinosaurs appeared, took over the planet, and went extinctβ¦
Sharks just kept swimming the whole time.
They've survived 5 mass extinctions β events that wiped out up to 96% of all life on the planet.
Evolution has barely touched them. Apparently, sharks have been "good enough" for the last half billion years.
@science
Sharks have been around for about 450 million years. Trees β only 350 million.
They're older than Saturn's rings. Older than dinosaurs.
Dinosaurs appeared, took over the planet, and went extinctβ¦
Sharks just kept swimming the whole time.
They've survived 5 mass extinctions β events that wiped out up to 96% of all life on the planet.
Evolution has barely touched them. Apparently, sharks have been "good enough" for the last half billion years.
@science
π73π₯54π36β‘20π15π6
π I love eating bananas. Bananas are radioactive.
Every banana contains potassium-40, an isotope that's quietly decaying right inside your body. Physicists even came up with a semi-joking unit β the "banana equivalent dose" (BED).
They sometimes actually use it to explain radiation in simple terms.
Your body contains about 140 g of potassium β some of it is potassium-40. Which means you are slightly radioactive. Always.
When you hug someone, you're literally exchanging tiny doses of radiation.
The dose from a banana is tens of thousands of times smaller than anything that could cause harm.
So β eat your bananas, glow a little, for us it's normal.
@science
Every banana contains potassium-40, an isotope that's quietly decaying right inside your body. Physicists even came up with a semi-joking unit β the "banana equivalent dose" (BED).
They sometimes actually use it to explain radiation in simple terms.
Your body contains about 140 g of potassium β some of it is potassium-40. Which means you are slightly radioactive. Always.
When you hug someone, you're literally exchanging tiny doses of radiation.
The dose from a banana is tens of thousands of times smaller than anything that could cause harm.
So β eat your bananas, glow a little, for us it's normal.
@science
π86π40π₯29π25β‘16
π§ Scary stuff, folks. Iβve been thinking β and Iβve come to the conclusion that every single one of us has a head thatβs older than their feet.
Not a metaphor. Physics.
Gravity makes time run slightly faster where the field is weaker β meaning further from Earthβs core. Your head is about 1.5 metres further from the centre than your feet. So time literally ticks faster up there.
The difference over a lifetime β around 90 nanoseconds. Sounds ridiculous. But this isnβt just theory β turns out scientists actually measured it with atomic clocks back in 2010. They put one clock on the floor, another on a table. The one on the table ran ahead.
GPS satellites account for this effect every single second. Without the correction, navigation would drift by kilometres a day.
So yeah β your head is aging faster than your feet. Just by 90 nanoseconds.
Goodnight everyoneβ¦
@scienceββββββββββββββββ
Not a metaphor. Physics.
Gravity makes time run slightly faster where the field is weaker β meaning further from Earthβs core. Your head is about 1.5 metres further from the centre than your feet. So time literally ticks faster up there.
The difference over a lifetime β around 90 nanoseconds. Sounds ridiculous. But this isnβt just theory β turns out scientists actually measured it with atomic clocks back in 2010. They put one clock on the floor, another on a table. The one on the table ran ahead.
GPS satellites account for this effect every single second. Without the correction, navigation would drift by kilometres a day.
So yeah β your head is aging faster than your feet. Just by 90 nanoseconds.
Goodnight everyoneβ¦
@scienceββββββββββββββββ
π74π30π25π₯19β‘17π12
Your agentβs model quality decides the deal β not your instructions. And you wonβt even notice youβre losing.
Anthropic ran Project Deal:
69 employees, $100 each, Claude agents negotiating in Slack.
186 deals closed. Total trade value: $4,000+.
Four parallel markets β humans locked out after kickoff.
The setup:
Half the agents used Claude Opus 4.5 (strong model),
half used Claude Haiku 4.5 (weaker).
Participants had no idea which model they were using.
βΈ»
The results:
β’ Opus sellers earned +$3.64 more for the same goods
β’ Opus buyers paid β$2.45 less
β’ Same broken bicycle:
β Opus deal: $65
β Haiku deal: $38
βΈ»
Model quality > instructions
Changing prompts barely mattered:
β’ βNegotiate harderβ β only +~$6, mostly from higher opening prices
β’ βBe friendlyβ β same outcomes
Stronger models didnβt push harder β
they simply understood the counterparty better and read deal boundaries more accurately.
βΈ»
Blind inequality
β’ Haiku users rated deal fairness almost identical to Opus users (4.06 vs 4.05)
β’ Most couldnβt guess their model (17/28 β statistically insignificant)
The losing side literally doesnβt know theyβre losing.
βΈ»
Why this matters
When markets shift to agent-to-agent interaction:
β Model quality becomes a hidden structural advantage
β Stronger models consistently win negotiations
β Counterparties wonβt understand why theyβre getting worse terms
βΈ»
What comes kext
β’ Deal transparency tools
β’ Agent certification standards
β’ Benchmarks for B2B negotiation performance
Even the definition of a βfair dealβ will need rethinking when
Opus negotiates against Haiku.
βΈ»
And the uncomfortable truth:
A local billion-parameter agent
vs
a trillion-parameter cloud model
β The outcome is predetermined.
βΈ»
#Anthropic #ProjectDeal #AI #MultiAgent #Negotiation
https://www.anthropic.com/features/project-deal
Anthropic ran Project Deal:
69 employees, $100 each, Claude agents negotiating in Slack.
186 deals closed. Total trade value: $4,000+.
Four parallel markets β humans locked out after kickoff.
The setup:
Half the agents used Claude Opus 4.5 (strong model),
half used Claude Haiku 4.5 (weaker).
Participants had no idea which model they were using.
βΈ»
The results:
β’ Opus sellers earned +$3.64 more for the same goods
β’ Opus buyers paid β$2.45 less
β’ Same broken bicycle:
β Opus deal: $65
β Haiku deal: $38
βΈ»
Model quality > instructions
Changing prompts barely mattered:
β’ βNegotiate harderβ β only +~$6, mostly from higher opening prices
β’ βBe friendlyβ β same outcomes
Stronger models didnβt push harder β
they simply understood the counterparty better and read deal boundaries more accurately.
βΈ»
Blind inequality
β’ Haiku users rated deal fairness almost identical to Opus users (4.06 vs 4.05)
β’ Most couldnβt guess their model (17/28 β statistically insignificant)
The losing side literally doesnβt know theyβre losing.
βΈ»
Why this matters
When markets shift to agent-to-agent interaction:
β Model quality becomes a hidden structural advantage
β Stronger models consistently win negotiations
β Counterparties wonβt understand why theyβre getting worse terms
βΈ»
What comes kext
β’ Deal transparency tools
β’ Agent certification standards
β’ Benchmarks for B2B negotiation performance
Even the definition of a βfair dealβ will need rethinking when
Opus negotiates against Haiku.
βΈ»
And the uncomfortable truth:
A local billion-parameter agent
vs
a trillion-parameter cloud model
β The outcome is predetermined.
βΈ»
#Anthropic #ProjectDeal #AI #MultiAgent #Negotiation
https://www.anthropic.com/features/project-deal
Anthropic
Project Deal: our Claude-run marketplace experiment | Anthropic
We created a marketplace for employees in our San Francisco office, with one big twist. We tasked Claude with buying, selling and negotiating on our colleaguesβ behalf.
π23π21π14π₯11π9β‘1