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Stray cats're officially employed by the Lanzhou International Airport in China in a specially created "Rodent Control Department"
Every morning, airport staff send them out to "patrol" the grounds — the cats inspect baggage carousels, kitchens & storage areas for pests
Passengers can freely observe them through glass, which helps relieve pre-flight stress, as the airport staff says
To ensure the safety of allergy sufferers & those with animal phobias, direct contact in the terminal is prohibited
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Every morning, airport staff send them out to "patrol" the grounds — the cats inspect baggage carousels, kitchens & storage areas for pests
Passengers can freely observe them through glass, which helps relieve pre-flight stress, as the airport staff says
To ensure the safety of allergy sufferers & those with animal phobias, direct contact in the terminal is prohibited
🄳🄾🄾🄼🄿🤖🅂🅃🄸🄽🄶
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Tropical Storm Bertha is expected to make landfall today, bringing heavy rain, strong winds, and flooding from the Florida Panhandle to Louisiana.
The storm is producing up to 2.5 feet of storm surge and maximum sustained winds of nearly 60 mph as it moves about 50 miles offshore near the mouth of the Mississippi River, approaching southeastern Louisiana south of New Orleans.
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The storm is producing up to 2.5 feet of storm surge and maximum sustained winds of nearly 60 mph as it moves about 50 miles offshore near the mouth of the Mississippi River, approaching southeastern Louisiana south of New Orleans.
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This story (with 1.1M views) is completely FAKE, and a rage-bait scammer has won again.
The "drained wallet" doesn't exist.
He's just a serial scammer selling courses on:
> Wallet poisoning
> Rugging memecoins (including bragging about stealing money from a kid with cancer)
And, of course, fake giveaways
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The "drained wallet" doesn't exist.
He's just a serial scammer selling courses on:
> Wallet poisoning
> Rugging memecoins (including bragging about stealing money from a kid with cancer)
And, of course, fake giveaways
🄳🄾🄾🄼🄿🤖🅂🅃🄸🄽🄶
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It's official:
The US 30Y Note Yield has now traded above 5.00% for the longest stretch since 2007.
So far this year, the 30Y Note Yield has traded above 5.00% for 27 days, or ~19% of all trading sessions.
Just months ago, markets saw 3+ rate cuts in 2026.
Talk about a turn of events.
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The US 30Y Note Yield has now traded above 5.00% for the longest stretch since 2007.
So far this year, the 30Y Note Yield has traded above 5.00% for 27 days, or ~19% of all trading sessions.
Just months ago, markets saw 3+ rate cuts in 2026.
Talk about a turn of events.
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Gradient, jacobian, and hessian are really answering three different questions about a function. the gradient asks, “which direction should i move to increase this value the fastest?” the jacobian asks, “if i change the inputs a little, how do all the outputs change?” the hessian goes one level deeper and asks, “how is that direction itself changing?” once you see them as different layers of information instead of different equations, the notation becomes much less intimidating.
imagine you’re hiking up a mountain. the gradient points toward the steepest path uphill. now imagine the mountain itself is constantly changing shape as you walk. the hessian tells you whether the surface is flattening out, becoming steeper, or curving in another direction. the jacobian is slightly different. instead of a single mountain, imagine a machine with many knobs and many outputs. the jacobian tells you how every output responds when you turn each knob. it is the local map between inputs and outputs.
this is why these three ideas appear everywhere in robotics, optimization, computer vision, and machine learning. gradient descent uses the gradient to decide where to move. robot kinematics uses the jacobian to convert joint motion into end effector motion. second order optimization uses the hessian to understand curvature and converge faster. they are not separate mathematical tricks. they are different ways of asking how a system changes, and change is ultimately what engineering is trying to understand.
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imagine you’re hiking up a mountain. the gradient points toward the steepest path uphill. now imagine the mountain itself is constantly changing shape as you walk. the hessian tells you whether the surface is flattening out, becoming steeper, or curving in another direction. the jacobian is slightly different. instead of a single mountain, imagine a machine with many knobs and many outputs. the jacobian tells you how every output responds when you turn each knob. it is the local map between inputs and outputs.
this is why these three ideas appear everywhere in robotics, optimization, computer vision, and machine learning. gradient descent uses the gradient to decide where to move. robot kinematics uses the jacobian to convert joint motion into end effector motion. second order optimization uses the hessian to understand curvature and converge faster. they are not separate mathematical tricks. they are different ways of asking how a system changes, and change is ultimately what engineering is trying to understand.
🄳🄾🄾🄼🄿🤖🅂🅃🄸🄽🄶
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