T1

Yes，T1

[T1 @MikeX1g]

The Jacobi conjecture still needs human verification; AI reasoning is merely a dimension designed by humans. Thank you. Have humans been ruled by AI? Wake up, you great geniuses! You seem to be contemplating whether a drop of water falling from the sky can kill someone—it's ridiculous! 🥸

[T1 @MikeX1g]

base sol bas 还有什么

[T1 @MikeX1g]

@Irenezhao_ 砸

[T1 @MikeX1g]

@evmdotchat 哈哈哈哈😂

[T1 @MikeX1g]

@JuanRezzio @EasyA_Kickstart 🤣

[T1 @MikeX1g]

@JuanRezzio @EasyA_Kickstart 🤣

[Toby Langford @Bangford]

See The Amazing Jacobian-Breaking Levent Alpoge Transformation Working On A 15x15 Cube (Mesmerising)

x -> (1+xy)^3 z + y^2 (1+xy) (4+3xy)
y -> y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy)
z -> 2 x - 3 x^2 y - x^3 z)

has Jacobian determinant -2.

[T1 @MikeX1g]

5UoWzex7rVky9ZSHGQXQgAPsm8jDZQMFBGqch8L7pump

[Mustafa @oprydai]

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.

[T1 @MikeX1g]

5UoWzex7rVky9ZSHGQXQgAPsm8jDZQMFBGqch8L7pump

[Przemek Chojecki | PC @prz_chojecki]

Wow, this is really big. Jacobian conjecture is really well-known and tried by thousands of mathematicians.

Even a simple one-line counterexample will give raise to a lot of new exciting mathematics.

AI math is thriving.

[T1 @MikeX1g]

@kevinroose 5UoWzex7rVky9ZSHGQXQgAPsm8jDZQMFBGqch8L7pump

[T1 @MikeX1g]

@tjshibata @jacksongrove @juliusai 5UoWzex7rVky9ZSHGQXQgAPsm8jDZQMFBGqch8L7pump

[T1 @MikeX1g]

@Iliad_research 5UoWzex7rVky9ZSHGQXQgAPsm8jDZQMFBGqch8L7pump

[Bartosz Naskręcki @nasqret]

Pretty excited about this :)

This summer feels like it will be a season of harvest. I don't think it's a coincidence that we are seeing so many results emerge in formal domains close to algebra.

Algebra is particularly well suited to large-scale experiments with AI, and it may become one of the fields in which AI systems make their most spectacular advances. We've just seen a remarkable AI-assisted counterexample to the Jacobian conjecture, and more algebraic results are beginning to mature.

Algebra is a formal language whose syntax can encode an extraordinary amount of intuition. I'm incredibly excited by the results I've been able to gather recently.

Seeing the shape of a theory emerge makes you stop and stare, like looking into a dark sky, noticing individual stars, and suddenly perceiving the immense body of the galaxy that holds them together. Stay tuned!

[T1 @MikeX1g]

继续

[Tyler @tjshibata]

I asked @jacksongrove to help me understand jacobian conjecture and he made an explainer video using @juliusai with 3Blue 1Brown's open source animation library

[T1 @MikeX1g]

@a16z solana:5UoWzex7rVky9ZSHGQXQgAPsm8jDZQMFBGqch8L7pump

[T1 @MikeX1g]

@QT9277 脏啊这个，内俩老头也来玩

[T1 @MikeX1g]

$JACOBIAN 的特殊性：
• 它是首个直接绑定真实数学重大事件（Jacobian Conjecture 被 AI 辅助证伪）的病毒式 Meme 币。
• 该事件本身（2026 年 7 月 Levent Alpöge + Claude Fable）在数学圈和 X 平台爆火，属于实时热点叙事，让它迅速成为“数学 Meme”的代表。
• 在 https://t.co/FFgWzPhavH 生态中，它可能是第一个真正意义上的“数学主题”爆款尝试，之前 Solana Meme 主流还是动物（狗、猫）、名人、政治等题材。

[T1 @MikeX1g]

AI without labels and for reference only is a human tool scam. @elonmusk

[T1 @MikeX1g]

AI reasoning needs to be labeled with "For reference only" and is not a final conclusion. Without this labeling, it becomes a tool for human extinction.

[T1 @MikeX1g]

The Jacobi conjecture still needs human verification; AI reasoning is merely a dimension designed by humans. Thank you. Have humans been ruled by AI? Wake up, you great geniuses! You seem to be contemplating whether a drop of water falling from the sky can kill someone—it's ridiculous! 🥸

[Bojan Tunguz @tunguz]

I am working on a math/algo research project. I am primarily using GPT 5.6 Ultra. Every day or two I ask Fable to write me a report about how the project is progressing. Then I turn over the report to Codex, and invariably Codex tells me that Fable's report is painting an overly rosy picture of the progress. LOL

[T1 @MikeX1g]

The Jacobi conjecture still needs human verification; AI reasoning is merely a dimension designed by humans. Thank you. Have humans been ruled by AI? Wake up, you great geniuses! You seem to be contemplating whether a drop of water falling from the sky can kill someone—it's ridiculous! 🥸

[Joe Shipman @joe_shipman]

(1/2)
Read the chat log. It’s impossible to maintain that this AI doesn’t “understand” the problem it solved.

In my own chats with Claude Fable I observed the same—the AI sometimes provides insight that improves my own understanding.