An “AI trust crisis” triggered a 60% surge in VVV
A mathematician asked a question. Then VVV surged 60%.
Here’s what happened.
New York University mathematician Tristan Buckmaster and his collaborators fed the draft of their entire project into Codex—OpenAI’s coding model. They wanted it to help with some calculations.
Then he heard something: An internal OpenAI team had made similar progress in the same area.
So he asked directly: “Were my conversations used to train your models?”
The response was: The model did not access user data.
But as for the “training” part—there was no answer.
Later, OpenAI issued an official response, essentially denying that researchers or agents had accessed specific user data, but—
“Although unlikely, it cannot be ruled out.”
Think about that wording.
“Unlikely, but cannot be ruled out.”
Translated into plain English: “We didn’t look, but we can’t guarantee we didn’t.”
The community’s fear is real.
When the stakes are high enough, can these labs—OpenAI, Anthropic, Google—see all of your work and then produce the results before you do?
Buckmaster is no nobody. He is an NYU mathematician working on partial differential equations and fluid mechanics, and has published in Annals of Mathematics. Even he couldn’t get a clear answer.
What about you?
The things you type into ChatGPT every day—code, strategies, paper drafts, business plans—where do they go?
Someone has already given an answer with real money.
Trader based16z directly showed his positions: spot + perpetual contracts + OTC call options with a $25 strike price, all long VVV.
His logic is simple: This incident has made the importance of “private inference” widely understood. And among all the assets capturing this narrative, Venice is the most liquid.
He even compared VVV’s circulating market cap with ZEC’s situation when it was at $50.
How far did ZEC rise from $50? Look it up yourself.
So what exactly is Venice doing?
Venice AI, founded by Erik Voorhees, provides consumers with a chat application and developers with an API. Its selling point comes down to two words: privacy and fewer restrictions.
Privacy comes in four layers: anonymous mode hides your identity; zero-retention mode relies on the service provider’s discretion; TEE mode puts inference inside a protected hardware environment; and end-to-end encryption mode encrypts data from your device until it is decrypted inside the protected environment.
The business is already up and running.
Data disclosed by Banyan shows that Venice’s annualized revenue rose from $14 million in January this year to more than $100 million in August.
VVV is a token issued by Venice on Base. For every $100 of API credits purchased, $5 is used to buy back and burn VVV. On September 1, annual emissions had already fallen from 3 million tokens to 2.5 million, and on October 1 they will drop again to 2 million.
Revenue is rising. Supply is falling. Demand is increasing.
This is not the fundamental case for a “narrative token.”
But the truly painful question is not whether Venice is doing well.
It is: Why was this able to ignite the market?
Because AI is moving from “answering general-knowledge questions” to participating in academic papers, code, product development, and trading strategies.
Every word you type into the input box is becoming an exploitable asset.
In the past, when you asked AI, “What’s the weather like today?” nobody cared. Now, when you feed it the core strategy of a project or an unpublished paper draft—
you are feeding ammunition to a machine that may belong to a competitor.
OpenAI said, “Although unlikely, it cannot be ruled out.”
The market said: “Then I’ll solve it myself.”
VVV broke through $25 and briefly hit a new high. A 60% gain.
This is not hype.
This is the market’s first pricing of the product-market fit for “private inference.”
As AI grows more powerful, the things you entrust to it become more valuable—
whoever can let you use AI without showing your hand to others will win.
Venice has found its place.
VVV has simply put a price on that place.#Gate全球首发股票事件合约 #苹果发布会 #LAPTOP空投今晚开放 $BTC $ZEC $VVV
A mathematician asked a question. Then VVV surged 60%.
Here’s what happened.
New York University mathematician Tristan Buckmaster and his collaborators fed the draft of their entire project into Codex—OpenAI’s coding model. They wanted it to help with some calculations.
Then he heard something: An internal OpenAI team had made similar progress in the same area.
So he asked directly: “Were my conversations used to train your models?”
The response was: The model did not access user data.
But as for the “training” part—there was no answer.
Later, OpenAI issued an official response, essentially denying that researchers or agents had accessed specific user data, but—
“Although unlikely, it cannot be ruled out.”
Think about that wording.
“Unlikely, but cannot be ruled out.”
Translated into plain English: “We didn’t look, but we can’t guarantee we didn’t.”
The community’s fear is real.
When the stakes are high enough, can these labs—OpenAI, Anthropic, Google—see all of your work and then produce the results before you do?
Buckmaster is no nobody. He is an NYU mathematician working on partial differential equations and fluid mechanics, and has published in Annals of Mathematics. Even he couldn’t get a clear answer.
What about you?
The things you type into ChatGPT every day—code, strategies, paper drafts, business plans—where do they go?
Someone has already given an answer with real money.
Trader based16z directly showed his positions: spot + perpetual contracts + OTC call options with a $25 strike price, all long VVV.
His logic is simple: This incident has made the importance of “private inference” widely understood. And among all the assets capturing this narrative, Venice is the most liquid.
He even compared VVV’s circulating market cap with ZEC’s situation when it was at $50.
How far did ZEC rise from $50? Look it up yourself.
So what exactly is Venice doing?
Venice AI, founded by Erik Voorhees, provides consumers with a chat application and developers with an API. Its selling point comes down to two words: privacy and fewer restrictions.
Privacy comes in four layers: anonymous mode hides your identity; zero-retention mode relies on the service provider’s discretion; TEE mode puts inference inside a protected hardware environment; and end-to-end encryption mode encrypts data from your device until it is decrypted inside the protected environment.
The business is already up and running.
Data disclosed by Banyan shows that Venice’s annualized revenue rose from $14 million in January this year to more than $100 million in August.
VVV is a token issued by Venice on Base. For every $100 of API credits purchased, $5 is used to buy back and burn VVV. On September 1, annual emissions had already fallen from 3 million tokens to 2.5 million, and on October 1 they will drop again to 2 million.
Revenue is rising. Supply is falling. Demand is increasing.
This is not the fundamental case for a “narrative token.”
But the truly painful question is not whether Venice is doing well.
It is: Why was this able to ignite the market?
Because AI is moving from “answering general-knowledge questions” to participating in academic papers, code, product development, and trading strategies.
Every word you type into the input box is becoming an exploitable asset.
In the past, when you asked AI, “What’s the weather like today?” nobody cared. Now, when you feed it the core strategy of a project or an unpublished paper draft—
you are feeding ammunition to a machine that may belong to a competitor.
OpenAI said, “Although unlikely, it cannot be ruled out.”
The market said: “Then I’ll solve it myself.”
VVV broke through $25 and briefly hit a new high. A 60% gain.
This is not hype.
This is the market’s first pricing of the product-market fit for “private inference.”
As AI grows more powerful, the things you entrust to it become more valuable—
whoever can let you use AI without showing your hand to others will win.
Venice has found its place.
VVV has simply put a price on that place.#Gate全球首发股票事件合约 #苹果发布会 #LAPTOP空投今晚开放 $BTC $ZEC $VVV
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