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I've noticed that starting a group chat is easy. Keeping people engaged six months later is much harder. The more I study decentralized AI, the more I think the industry may be facing the same problem. What if intelligence isn't the hardest thing to build anymore? Models are improving rapidly. Compute is becoming more accessible. Open source capabilities continue to close gaps that once looked impossible to cross. Technology attracts attention. But networks survive because people continue contributing long after the technology stops feeling new. Someone has to provide compute. Someone has to contribute models. Someone has to build applications, verification systems, and infrastructure that make the network more useful than it was yesterday. That's why I've become interested in @OpenGradient . What stands out to me isn't the intelligence itself. It's whether a network can keep attracting contributors after the initial excitement fades. More than 263,500 wallets have interacted with the network, over 100 developers have contributed models, and more than 2,000 models are already hosted. Those metrics don't tell me which model is smartest. They tell me something potentially more important: participation is compounding. The hidden tradeoff is that intelligence can often be scaled with more compute, more data, and better models. Coordination is different. It requires incentives, trust, verification, and long term alignment between participants who may never know each other. The paradox is that if AI succeeds in making intelligence abundant, intelligence itself may become a commodity. Coordination may become the layer that determines which AI networks survive. History is full of technologies that worked. The ones that transformed industries became ecosystems like Opengradient. So as decentralized AI evolves, should we spend less time asking which model is smartest and more time asking which network can sustain participation for the next decade? #OPG $OPG $SYN $BEL
I've noticed that starting a group chat is easy.
Keeping people engaged six months later is much harder.
The more I study decentralized AI, the more I think the industry may be facing the same problem.
What if intelligence isn't the hardest thing to build anymore?
Models are improving rapidly. Compute is becoming more accessible. Open source capabilities continue to close gaps that once looked impossible to cross.
Technology attracts attention.
But networks survive because people continue contributing long after the technology stops feeling new.
Someone has to provide compute. Someone has to contribute models. Someone has to build applications, verification systems, and infrastructure that make the network more useful than it was yesterday.
That's why I've become interested in @OpenGradient .
What stands out to me isn't the intelligence itself. It's whether a network can keep attracting contributors after the initial excitement fades. More than 263,500 wallets have interacted with the network, over 100 developers have contributed models, and more than 2,000 models are already hosted.
Those metrics don't tell me which model is smartest.
They tell me something potentially more important: participation is compounding.
The hidden tradeoff is that intelligence can often be scaled with more compute, more data, and better models. Coordination is different. It requires incentives, trust, verification, and long term alignment between participants who may never know each other.
The paradox is that if AI succeeds in making intelligence abundant, intelligence itself may become a commodity.
Coordination may become the layer that determines which AI networks survive.
History is full of technologies that worked. The ones that transformed industries became ecosystems like Opengradient.
So as decentralized AI evolves, should we spend less time asking which model is smartest and more time asking which network can sustain participation for the next decade?
#OPG $OPG $SYN $BEL
Smartest Models
Strongest Networks
22 heure(s) restante(s)
$BTW Trade Setup: Long Entry Zone: 0.1020 – 0.1050 TP1: 0.1120 TP2: 0.1200 TP3: 0.1300 SL: 0.0960 Price is trading above the 200 EMA (0.1000) after a strong recovery from the 0.0710 low. As long as price holds above the EMA support zone, the path of least resistance remains to the upside with a potential retest of recent highs. #Write2Earn $SYN $ID #eth #cryptofirst21
$BTW

Trade Setup: Long

Entry Zone: 0.1020 – 0.1050

TP1: 0.1120

TP2: 0.1200

TP3: 0.1300

SL: 0.0960

Price is trading above the 200 EMA (0.1000) after a strong recovery from the 0.0710 low. As long as price holds above the EMA support zone, the path of least resistance remains to the upside with a potential retest of recent highs.
#Write2Earn $SYN $ID #eth #cryptofirst21
Vérifié
BREAKING: Trump criticizes NATO allies over Iran. U.S. President Donald Trump says that after decades of American spending on NATO defense, some allies are unwilling to take a stronger role against what he describes as Iran's nuclear threat. • Trump questions burden-sharing within NATO. • Signals growing frustration with allies' defense commitments. • Iran remains at the center of escalating geopolitical tensions. • Comments could fuel debate over future U.S. military and foreign policy strategy. #TRUMP #IranWontBlockHormuzFor60Days $BSB $SPCX $RE #cryptofirst21
BREAKING: Trump criticizes NATO allies over Iran.

U.S. President Donald Trump says that after decades of American spending on NATO defense, some allies are unwilling to take a stronger role against what he describes as Iran's nuclear threat.

• Trump questions burden-sharing within NATO.
• Signals growing frustration with allies' defense commitments.
• Iran remains at the center of escalating geopolitical tensions.
• Comments could fuel debate over future U.S. military and foreign policy strategy.

#TRUMP #IranWontBlockHormuzFor60Days $BSB $SPCX $RE #cryptofirst21
I think AI image generation is quietly moving through the same transition that cloud computing went through years ago. At first, everyone cared about the underlying provider. Eventually, most users cared more about whether the service was reliable, secure, and easy to use. That’s why Image Studio on @OpenGradient feels interesting to me. On the surface, it's a way to generate images across Gemini, ByteDance, and xAI models from a single interface. But the bigger implication may be what happens when model access becomes abundant. When multiple models sit behind one layer, the challenge shifts. The question is no longer whether an image can be generated. The question becomes whether users can trust the system handling the request. This creates a tension the industry rarely discusses. More model choice increases flexibility, but it can also reduce transparency. Users gain access to more intelligence while becoming further removed from the mechanisms producing it. The contradiction is that better AI models do not automatically create more trust. In fact, as models become interchangeable, trust may migrate away from the models themselves and toward the infrastructure coordinating them. That suggests a different future. The most important AI layer may not be the one generating images. It may be the one proving, protecting, and coordinating them. Do you think the long term moat in AI will come from models or trust infrastructure? #OPG $OPG $SPCX $RE
I think AI image generation is quietly moving through the same transition that cloud computing went through years ago.
At first, everyone cared about the underlying provider. Eventually, most users cared more about whether the service was reliable, secure, and easy to use.
That’s why Image Studio on @OpenGradient feels interesting to me.
On the surface, it's a way to generate images across Gemini, ByteDance, and xAI models from a single interface. But the bigger implication may be what happens when model access becomes abundant.
When multiple models sit behind one layer, the challenge shifts. The question is no longer whether an image can be generated. The question becomes whether users can trust the system handling the request.
This creates a tension the industry rarely discusses.
More model choice increases flexibility, but it can also reduce transparency. Users gain access to more intelligence while becoming further removed from the mechanisms producing it.
The contradiction is that better AI models do not automatically create more trust. In fact, as models become interchangeable, trust may migrate away from the models themselves and toward the infrastructure coordinating them.
That suggests a different future.
The most important AI layer may not be the one generating images. It may be the one proving, protecting, and coordinating them.
Do you think the long term moat in AI will come from models or trust infrastructure?
#OPG $OPG $SPCX $RE
Models & Compute
76%
Trust Infrastructure
24%
51 Votes • Vote fermé
Michael Saylor : Bitcoin unity over tribalism Michael Saylor argues that the community agrees on 99% of what matters and shouldn't let the remaining 1% create division. • Most global capital still hasn't entered Bitcoin. • Internal debates may matter less than long-term adoption. • The opportunity ahead could be larger than the disagreements today. "Don't let the 1% divide us when 99% of the opportunity is still ahead." #bitcoin #BTC $BSB $SPCX $RE #cryptofirst21
Michael Saylor : Bitcoin unity over tribalism

Michael Saylor argues that the community agrees on 99% of what matters and shouldn't let the remaining 1% create division.

• Most global capital still hasn't entered Bitcoin.
• Internal debates may matter less than long-term adoption.
• The opportunity ahead could be larger than the disagreements today.

"Don't let the 1% divide us when 99% of the opportunity is still ahead."

#bitcoin #BTC $BSB $SPCX $RE #cryptofirst21
Hormuz Update Could Calm Global Markets🌍 Trump claims there will be no tolls in the Strait of Hormuz during a proposed 60 day ceasefire period, with shipping lanes remaining open. Why does this matter? The Strait of Hormuz is one of the world's most critical energy corridors, handling a significant share of global oil exports. Markets have been pricing in disruption risks for weeks. Any signal that energy flows remain uninterrupted could reduce immediate fears of supply shocks and ease pressure on oil prices. The bigger story isn't the tolls. It's whether this signals progress toward a broader regional agreement. For now, traders will be watching one thing: Will diplomacy move faster than market uncertainty? #TRUMP $BSB $SPCX $OPG #BitcoinNetworkActivityNearAllTimeHigh
Hormuz Update Could Calm Global Markets🌍

Trump claims there will be no tolls in the Strait of Hormuz during a proposed 60 day ceasefire period, with shipping lanes remaining open.

Why does this matter?
The Strait of Hormuz is one of the world's most critical energy corridors, handling a significant share of global oil exports.
Markets have been pricing in disruption risks for weeks.

Any signal that energy flows remain uninterrupted could reduce immediate fears of supply shocks and ease pressure on oil prices.

The bigger story isn't the tolls.
It's whether this signals progress toward a broader regional agreement.

For now, traders will be watching one thing:
Will diplomacy move faster than market uncertainty?
#TRUMP $BSB $SPCX $OPG #BitcoinNetworkActivityNearAllTimeHigh
Every day, I use Google Maps without thinking about it. I trust that the route on my screen reflects what's actually happening on the road. The moment that trust disappears, the map loses most of its value. That thought came back while I was reading about the expansion of Nous Hermes inference networks on @OpenGradient . The same question kept returning: How do you know the answer you're seeing was actually generated the way the network claims? The interesting part wasn't the model. It was the verification pipeline. Most AI infrastructure discussions focus on generating answers. OpenGradient is focused on proving answers. That distinction sounds small, but I think it changes how the network creates value. Without verification, AI is a service users must trust. With verification, trust becomes infrastructure. Generating an inference and verifying an inference are fundamentally different tasks. One produces output. The other produces confidence in that output. The narrative is that AI networks compete on intelligence. The reality is that OpenGradient may be competing on trust. Models attract users. Verification keeps trust from becoming a bottleneck. That's why the Nous Hermes milestone caught my attention. Not because it adds another model to the network, but because every new inference increases the importance of proving that execution happened as claimed. The infrastructure story and the market story may be running on different timelines. Markets react quickly to model adoption. Trust infrastructure compounds more slowly because every increase in activity creates additional verification requirements. As #OPG scales, the question I'm interested in is simple: Can verification throughput grow as quickly as inference throughput? Because if proving answers becomes harder than generating them, verification, not compute, could become the network's limiting factor. The architecture may be ahead of the market's ability to measure it. $OPG {future}(OPGUSDT) $SPCX {future}(SPCXUSDT) $BSB {future}(BSBUSDT) As AI networks mature, what becomes more valuable?
Every day, I use Google Maps without thinking about it.

I trust that the route on my screen reflects what's actually happening on the road.
The moment that trust disappears, the map loses most of its value.

That thought came back while I was reading about the expansion of Nous Hermes inference networks on @OpenGradient .

The same question kept returning:
How do you know the answer you're seeing was actually generated the way the network claims?

The interesting part wasn't the model.
It was the verification pipeline.

Most AI infrastructure discussions focus on generating answers.
OpenGradient is focused on proving answers.
That distinction sounds small, but I think it changes how the network creates value.

Without verification, AI is a service users must trust.
With verification, trust becomes infrastructure.

Generating an inference and verifying an inference are fundamentally different tasks. One produces output. The other produces confidence in that output.

The narrative is that AI networks compete on intelligence.
The reality is that OpenGradient may be competing on trust.
Models attract users.
Verification keeps trust from becoming a bottleneck.

That's why the Nous Hermes milestone caught my attention. Not because it adds another model to the network, but because every new inference increases the importance of proving that execution happened as claimed.

The infrastructure story and the market story may be running on different timelines. Markets react quickly to model adoption. Trust infrastructure compounds more slowly because every increase in activity creates additional verification requirements.

As #OPG scales, the question I'm interested in is simple:

Can verification throughput grow as quickly as inference throughput?

Because if proving answers becomes harder than generating them, verification, not compute, could become the network's limiting factor.

The architecture may be ahead of the market's ability to measure it.

$OPG
$SPCX
$BSB
As AI networks mature, what becomes more valuable?
A) Generating answers
83%
B) Proving answers
17%
59 Votes • Vote fermé
CZ Says Bitcoin’s Next Bear Market May Look Nothing Like the Last One • Bitcoin's pullback is roughly 50%, far less severe than the 80%+ crashes of previous cycles. • Compared to the 2022 lows near $16K after the Terra and FTX collapses, BTC is still up around 4–5x. • The biggest change: the U.S. has shifted from crypto crackdowns to building a regulatory framework, encouraging builders and institutions to return. • Institutional adoption is at record levels, with players like BlackRock and Bitcoin ETFs reshaping market structure. • CZ believes former cycle highs, such as $60K, could become future support zones as investor behavior evolves. • No major exchange or lending platform failures have occurred in the last six months, suggesting leverage risk is far lower than in previous cycles. • YZI Labs' portfolio allocation: 70% crypto, 20% AI, 10% biotech. CZ's core message: crypto is moving from a leverage driven market toward an infrastructure driven industry. What is your take ? #Write2Earn #BTCFalls4thDaySTRCBelowPar $BSB $SPCX $RE #cryptofirst21
CZ Says Bitcoin’s Next Bear Market May Look Nothing Like the Last One

• Bitcoin's pullback is roughly 50%, far less severe than the 80%+ crashes of previous cycles.
• Compared to the 2022 lows near $16K after the Terra and FTX collapses, BTC is still up around 4–5x.
• The biggest change: the U.S. has shifted from crypto crackdowns to building a regulatory framework, encouraging builders and institutions to return.
• Institutional adoption is at record levels, with players like BlackRock and Bitcoin ETFs reshaping market structure.
• CZ believes former cycle highs, such as $60K, could become future support zones as investor behavior evolves.
• No major exchange or lending platform failures have occurred in the last six months, suggesting leverage risk is far lower than in previous cycles.
• YZI Labs' portfolio allocation: 70% crypto, 20% AI, 10% biotech.

CZ's core message: crypto is moving from a leverage driven market toward an infrastructure driven industry.

What is your take ?

#Write2Earn #BTCFalls4thDaySTRCBelowPar
$BSB $SPCX $RE #cryptofirst21
Vérifié
The U.S.-Iran peace deal is already starting to collapse. Iran has officially suspended the entire 60-day negotiation process after accusing the U.S. of violating the agreement less than 24 hours after it was signed. Vice President JD Vance has now canceled his Switzerland trip for the talks. #OilHeadsForDeepWeeklyLoss $SPCX $BSB $SIREN #cryptofirst21
The U.S.-Iran peace deal is already starting to collapse.

Iran has officially suspended the entire 60-day negotiation process after accusing the U.S. of violating the agreement less than 24 hours after it was signed.

Vice President JD Vance has now canceled his Switzerland trip for the talks.

#OilHeadsForDeepWeeklyLoss $SPCX $BSB $SIREN #cryptofirst21
Vérifié
UPDATE: SpaceX shares fell for a second straight day, pushing the company’s market cap below Amazon after last week’s historic IPO rally #Write2Earn $SPCX $SPCXB #cryptofirst21 #FedHawkishDotPlotFlattensYieldCurve
UPDATE: SpaceX shares fell for a second straight day, pushing the company’s market cap below Amazon after last week’s historic IPO rally

#Write2Earn $SPCX $SPCXB #cryptofirst21 #FedHawkishDotPlotFlattensYieldCurve
🌍 BREAKING: The newly announced U.S.-Iran agreement is being described by supporters as a historic "grand bargain", the first deal signed by American and Iranian presidents since the 1979 Islamic Revolution. But across the Middle East, the reaction is far more divided. 🇮🇱 Israel reportedly views the agreement as a strategic setback. 🇸🇦 Gulf states are concerned about a shifting regional balance of power. 🇱🇧 Lebanon could see its political and security landscape increasingly tied to the new U.S.-Iran framework. The deal may reduce the risk of immediate conflict, but it is also redrawing geopolitical alliances across the region. One agreement. Many winners. Many worried neighbors. #breakingnews #TRUMP #cryptofirst21 #Fed4thConsecutiveRateHold $SPCX $BSB
🌍 BREAKING: The newly announced U.S.-Iran agreement is being described by supporters as a historic "grand bargain", the first deal signed by American and Iranian presidents since the 1979 Islamic Revolution.

But across the Middle East, the reaction is far more divided.

🇮🇱 Israel reportedly views the agreement as a strategic setback.
🇸🇦 Gulf states are concerned about a shifting regional balance of power.
🇱🇧 Lebanon could see its political and security landscape increasingly tied to the new U.S.-Iran framework.

The deal may reduce the risk of immediate conflict, but it is also redrawing geopolitical alliances across the region.

One agreement.
Many winners.
Many worried neighbors.

#breakingnews #TRUMP #cryptofirst21 #Fed4thConsecutiveRateHold $SPCX $BSB
i've started to think that the ai industry is having the same conversation the cloud industry had years ago. everyone is focused on performance. very few are focused on verification. most ai infrastructure today assumes that trust is inherited from the model. if a model is reputable, its outputs are treated as trustworthy by default. @OpenGradient haca architecture starts from a fundamentally different assumption. trust must be proven. by combining model hosting, trusted execution, verifiable inference, cryptographic attestation, and on chain settlement, haca attempts to create something that most ai systems still lack: a verifiable chain of provenance for computation itself. what makes this interesting isn't the architecture. it's the economic implication. for most of computing history, computation was scarce and trust was assumed. haca is effectively a bet that ai flips that equation. as models become increasingly abundant and capable, intelligence may become easier to access than certainty. in that world, the question shifts from: "can ai generate this output?" to "can anyone prove how this output was generated?" that's a very different market. the more i study opengradient, the less i think haca is competing with other ai models. it's competing with an assumption that has quietly shaped the entire industry: that intelligence creates trust. haca suggests the opposite. trust may become the prerequisite for intelligence to have economic value at all. of course, architecture is not adoption. the market still has to decide whether verifiability is important enough to justify additional complexity, costs, and workflow changes. but if ai outputs eventually become as abundant as information itself, the scarce resource may not be intelligence. it may be proof. and that makes haca one of the more interesting infrastructure experiments i'm watching today. #OPG $SYN $SPCX $OPG What will be the more valuable layer in Opengradient?
i've started to think that the ai industry is having the same conversation the cloud industry had years ago.
everyone is focused on performance.
very few are focused on verification.
most ai infrastructure today assumes that trust is inherited from the model. if a model is reputable, its outputs are treated as trustworthy by default.
@OpenGradient haca architecture starts from a fundamentally different assumption.
trust must be proven.
by combining model hosting, trusted execution, verifiable inference, cryptographic attestation, and on chain settlement, haca attempts to create something that most ai systems still lack: a verifiable chain of provenance for computation itself.
what makes this interesting isn't the architecture.
it's the economic implication.
for most of computing history, computation was scarce and trust was assumed. haca is effectively a bet that ai flips that equation. as models become increasingly abundant and capable, intelligence may become easier to access than certainty.
in that world, the question shifts from:
"can ai generate this output?"
to
"can anyone prove how this output was generated?"
that's a very different market.
the more i study opengradient, the less i think haca is competing with other ai models.
it's competing with an assumption that has quietly shaped the entire industry:
that intelligence creates trust.
haca suggests the opposite.
trust may become the prerequisite for intelligence to have economic value at all.
of course, architecture is not adoption. the market still has to decide whether verifiability is important enough to justify additional complexity, costs, and workflow changes.
but if ai outputs eventually become as abundant as information itself, the scarce resource may not be intelligence.
it may be proof.
and that makes haca one of the more interesting infrastructure experiments i'm watching today.
#OPG $SYN $SPCX $OPG
What will be the more valuable layer in Opengradient?
Better AI performance
72%
Verifiable AI provenance
28%
43 Votes • Vote fermé
Kevin Warsh just ended his first ever FOMC meeting as Fed chair. His message to markets: "I can't give you any guidance on what we're going to do next." Here is what he said: 1. Inflation is still way above the Fed's 2% target and prices are too high for most people 2. "We will fix five years of misses on inflation", he is directly saying the previous Fed failed 3. The Fed will no longer tell you in advance what it plans to do with interest rates 4. He watches stock market prices more than anything else when making decisions 5. Interest rates are hurting the housing market but are not slowing down financial markets 6. All 19 members at the table agreed not to raise rates today 7. The 2% inflation target is not changing 8. He refused to say whether bond yields rising after today's decision concerns him 9. He refused to say whether he has spoken to Trump since becoming Fed chair Under Powell, the Fed always told markets what was coming next. Under Warsh, that is gone. #Fed4thConsecutiveRateHold #cryptofirst21 $BSB $NVDAB $TSLAB
Kevin Warsh just ended his first ever FOMC meeting as Fed chair.

His message to markets: "I can't give you any guidance on what we're going to do next."

Here is what he said:

1. Inflation is still way above the Fed's 2% target and prices are too high for most people

2. "We will fix five years of misses on inflation", he is directly saying the previous Fed failed

3. The Fed will no longer tell you in advance what it plans to do with interest rates

4. He watches stock market prices more than anything else when making decisions

5. Interest rates are hurting the housing market but are not slowing down financial markets

6. All 19 members at the table agreed not to raise rates today

7. The 2% inflation target is not changing

8. He refused to say whether bond yields rising after today's decision concerns him

9. He refused to say whether he has spoken to Trump since becoming Fed chair

Under Powell, the Fed always told markets what was coming next. Under Warsh, that is gone.

#Fed4thConsecutiveRateHold #cryptofirst21
$BSB $NVDAB $TSLAB
Vérifié
🇮🇷 The US and Iran War have now officially ENDED after 110 days. Both countries have signed a 14 point MOU to end the war effective immediately, per Axios. 1. Immediate permanent ceasefire on all fronts, including Lebanon. No more wars or threats. 2. Respect Lebanon’s sovereignty and territorial integrity. 3. Fully reopen Strait of Hormuz to commercial shipping. 4. Lift US naval blockade on Iran. 5. Release frozen Iranian assets. 6. Waivers for Iranian oil exports/sales. 7. Iran commits never to make or get nuclear weapons. 8. IAEA monitors Iran’s nuclear stockpile; no further advances. 9. Start 60-day talks for a final comprehensive deal. 10. Create $300 billion fund for Iran’s reconstruction. 11. Set up monitoring to check compliance. 12. Outline path for final agreement (possibly UN backed). 13. Allies on both sides commit to upholding the ceasefire. 14. Define timelines and rules for implementation/enforcement. #Write2Earn #bitcoin #ETH #cryptofirst21 $SIREN $SPCX $BSB
🇮🇷 The US and Iran War have now officially ENDED after 110 days.

Both countries have signed a 14 point MOU to end the war effective immediately, per Axios.

1. Immediate permanent ceasefire on all fronts, including Lebanon. No more wars or threats.

2. Respect Lebanon’s sovereignty and territorial integrity.

3. Fully reopen Strait of Hormuz to commercial shipping.

4. Lift US naval blockade on Iran.

5. Release frozen Iranian assets.

6. Waivers for Iranian oil exports/sales.

7. Iran commits never to make or get nuclear weapons.

8. IAEA monitors Iran’s nuclear stockpile; no further advances.

9. Start 60-day talks for a final comprehensive deal.

10. Create $300 billion fund for Iran’s reconstruction.

11. Set up monitoring to check compliance.
12. Outline path for final agreement (possibly UN backed).

13. Allies on both sides commit to upholding the ceasefire.

14. Define timelines and rules for implementation/enforcement.
#Write2Earn #bitcoin #ETH #cryptofirst21
$SIREN $SPCX $BSB
Apple's Intel Partnership Is Bigger Than It Looks Trump says Apple will work with Intel to design and manufacture chips in the U.S. This isn't just another partnership. Apple gets supply chain diversification. Intel gets its biggest foundry validation yet. The U.S. gets closer to bringing advanced chip production back home. The AI race won't be won only by who builds the best models. It may be won by who controls the factories making the chips. #Write2Earn #Fed4thConsecutiveRateHold $BSB $SPCXB $SPCX #cryptofirst21
Apple's Intel Partnership Is Bigger Than It Looks

Trump says Apple will work with Intel to design and manufacture chips in the U.S.

This isn't just another partnership.

Apple gets supply chain diversification.

Intel gets its biggest foundry validation yet.

The U.S. gets closer to bringing advanced chip production back home.

The AI race won't be won only by who builds the best models.

It may be won by who controls the factories making the chips.

#Write2Earn #Fed4thConsecutiveRateHold $BSB $SPCXB $SPCX #cryptofirst21
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