🇨🇭 Global One SI - Prompt
#WTI Getting tight $200 oil bulls The problem with being ahead of the curve is, everyone thinks you're retarded. 😜
#WTI US oil prices collapse below $87/barrel after President Trump cancels scheduled strikes on Iran.
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Forwarded from 🛢WTI, Brent Crude Oil, NGAS Trading 📊
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🇺🇸🇮🇷 Trump was talking about taking Iranian oil infrastructure back in 1987.
In a Barbara Walters interview during the Tanker War, he argued the U.S. should stop protecting Gulf oil routes for free and make allies pay for the security they benefit from.
Then he went further: if Iran attacked America again, he said the U.S. should “go in and grab one of their big oil installations” and keep it to recover losses.
Communication and Policy Strategist #realazadeh points out that this is the same framework Trump has carried for nearly 40 years: allies pay up, U.S. power gets compensated, and Iranian oil becomes leverage.
That makes his current Kharg Island threat look less like a new idea and more like an old doctrine returning in real time.
Most people are watching the nuclear talks. Trump may be looking at the oil map he has had in his head since 1987.
In a Barbara Walters interview during the Tanker War, he argued the U.S. should stop protecting Gulf oil routes for free and make allies pay for the security they benefit from.
Then he went further: if Iran attacked America again, he said the U.S. should “go in and grab one of their big oil installations” and keep it to recover losses.
Communication and Policy Strategist #realazadeh points out that this is the same framework Trump has carried for nearly 40 years: allies pay up, U.S. power gets compensated, and Iranian oil becomes leverage.
That makes his current Kharg Island threat look less like a new idea and more like an old doctrine returning in real time.
Most people are watching the nuclear talks. Trump may be looking at the oil map he has had in his head since 1987.
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🇨🇭 Global One SI - Prompt
$BB Everyone loved it at $10. Few were paying attention at $6. The chart is now doing exactly what strong trends do: Pullback. Consolidate. Build energy. Continue. As long as the higher-low structure remains intact, I remain extremely constructive on…
The signs for you to buy $BB at less than $10 was presented to you on a platter.
🇨🇭 Global One SI - Prompt
One more day until the FIFA World Cup 2026 comes to America! 🔥🇺🇸 Let's goooo!
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FIFA world cup 2026 opening ceremony.
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🇨🇭 Global One SI - Prompt
$AMD/USD H2 #Indicator #Signal #Trading #GlobalOneAI
$AMD's marketing chief boasts '15 out of 15' on Amazon's best-seller CPU chart, leaving Intel without a single spot.
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President Trump says the U.S. “made a great settlement of war with Iran.”
$INFQ $AMPG $XNDU $ALRIB $HQ $LAES
The countdown to the commercial quantum era has officially begun.
As we march toward 2030, the race for global quantum supremacy isn't just about the tech giants anymore, it’s about the specialized ecosystem enabling the revolution.
These 6 stocks are positioned at the absolute center of this multi-billion-dollar shift:
The Hardware & Core Architects
$XNDU (Xanadu) | Market Cap: $3.51B – Leading the charge in photonic quantum computing using light instead of electricity. Their PennyLane software is already an industry standard for quantum machine learning.
$INFQ (Infleqtion) | Market Cap: $2.94B – Utilizing neutral-atom technology to bypass extreme cooling requirements. They are scaling fast with highly competitive quantum sensors and atomic clocks.
The Software Gateway
$HQ (Horizon Quantum Holdings) | Market Cap: $516.3M – Solving the massive quantum coding gap. Horizon automatically translates traditional code into quantum-ready algorithms, democratizing enterprise access.
Critical Infrastructure
$ALRIB (Riber S.A.) | Market Cap: €262M – A European micro-cap powerhouse holding a near-global duopoly on Molecular Beam Epitaxy (MBE) machines. Essential for building ultra-pure quantum chips.
$AMPG (AmpliTech Group) | Market Cap: $192.8M – Designing specialized cryogenic low-noise amplifiers (LNAs) that can boost ultra-faint quantum signals at temperatures near absolute zero.
The Defensive Cybersecurity Shield
$LAES (SEALSQ Corp) | Market Cap: $677.2M – Addressing the "Y2Q" quantum threat. They manufacture physical, quantum-resistant microchips equipped with next-gen NIST security standards.
The countdown to the commercial quantum era has officially begun.
As we march toward 2030, the race for global quantum supremacy isn't just about the tech giants anymore, it’s about the specialized ecosystem enabling the revolution.
These 6 stocks are positioned at the absolute center of this multi-billion-dollar shift:
The Hardware & Core Architects
$XNDU (Xanadu) | Market Cap: $3.51B – Leading the charge in photonic quantum computing using light instead of electricity. Their PennyLane software is already an industry standard for quantum machine learning.
$INFQ (Infleqtion) | Market Cap: $2.94B – Utilizing neutral-atom technology to bypass extreme cooling requirements. They are scaling fast with highly competitive quantum sensors and atomic clocks.
The Software Gateway
$HQ (Horizon Quantum Holdings) | Market Cap: $516.3M – Solving the massive quantum coding gap. Horizon automatically translates traditional code into quantum-ready algorithms, democratizing enterprise access.
Critical Infrastructure
$ALRIB (Riber S.A.) | Market Cap: €262M – A European micro-cap powerhouse holding a near-global duopoly on Molecular Beam Epitaxy (MBE) machines. Essential for building ultra-pure quantum chips.
$AMPG (AmpliTech Group) | Market Cap: $192.8M – Designing specialized cryogenic low-noise amplifiers (LNAs) that can boost ultra-faint quantum signals at temperatures near absolute zero.
The Defensive Cybersecurity Shield
$LAES (SEALSQ Corp) | Market Cap: $677.2M – Addressing the "Y2Q" quantum threat. They manufacture physical, quantum-resistant microchips equipped with next-gen NIST security standards.
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🇨🇭 Global One SI - Prompt
POV: That friend who always says 'I don't have money' but magically finds funds to buy the dip
And this is exactly why I bought the dip ago.
Conviction Pays 🫡
Conviction Pays 🫡
🇨🇭 Global One SI - Prompt
Robotics funding is moving fast. The latest 5 major rounds alone represent $2.41B: NEURARobotics — up to $1.4B GeneralistAI — $400M Mind_Robotics — $400M Standardbots — $200M SlamcoreLtd — $14M The money is going into Physical AI robot foundation models…
The robotics race is not one lane.
‣Robotiq handles the grip
‣OTTO moves the load
‣Boston Dynamics pushes mobility
‣OnRobot builds the end effectors
‣Tesla brings humanoids into the debate
‣Symbotic attacks warehouse automation
Different robots. Same pressure on human labor.
#Robotics #Automation #HumanoidRobots #PhysicalAI #IndustrialRobotics #BostonDynamics #TeslaOptimus #Symbotic #AI #FutureOfWork
‣Robotiq handles the grip
‣OTTO moves the load
‣Boston Dynamics pushes mobility
‣OnRobot builds the end effectors
‣Tesla brings humanoids into the debate
‣Symbotic attacks warehouse automation
Different robots. Same pressure on human labor.
#Robotics #Automation #HumanoidRobots #PhysicalAI #IndustrialRobotics #BostonDynamics #TeslaOptimus #Symbotic #AI #FutureOfWork
🇨🇭 Global One SI - Prompt
JEFF BEZOS JUST EMERGED FROM STEALTH WITH A $41 BILLION AI STARTUP CALLED PROMETHEUS $12 billion raised. Valued at $41 billion. Coming out of stealth today. The backers: Bezos personally, JPMorgan, BlackRock, Goldman Sachs, DST Global, and Arch Venture Partners.…
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Jeff Bezos on CNBC explains revealed what Prometheus is building.
Today his new company Prometheus announced a $12B funding round at a valuation of $41B .
Prometheus trying to build an artificial general engineer that can help design and manufacture physical products like engines, medical devices, and electronics.
So the target areas are hard physical products like jet engines, chips, bridges, medical devices, consumer electronics, aerospace systems, vehicles, and drug design, where design cycles can take years because every idea has to survive physics, materials, cost, testing, and factory limits.
Bezos’ jet-engine example explains it well: asking for the same engine with 10% more thrust can become a 10-year engineering program, and Prometheus wants to shrink that “dream-build” cycle by 10x or more.
The $6.2B launch funding gave Prometheus a massive starting base, and the new raise says the company likely needs far more compute, talent, and industrial data before it can prove the product.
Their $41B valuation shows that frontier AI is becoming less a software race than a compute procurement race.
A company with no broadly shipped product can raise $12 billion at a $41 billion valuation because investors are not only funding a model, they are prepaying for the machines that might make the model possible.
The scarce asset is no longer just talent or algorithms, but clustered GPUs, power contracts, cooling, networking, and the operational skill to keep expensive silicon busy.
They are proof that demand is arriving faster than infrastructure can be built, and that every frontier funding round quietly turns into a future claim on power, racks, GPUs, and uptime.
Today his new company Prometheus announced a $12B funding round at a valuation of $41B .
Prometheus trying to build an artificial general engineer that can help design and manufacture physical products like engines, medical devices, and electronics.
So the target areas are hard physical products like jet engines, chips, bridges, medical devices, consumer electronics, aerospace systems, vehicles, and drug design, where design cycles can take years because every idea has to survive physics, materials, cost, testing, and factory limits.
Bezos’ jet-engine example explains it well: asking for the same engine with 10% more thrust can become a 10-year engineering program, and Prometheus wants to shrink that “dream-build” cycle by 10x or more.
The $6.2B launch funding gave Prometheus a massive starting base, and the new raise says the company likely needs far more compute, talent, and industrial data before it can prove the product.
Their $41B valuation shows that frontier AI is becoming less a software race than a compute procurement race.
A company with no broadly shipped product can raise $12 billion at a $41 billion valuation because investors are not only funding a model, they are prepaying for the machines that might make the model possible.
The scarce asset is no longer just talent or algorithms, but clustered GPUs, power contracts, cooling, networking, and the operational skill to keep expensive silicon busy.
They are proof that demand is arriving faster than infrastructure can be built, and that every frontier funding round quietly turns into a future claim on power, racks, GPUs, and uptime.
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OpenAI is buying Ona to give Codex agents a secure cloud desk that stays open after humans leave.
Codex already has 5M weekly users, up 400%, but harder work breaks the old chat pattern because agents need tools, files, credentials, logs, and time.
Ona adds persistent cloud workspaces, meaning an agent gets a controlled place to run commands, inspect systems, preserve context, and resume work without depending on one device.
The enterprise angle is the real acquisition target: companies want agents inside their own cloud boundary, with scoped credentials, review trails, access limits, and auditable activity.
This makes Codexmore like a managed execution layer for tests, bug fixes, refactors, vulnerability work, migrations, and multi-step knowledge tasks.
Codex already has 5M weekly users, up 400%, but harder work breaks the old chat pattern because agents need tools, files, credentials, logs, and time.
Ona adds persistent cloud workspaces, meaning an agent gets a controlled place to run commands, inspect systems, preserve context, and resume work without depending on one device.
The enterprise angle is the real acquisition target: companies want agents inside their own cloud boundary, with scoped credentials, review trails, access limits, and auditable activity.
This makes Codexmore like a managed execution layer for tests, bug fixes, refactors, vulnerability work, migrations, and multi-step knowledge tasks.
🇨🇭 Global One SI - Prompt
OpenAI is buying Ona to give Codex agents a secure cloud desk that stays open after humans leave. Codex already has 5M weekly users, up 400%, but harder work breaks the old chat pattern because agents need tools, files, credentials, logs, and time. Ona adds…
OpenAI is buying Ona because Codex’s next bottleneck is not model intelligence, but secure execution inside enterprise infrastructure.
A coding agent cannot do serious production work through chat alone, because it needs a running workspace with the repo, build tools, test data, credentials, logs, permissions, and enough state to continue work over hours or days.
The technical asset is customer-controlled cloud execution, meaning the agent can run inside the customer’s cloud boundary instead of forcing sensitive code, secrets, and workflow state into a generic external sandbox.
Because, most enterprise client of OpenAI will ask question like “Can Codex safely operate for hours or days inside a bank, pharma company, or sovereign fund’s real cloud environment, with their access rules, logs, credentials, reviews, and security controls?”
And that's the gap this acquisition will fill.
OpenAI says Ona brings secure, persistent environments where agents can access tools, systems, and context over time, and can keep working inside a customer’s cloud even when laptops are closed.
So now OpenAI can charge for longer-running, higher-value workflows such as migrations, vulnerability fixes, test generation, incident investigation, refactoring, and internal tool creation, not just short coding tasks.
A coding agent cannot do serious production work through chat alone, because it needs a running workspace with the repo, build tools, test data, credentials, logs, permissions, and enough state to continue work over hours or days.
The technical asset is customer-controlled cloud execution, meaning the agent can run inside the customer’s cloud boundary instead of forcing sensitive code, secrets, and workflow state into a generic external sandbox.
Because, most enterprise client of OpenAI will ask question like “Can Codex safely operate for hours or days inside a bank, pharma company, or sovereign fund’s real cloud environment, with their access rules, logs, credentials, reviews, and security controls?”
And that's the gap this acquisition will fill.
OpenAI says Ona brings secure, persistent environments where agents can access tools, systems, and context over time, and can keep working inside a customer’s cloud even when laptops are closed.
So now OpenAI can charge for longer-running, higher-value workflows such as migrations, vulnerability fixes, test generation, incident investigation, refactoring, and internal tool creation, not just short coding tasks.
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