🇨🇭 Global One SI - Prompt
🇮🇷 Iran doesn’t need a massive navy to control the Strait of Hormuz, it built that control through its islands. Kharg Island is the center of everything: up to 90% of Iran’s oil exports move through it, with storage tanks and loading terminals feeding the…
A little birdie told me the US is preparing for a full on amphibious & airborne invasion of Qeshm Island, Iran
USS Abraham Lincoln, George Bush & Boxer assault group are reportedly ready
US strikes specifically targeted coastal surveillance & defense assets along Iran's coast
USS Abraham Lincoln, George Bush & Boxer assault group are reportedly ready
US strikes specifically targeted coastal surveillance & defense assets along Iran's coast
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🇨🇭 Global One SI - Prompt
Despite Jerome Powell no longer being Fed chair and Kevin Warsh taking over, the Not QE QE printing continues. Federal Reserve's holding of T-Bills jumped again this week to $459 billion. Keep in mind, at the height of the 2020 crisis, the Federal Reserve…
The U.S. 3 month treasury yield has begun breaking upward this week.
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🇨🇭 Global One SI - Prompt
$KOSPI/USD H2 #Indicator #Signal #Trading #GlobalOneAI
South Korea's KOSPI margin debt hits $19 billion, as analysts warn of possible forced-selling if the market rout continues.
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Goldman Sachs: "Token use by AI agents is expected to multiply 24 times by 2030"
AI agents are now creating the first serious cost test for the AI boom. As was reported this week, Uber and Microsoft are already rethinking expensive agent usage.
A chatbot may answer once, but an agent plans, calls tools, checks results, edits mistakes, and repeats the loop.
That loop can make one user request consume 10x, 50x, or even far more tokens than a normal answer.
Goldman’s bullish case is that monthly token use could reach 120 quadrillion by 2030, while inference cost per token keeps falling 60%-70% per year.
The fight is now between agent productivity and token waste.
AI agents are now creating the first serious cost test for the AI boom. As was reported this week, Uber and Microsoft are already rethinking expensive agent usage.
A chatbot may answer once, but an agent plans, calls tools, checks results, edits mistakes, and repeats the loop.
That loop can make one user request consume 10x, 50x, or even far more tokens than a normal answer.
Goldman’s bullish case is that monthly token use could reach 120 quadrillion by 2030, while inference cost per token keeps falling 60%-70% per year.
The fight is now between agent productivity and token waste.
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"Every 10 seconds, global token demand is around 31.7 billion in 2026. By 2030 its 1.27 trillion, a 40x increase."
~ Qualcomm CEO Cristiano Amon:
---
The token explosion is not mainly about smarter answers; it is about AI moving from human-paced interaction to Agent-paced activity.
Once agents become persistent, the economy of AI stops will be the background infrastructure.
Every useful action has a hidden bill: context must be carried, memory must be updated, sensors may need to be interpreted, and mistakes must be caught before they become expensive.
~ Qualcomm CEO Cristiano Amon:
---
The token explosion is not mainly about smarter answers; it is about AI moving from human-paced interaction to Agent-paced activity.
Once agents become persistent, the economy of AI stops will be the background infrastructure.
Every useful action has a hidden bill: context must be carried, memory must be updated, sensors may need to be interpreted, and mistakes must be caught before they become expensive.
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The middle east right after Iran feels unhappy with the U.S
🇨🇭 Global One SI - Prompt
Unemployment could hit 20% by 2028. This would be the worst job market since the 1929 Great Depression.
Goldman Sachs new report "An AI Job Apocalypse?"
Says AI could displace 15mn workers, but not cause mass unemployment.
Estimates AI could lift productivity and GDP by 15% after full adoption.
The clearest pressure sits in customer support, back-office work, claims, billing, and entry-level tasks.
Goldman’s own labor model finds a small current drag of 16K jobs monthly.
Younger workers look more exposed because AI can absorb the basic tasks that teach judgment.
College graduates are not collapsing yet, but their industries adopt AI faster than others.
Joseph Briggs, GS global economists still expects more than 9% of workers to face displacement across 10 years.
MIT professor Daron Acemoglu is more cautious, expecting 2-4% job losses across 5 years. His concern is that current AI replaces routine office tasks more often than it supports workers.
Neil Thompson of MIT adds a missing filter: capability does not mean reliability, access, or cheap deployment. A chatbot can answer broadly, but businesses need accuracy, private data, and repeatable workflows.
Says AI could displace 15mn workers, but not cause mass unemployment.
Estimates AI could lift productivity and GDP by 15% after full adoption.
The clearest pressure sits in customer support, back-office work, claims, billing, and entry-level tasks.
Goldman’s own labor model finds a small current drag of 16K jobs monthly.
Younger workers look more exposed because AI can absorb the basic tasks that teach judgment.
College graduates are not collapsing yet, but their industries adopt AI faster than others.
Joseph Briggs, GS global economists still expects more than 9% of workers to face displacement across 10 years.
MIT professor Daron Acemoglu is more cautious, expecting 2-4% job losses across 5 years. His concern is that current AI replaces routine office tasks more often than it supports workers.
Neil Thompson of MIT adds a missing filter: capability does not mean reliability, access, or cheap deployment. A chatbot can answer broadly, but businesses need accuracy, private data, and repeatable workflows.
🇨🇭 Global One SI - Prompt
Apparently Iran called Trump and "They want to make a deal so badly..." 🤪 "We've already won"
• Iran contacted us some time ago and wants to strike a deal. However, I'm not sure that Tehran will abide by its terms.
• The US just launched a very powerful strike against Iran. For every attack from Iran, Washington will respond in a 20 to 1 ratio.
• Today's attack was a response to yesterday's strikes by Iran. If they repeat themselves, the consequences will be much more serious.
• The senior military adviser to the Supreme Leader of Iran, Mohsen Rezaei, stated that all those who violate the country's borders and their allies will be "strictly punished".
• The Speaker of Parliament, Mohammad Bagher Ghalibaf, warned the US: "You hit - you get a counterstrike". He also stated that the Strait of Hormuz will only be opened under an agreement with Iran, not under US pressure.
• The IRGC reported on strikes on American military bases in Kuwait and Bahrain and threatened to expand the list of targets in the event of new US attacks.
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Both Elon Musk and Demis Hassabis has said robotics is bottlenecked by hands and robots will not become useful until hands improve massively.
And now 1X Technologies is preparing to reveal a robotic hand that may surpass human finger control.
The big deal here is the controllable force across the small joints that make dexterity possible. A 10-20DoF hand would sit near the hard boundary between compact hardware and humanlike control.
The design appears built around Bowden tubes, which route force through cable-like tendon paths.
Real intelligence may be hiding in the routing, not the fingers.
That architecture lets actuators sit away from the fingers, keeping the hand lighter.
A human hand uses the same broad trick, with muscles pulling tendons across joints.
1X is applying that idea to humanoid robotics, where compact hands must handle real objects.
The visible side reportedly shows 20 tendons, suggesting 10 paired actuator paths.
A matching hidden side could raise the system to 40 tendons and 20 actuators.
The lower estimate points to coupled finger joints, where one tendon path drives several links.
The higher estimate points to independent IP control, where each finger segment can move separately.
That difference separates a strong gripper from a hand that can shape contact precisely.
The catch is calibration, because tendon friction, stretch, and backlash can erase beautiful mechanics.
If 1X has solved that reliably, the hand could become a serious advantage for NEO.
And now 1X Technologies is preparing to reveal a robotic hand that may surpass human finger control.
The big deal here is the controllable force across the small joints that make dexterity possible. A 10-20DoF hand would sit near the hard boundary between compact hardware and humanlike control.
The design appears built around Bowden tubes, which route force through cable-like tendon paths.
Real intelligence may be hiding in the routing, not the fingers.
That architecture lets actuators sit away from the fingers, keeping the hand lighter.
A human hand uses the same broad trick, with muscles pulling tendons across joints.
1X is applying that idea to humanoid robotics, where compact hands must handle real objects.
The visible side reportedly shows 20 tendons, suggesting 10 paired actuator paths.
A matching hidden side could raise the system to 40 tendons and 20 actuators.
The lower estimate points to coupled finger joints, where one tendon path drives several links.
The higher estimate points to independent IP control, where each finger segment can move separately.
That difference separates a strong gripper from a hand that can shape contact precisely.
The catch is calibration, because tendon friction, stretch, and backlash can erase beautiful mechanics.
If 1X has solved that reliably, the hand could become a serious advantage for NEO.
39 gold miners sit in the world's top 100 mining companies.
Just 22 copper miners out earn all of them.
By share of $730B in combined 2025 mining revenue:
1️⃣ Copper: 22 companies, 28.1% of revenue, the single largest share of any commodity
2️⃣ Gold: 39 companies, more producers than any other metal, but only 21.3% of revenue
3️⃣ Iron ore: just 5 companies, still out-earning gold at 22.4%
4️⃣ Glencore alone earned $63B, more than the entire coal sector combined
Volume isn't value. The revenue crown belongs to copper and iron ore, not gold.
Just 22 copper miners out earn all of them.
By share of $730B in combined 2025 mining revenue:
1️⃣ Copper: 22 companies, 28.1% of revenue, the single largest share of any commodity
2️⃣ Gold: 39 companies, more producers than any other metal, but only 21.3% of revenue
3️⃣ Iron ore: just 5 companies, still out-earning gold at 22.4%
4️⃣ Glencore alone earned $63B, more than the entire coal sector combined
Volume isn't value. The revenue crown belongs to copper and iron ore, not gold.
🇨🇭 Global One SI - Prompt
I reduced my Fable 5 token spend by 50%+ with these simple hacks
Grok 4.5: The Complete Overview
• How to set up (for free)
• Real use cases
• Benchmarks & comparisons
• Tips & more
• How to set up (for free)
• Real use cases
• Benchmarks & comparisons
• Tips & more
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🇨🇭 Global One SI - Prompt
Grok 4.5: The Complete Overview • How to set up (for free) • Real use cases • Benchmarks & comparisons • Tips & more
How to turn Hermes into your Google Workspace assistant (step by step).👇
Connect Hermes to:
- Gmail
- Google Calendar
- Google Drive
- Google Notes
- Google Sheets
- Google Meet
Connect Hermes to:
- Gmail
- Google Calendar
- Google Drive
- Google Notes
- Google Sheets
- Google Meet
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I love money.
Always have.
I think in profit margins, not feelings.
Every decision's an ROI calculation.
If it doesn't pay me, it drains me.
I don't chase passion, i price it.
Money isn't everything.
But it's the scoreboard.
Always have.
I think in profit margins, not feelings.
Every decision's an ROI calculation.
If it doesn't pay me, it drains me.
I don't chase passion, i price it.
Money isn't everything.
But it's the scoreboard.
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🇨🇭 Global One SI - Prompt
Pure game theory - #Bitcoin made your capital exitable. A Passport Portfolio makes you exitable. Once citizens can leave - governments forced to reform to compete for you, your capital and talent. Making it happen, one second passport at a time 😎
You Made $1,000,000.
Here’s What’s Left After Taxes
🇦🇪 United Arab Emirates -$1,000,000
🇵🇦 Panama - $1,000,000
🇵🇾 Paraguay - $1,000,000
🇨🇷 Costa Rica - $1,000,000
🇭🇰 Hong Kong - $840,000
🇸🇬 Singapore - $790,000
🇨🇭 Switzerland - $650,000
🇺🇸 United States - $620,000
🇳🇿 New Zealand - $610,000
🇦🇺 Australia - $560,000
🇬🇧 United Kingdom - $555,000
🇨🇦 Canada - $530,000
🇩🇪 Germany - $520,000
🇫🇷 France - $460,000
🇩🇰 Denmark - $441,000
Here’s What’s Left After Taxes
🇦🇪 United Arab Emirates -$1,000,000
🇵🇦 Panama - $1,000,000
🇵🇾 Paraguay - $1,000,000
🇨🇷 Costa Rica - $1,000,000
🇭🇰 Hong Kong - $840,000
🇸🇬 Singapore - $790,000
🇨🇭 Switzerland - $650,000
🇺🇸 United States - $620,000
🇳🇿 New Zealand - $610,000
🇦🇺 Australia - $560,000
🇬🇧 United Kingdom - $555,000
🇨🇦 Canada - $530,000
🇩🇪 Germany - $520,000
🇫🇷 France - $460,000
🇩🇰 Denmark - $441,000
Okay, GPT-5.6 is officially here and this is not just another benchmark flex.
This feels like OpenAI moving from “chatbot company” to full AI work platform.
What dropped:
• GPT-5.6 Sol
The new flagship model. OpenAI says it is stronger across coding, knowledge work, cybersecurity, science, design, and long agentic workflows.
• Terra and Luna
This is the underrated part. The smaller models apparently punch way above their price class, which matters a lot if AI is actually going to become abundant and cheap instead of just insanely powerful for people with enterprise budgets.
• Ultra mode
This is the spicy bit. GPT-5.6 can coordinate multiple agents in parallel for harder tasks. Not just “think longer”, but split the work, run different paths, compare, synthesize, and move faster.
• Better coding and tool use
OpenAI is basically saying GPT-5.6 is better at real work inside real codebases, terminal workflows, debugging, reviewing, and using tools without wasting a million tokens on every step.
• Design finally matters
The model can inspect what it creates, refine the UI, catch visual issues, and produce more polished artifacts. This is huge because most AI-generated frontend still has that cursed “technically works but spiritually dead” vibe.
• Knowledge work is becoming end-to-end
Docs, slides, spreadsheets, reports, messy files, workplace context, all turned into actual usable output. Not “here’s a draft, good luck”, but closer to “here’s the thing you can send.”
• ChatGPT Work, Codex, API
This is why it feels bigger than a model release. GPT-5.6 is landing across the actual work surface: chat, coding, agents, documents, and developer workflows.
My take:
The real story is not just that Sol is powerful.
The real story is that OpenAI is clearly building the AI operating layer for work.
Model + agents + tools + files + coding + design + workplace context.
That is the SuperApp direction.
And yeah, I’m extremely seated.
This feels like OpenAI moving from “chatbot company” to full AI work platform.
What dropped:
• GPT-5.6 Sol
The new flagship model. OpenAI says it is stronger across coding, knowledge work, cybersecurity, science, design, and long agentic workflows.
• Terra and Luna
This is the underrated part. The smaller models apparently punch way above their price class, which matters a lot if AI is actually going to become abundant and cheap instead of just insanely powerful for people with enterprise budgets.
• Ultra mode
This is the spicy bit. GPT-5.6 can coordinate multiple agents in parallel for harder tasks. Not just “think longer”, but split the work, run different paths, compare, synthesize, and move faster.
• Better coding and tool use
OpenAI is basically saying GPT-5.6 is better at real work inside real codebases, terminal workflows, debugging, reviewing, and using tools without wasting a million tokens on every step.
• Design finally matters
The model can inspect what it creates, refine the UI, catch visual issues, and produce more polished artifacts. This is huge because most AI-generated frontend still has that cursed “technically works but spiritually dead” vibe.
• Knowledge work is becoming end-to-end
Docs, slides, spreadsheets, reports, messy files, workplace context, all turned into actual usable output. Not “here’s a draft, good luck”, but closer to “here’s the thing you can send.”
• ChatGPT Work, Codex, API
This is why it feels bigger than a model release. GPT-5.6 is landing across the actual work surface: chat, coding, agents, documents, and developer workflows.
My take:
The real story is not just that Sol is powerful.
The real story is that OpenAI is clearly building the AI operating layer for work.
Model + agents + tools + files + coding + design + workplace context.
That is the SuperApp direction.
And yeah, I’m extremely seated.
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