🇨🇭 Global One SI - Prompt
POV: How bros with $17.38 in their portfolio feel when Trump announces Tarrifs
🇺🇸 JUST IN: Trump says European countries targeting US tech companies with a Digital Services Tax will be met with a 100% tariff.
🇨🇭 Global One SI - Prompt
🇺🇸 JUST IN: Trump says European countries targeting US tech companies with a Digital Services Tax will be met with a 100% tariff.
Economic warfare between nations has resumed, and in the end, it is ordinary people who will suffer
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🇨🇭 Global One SI - Prompt
“They will tell you it’s all over, it’s important you don’t believe them”
Until death, all defeat is psychological
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This has nothing to do with controlling his vehicle and even less racing over a mountain pass 😂😂😂
🎉 GPT-5.6 Sol is here! Full public release expected soon. Huge leap over Fable 5! 👀
🧠 Major gains in coding, biology workflows, and cybersecurity
⚡ New “max” and “ultra” reasoning modes with sub-agents
🚀 Will run at up to 750 tokens/sec on Cerebras (coming July)
💰 GPT‑5.6: Sol is $5/$30 ✦ Terra $2.50 /$15 ✦Luna $1/$6
📅 Currently in limited preview for trusted partners
🧠 Major gains in coding, biology workflows, and cybersecurity
⚡ New “max” and “ultra” reasoning modes with sub-agents
🚀 Will run at up to 750 tokens/sec on Cerebras (coming July)
💰 GPT‑5.6: Sol is $5/$30 ✦ Terra $2.50 /$15 ✦Luna $1/$6
📅 Currently in limited preview for trusted partners
OpenAI launches GPT-5.6 and says it is more powerful than Claude Mythos.
This is a new family of 3 models: Sol, Terra, and Luna.
Sol is the most powerful and most expensive.
Terra costs half as much as OpenAI's old top model while performing just as well. Luna is the cheapest and fastest, built for simple, high volume tasks.
OpenAI isn't releasing this to everyone yet.
It's starting with a small group of trusted partners only, and OpenAI says this limited rollout is happening at the request of the US government, before a wider public release in the coming weeks.
OpenAI claims Sol matches Claude Mythos on a cybersecurity test called ExploitBench, while using roughly a third of the computing power Mythos needs for the same task.
During testing, Sol could find security flaws in software and figure out some of the pieces needed to exploit them, but it could not put those pieces together into a fully working attack on its own.
To support its safety claims, OpenAI says it spent the equivalent of over 700,000 high end GPUs worth of computing time trying to find ways the model could be misused or tricked, on top of separate human testing.
This is a new family of 3 models: Sol, Terra, and Luna.
Sol is the most powerful and most expensive.
Terra costs half as much as OpenAI's old top model while performing just as well. Luna is the cheapest and fastest, built for simple, high volume tasks.
OpenAI isn't releasing this to everyone yet.
It's starting with a small group of trusted partners only, and OpenAI says this limited rollout is happening at the request of the US government, before a wider public release in the coming weeks.
OpenAI claims Sol matches Claude Mythos on a cybersecurity test called ExploitBench, while using roughly a third of the computing power Mythos needs for the same task.
During testing, Sol could find security flaws in software and figure out some of the pieces needed to exploit them, but it could not put those pieces together into a fully working attack on its own.
To support its safety claims, OpenAI says it spent the equivalent of over 700,000 high end GPUs worth of computing time trying to find ways the model could be misused or tricked, on top of separate human testing.
🇨🇭 Global One SI - Prompt
The triumvirate is real. Where do you align in this age? The choice is real.
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It's a tremendous matrix. The best matrix. It has agents like you have not seen before. You would not believe it.
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Central banks just bought 15x more gold than they officially admitted.
The buying is real,the reporting is a smokescreen.
The World Gold Council estimates central banks added 244 tonnes of gold in Q1 2026.
But the official IMF data shows only about 16 tonnes of reported purchases.
That gap is enormous.
Roughly 228 tonnes, about 93% of the total, went unreported.
WGC infers the rest from trade data, vault flows, and balance of payments gaps, not official disclosures.
The "15x more than reported" headline is sensational, but directionally it's accurate.
Here's why it matters.
The hidden buyers are mostly emerging market central banks, led by China and Asia.
They're stockpiling gold as a de-dollarization and sanctions hedge, and they prefer to disclose late or not at all.
The pattern is structural, not a blip.
Over 200 tonnes added in 10 of the last 11 quarters.
And it continues even with gold near record highs.
That tells you the buying is strategic, not price sensitive.
When the biggest buyers don't care about price and won't show their hand, that's a powerful floor under gold.
The buying is real,the reporting is a smokescreen.
The World Gold Council estimates central banks added 244 tonnes of gold in Q1 2026.
But the official IMF data shows only about 16 tonnes of reported purchases.
That gap is enormous.
Roughly 228 tonnes, about 93% of the total, went unreported.
WGC infers the rest from trade data, vault flows, and balance of payments gaps, not official disclosures.
The "15x more than reported" headline is sensational, but directionally it's accurate.
Here's why it matters.
The hidden buyers are mostly emerging market central banks, led by China and Asia.
They're stockpiling gold as a de-dollarization and sanctions hedge, and they prefer to disclose late or not at all.
The pattern is structural, not a blip.
Over 200 tonnes added in 10 of the last 11 quarters.
And it continues even with gold near record highs.
That tells you the buying is strategic, not price sensitive.
When the biggest buyers don't care about price and won't show their hand, that's a powerful floor under gold.
🇨🇭 Global One SI - Prompt
China Robotics Startup Map 2026 ➤ China Robotics: • 2000+ robotics startups ➝ 50+ humanoid robot companies ➝ $13B+ funding from 2015 to 2025 ‣ Humanoid robots ➝ Unitree ➝ AgiBot ➝ Fourier ➝ EngineAI ‣ Industrial robots ➝ Estun ➝ Efort ➝ Siasun…
Global Humanoid Robot Suppliers Map 2026
The humanoid race is becoming a full supply chain war.
• 100+ suppliers worldwide
• 50+ humanoid robot companies
• $15B+ projected humanoid market by 2030
➤ North America
Tesla
Figure
Agility Robotics
Apptronik
Sanctuary AI
Boston Dynamics
➤ China
Unitree
UBTECH
AGIBOT
Fourier
XPeng
Leju Robot
Keenon
➤ Europe
NEURA Robotics
PAL Robotics
Aldebaran
Ericsson
iRonCub3
➤ Japan / Korea
Toyota
Honda
Sony
Samsung
Rainbow Robotics
➤ Rest of Asia
Xiaomi
LimX Dynamics
PaXini
Hyundai Robotics
The winners will need more than a robot body.
They need:
• Core components
➝ Harmonic Drive
➝ Nabtesco
➝ MAXON
• Actuators and motors
➝ Siemens
➝ Yaskawa
➝ Inovance
• Sensors and perception
➝ Ouster
➝ Hesai
➝ RoboSense
➝ Sony IMX
• Batteries and power
➝ CATL
➝ BYD
➝ Panasonic
➝ LG Energy Solution
• AI and software
➝ NVIDIA
➝ Microsoft
➝ Google DeepMind
➝ OpenAI
➝ Huawei MindSpore
• Manufacturing and ODM
➝ Foxconn
➝ Flex
➝ Jabil
➝ Pegatron
• Testing and QA
➝ TÜV SÜD
➝ SGS
➝ Intertek
➝ UL Solutions
• System integration
➝ Accenture
➝ Deloitte
➝ Capgemini
➝ SoftBank Robotics
Humanoid robots are not one product category anymore.
They are becoming a global industrial stack.
Hardware. Actuation. Perception. Batteries. AI. Manufacturing. Deployment.
The humanoid race is becoming a full supply chain war.
• 100+ suppliers worldwide
• 50+ humanoid robot companies
• $15B+ projected humanoid market by 2030
➤ North America
Tesla
Figure
Agility Robotics
Apptronik
Sanctuary AI
Boston Dynamics
➤ China
Unitree
UBTECH
AGIBOT
Fourier
XPeng
Leju Robot
Keenon
➤ Europe
NEURA Robotics
PAL Robotics
Aldebaran
Ericsson
iRonCub3
➤ Japan / Korea
Toyota
Honda
Sony
Samsung
Rainbow Robotics
➤ Rest of Asia
Xiaomi
LimX Dynamics
PaXini
Hyundai Robotics
The winners will need more than a robot body.
They need:
• Core components
➝ Harmonic Drive
➝ Nabtesco
➝ MAXON
• Actuators and motors
➝ Siemens
➝ Yaskawa
➝ Inovance
• Sensors and perception
➝ Ouster
➝ Hesai
➝ RoboSense
➝ Sony IMX
• Batteries and power
➝ CATL
➝ BYD
➝ Panasonic
➝ LG Energy Solution
• AI and software
➝ NVIDIA
➝ Microsoft
➝ Google DeepMind
➝ OpenAI
➝ Huawei MindSpore
• Manufacturing and ODM
➝ Foxconn
➝ Flex
➝ Jabil
➝ Pegatron
• Testing and QA
➝ TÜV SÜD
➝ SGS
➝ Intertek
➝ UL Solutions
• System integration
➝ Accenture
➝ Deloitte
➝ Capgemini
➝ SoftBank Robotics
Humanoid robots are not one product category anymore.
They are becoming a global industrial stack.
Hardware. Actuation. Perception. Batteries. AI. Manufacturing. Deployment.
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🇨🇭 Global One SI - Prompt
UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models The pressure is coming from extreme bills, including users spending up to $35K/month, teams exceeding quotas by 200%, and companies cutting internal…
Trump and the US government just handed China the easiest win in the AI race.
60% of companies are already rerouting their AI spend toward cheaper, open-source models - and most of the best ones are Chinese (Qwen, DeepSeek, GLM, Kimi).
US frontier models are now being gatekept by the government AND priced at a premium for only marginal gains in intelligence.
To be fair, this is a genuinely hard spot for the US:
On one hand, you want America to lead AI innovation (especially so that you, as the government, can have access).
But you also want the most powerful models secured and controlled for national security reasons.
The problem is that those two goals are now directly at odds.
Every restriction placed on US frontier models makes the open-source alternative more attractive.
And for now, the best open-source alternatives aren't American.
Going to be very interesting to watch things play out from here.
60% of companies are already rerouting their AI spend toward cheaper, open-source models - and most of the best ones are Chinese (Qwen, DeepSeek, GLM, Kimi).
US frontier models are now being gatekept by the government AND priced at a premium for only marginal gains in intelligence.
To be fair, this is a genuinely hard spot for the US:
On one hand, you want America to lead AI innovation (especially so that you, as the government, can have access).
But you also want the most powerful models secured and controlled for national security reasons.
The problem is that those two goals are now directly at odds.
Every restriction placed on US frontier models makes the open-source alternative more attractive.
And for now, the best open-source alternatives aren't American.
Going to be very interesting to watch things play out from here.
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"The share of tokens used for US models on OpenRouter has collapsed" Bloomberg
On OpenRouter, US model token share fell from around 70% to around 30% in a year.
A clean warning signal.
open-weight Chinese models are becoming capable enough for routine work, cheaper to run, easier to customize, and less dependent on permission from a frontier lab.
On OpenRouter, US model token share fell from around 70% to around 30% in a year.
A clean warning signal.
open-weight Chinese models are becoming capable enough for routine work, cheaper to run, easier to customize, and less dependent on permission from a frontier lab.
I don’t think AI takes all jobs overnight.
That’s the cartoon version.
The real transition will be slower and much weirder: AI takes tasks first, then teams shrink, hiring slows, entry-level jobs disappear, and companies quietly realize they need fewer humans every year.
McKinsey already estimates that up to 30% of US work hours could be automated by 2030. The World Economic Forum expects 92 million jobs to be displaced by 2030, even while new jobs are created.
So no, everyone won’t be jobless next Monday.
But over the next 15 years, the pressure keeps building.
The obvious transition isn’t “no work.”
It’s 5 days becoming 4.
Then maybe 3.
Then the real question begins.
That’s the cartoon version.
The real transition will be slower and much weirder: AI takes tasks first, then teams shrink, hiring slows, entry-level jobs disappear, and companies quietly realize they need fewer humans every year.
McKinsey already estimates that up to 30% of US work hours could be automated by 2030. The World Economic Forum expects 92 million jobs to be displaced by 2030, even while new jobs are created.
So no, everyone won’t be jobless next Monday.
But over the next 15 years, the pressure keeps building.
The obvious transition isn’t “no work.”
It’s 5 days becoming 4.
Then maybe 3.
Then the real question begins.
🇨🇭 Global One SI - Prompt
$IBM/USD H2 #Indicator #Signal #Trading #GlobalOneAI Globalone.ch #Prompt #AI
$IBM unveils world's first publicly announced sub-1nm chip technology 👀
They just unveiled NanoStack, a breakthrough 3D transistor architecture designed for the 7 Å (~0.7 nm) technology node, making it the world's first publicly announced chip technology below 1 nanometer.
Instead of placing transistors side by side, NanoStack stacks them vertically, allowing nearly 100 billion transistors to fit on a silicon chip about the size of a fingernail while dramatically increasing transistor density.
IBM says its prototype delivers up to 50% higher performance or up to 70% lower power consumption compared with its 2 nm research chip introduced in 2021.
Acceleration is everywhere!
They just unveiled NanoStack, a breakthrough 3D transistor architecture designed for the 7 Å (~0.7 nm) technology node, making it the world's first publicly announced chip technology below 1 nanometer.
Instead of placing transistors side by side, NanoStack stacks them vertically, allowing nearly 100 billion transistors to fit on a silicon chip about the size of a fingernail while dramatically increasing transistor density.
IBM says its prototype delivers up to 50% higher performance or up to 70% lower power consumption compared with its 2 nm research chip introduced in 2021.
Acceleration is everywhere!