πŸ‡¨πŸ‡­ Global One SI - Prompt
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πŸŽ—GLOBAL ONE is a live super intelligence (SI) built on real-time dataβ€”designed for decisions. Currently focused on global financial markets

t.me/Prompts_SI @Global_one - Software/Developer/Programmer - Globalone.ch - Prompt - AI - Super Intelligence
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πŸ‡¨πŸ‡­ Global One SI - Prompt
Welcome #WTI
Safe to say the Strait of Hormuz is still closed.

Once global SPR levels are run down suddenly this illusion faces reality.

Two possible scenarios could play out here:
1. If the Federal Reserve is forced to do QE because of a financial crisis, without lockdowns, oil could easily rise to $200 a barrel.

2. Technically you don't even really need QE, all you need is nations to suddenly decide they need to refill their SPR. Then it becomes a panic for both Dollars and oil, which is something we've only seen briefly once before in 2022.

The end result of both scenarios is a global sovereign debt crisis, as nations are forced to liquidate US treasuries and gold to acquire oil with a skyrocketing Dollar.
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πŸ‡¨πŸ‡­ Global One SI - Prompt
Where humanoid robots are actually deployed Humanoid robots are not sold like cars yet. Most companies do not publish regional sales data so this chart tracks only what can be verified: β€’ commercial deployments β€’ pilots β€’ field tests β€’ research installs…
This map separates what is actually documented from what is still only demo visibility.

β€’ Tesla Optimus
➝ Factory pilot in North America

β€’ AGIBOT A2 / A2-W
➝ Commercial delivery signals in China

β€’ Fourier GR-1 / GR-2
➝ Rehab research pilots in China
➝ Demo presence in North America and Europe

β€’ NEURA 4NE-1
➝ Launch demos in Europe

β€’ XPENG IRON
➝ Public reveal in China

β€’ Leju KUAVO
➝ Education and service use in China
➝ Demo presence in Asia

β€’ Kepler Forerunner K2
➝ Factory pilot signal in China
➝ Expo demo in Europe

β€’ Persona AI
➝ Shipyard pilot in North America

β€’ MagicLab MagicBot
➝ Industrial pilot signal in China

β€’ Robot Era STAR1
➝ Public demos in China

Important detail
No public regional sales percentages are available.

So this is not a sales ranking.
It is a deployment signal map based on official public information.

The humanoid race is wider than the 5 names everyone repeats.
If you're not making enough money now, then you're not doing enough
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Anthropic wants to make its own drugs with help from Claude.

Claude Science is meant to do for lab research what Claude Code did for programming.

Drug discovery is messier, because molecules fail when biology, chemistry, safety, or dosing breaks.

Anthropic wants its researchers to feel those failures directly while shaping the product.

The first programs will target neglected diseases, including rare disorders and some tropical conditions.

These areas often have clearer biology but weaker commercial incentives than common diseases.

Many rare genetic disorders start with one broken gene, giving AI a cleaner target.

Common conditions usually involve many genes, tissues, histories, and environments interacting at once.

That difference makes early rare-disease work a harder business, but a clearer testbed.

Anthropic also avoids competing with pharma customers by choosing overlooked programs.

Anthropic already works closely with major drugmakers, so it understands where researchers get stuck.

Novartis CEO Vas Narasimhan joining the board gives those product decisions direct pharma-level pressure.

Anthropic bought Coefficient Bio and hired AlphaFold researcher John Jumper, so this is not a side experiment. Shows how seriously Anthropic is treating biology.
The AI capex cycle is now pushing memory into a much more aggressive pricing upcycle than expected.

UBS now expects DRAM prices to rise 32% quarter-over-quarter in Q3 and 18% in Q4, while NAND prices are expected to rise 30% in Q3 and 12% in Q4.

AI infrastructure is eating memory supply faster than the industry can add it. High Bandwidth Memory, DRAM, and NAND are all getting pulled into the same demand wave. UBS also sees the DRAM market staying undersupplied until at least 2028, because demand growth in 2027 is expected to be far above supply growth.
Sonnet 5 might be the worst-value model on this chart...

Cost per intelligence index task:

>1.3x more expensive than opus 4.8 max
>2.2x more expensive than gpt-5.5 xhigh
>4.8x more expensive than glm-5.2 max
>7.4x more expensive than kimi k2.6
>57x more expensive than deepseek v4 pro

And it still isn’t the strongest model here...

You’re not paying for better intelligence.

You’re paying the anthropic tax.
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πŸ‡¨πŸ‡­ Global One SI - Prompt
POV: How bros with $17.38 in their portfolio feel when Trump announces Tarrifs
Everyone said tariffs would kill US manufacturing.
The data says otherwise.

US ISM Manufacturing PMI (50 = expansion line):

2022-2025:

β†’ Mostly stuck below 50 for 2.5 straight years
β†’ Brief pokes above 50, never sustained

2026:

β†’ Broke above 50 in February
β†’ 5 straight months above the line
β†’ Hit 54 in June, the highest print since mid-2022

The predicted collapse never showed up in the data.

Europe should be reading this chart, not the headlines.
πŸ‡¨πŸ‡­ Global One SI - Prompt
How to turn Hermes into your personal assistant (save this)
Claude Fable is insane for UI/UX design work.

Inject this prompt into Claude Code, and you'll be able to ship Apple-style liquid glass design into ANY vibe-coded workflow:

(works in apps, websites, dashboard & more)
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You cannot build an AI data center without gas power.

Even renewable-first governments admit it now.

Global new gas power capacity jumped 31% in a year, to 1,047 GW in 2025:

πŸ‡ΊπŸ‡Έ US: 252 GW in development, a third tied to data centers, 2024 gas restrictions abolished in 2025

πŸ‡¨πŸ‡³ China: 153 GW in development

πŸ‡©πŸ‡ͺ Germany: passed a 9 GW gas bidding law in May, reversing years of gas reduction

πŸ‡―πŸ‡΅ Japan: more long-term LNG procurement for AI and chip demand

πŸ‡»πŸ‡³ Vietnam: named LNG a core pillar of its 2030 power plan

πŸ‡°πŸ‡· South Korea: Samsung's VC publicly requesting more LNG for new fabs

Renewables didn't replace gas and AI made gas necessary again.
β€œClaude code will kill software engineers”...

Absolutely not.

The best software engineers will earn 50-100x more than average developers...

Because their job is shifting from writing every line of code to leading teams of ai agents.

>Design the architecture
>Coordinate multiple agents
>Review their output
>Catch failures before production
>Turn generated code into reliable systems

The more agents you can control and manage effectively, the more valuable you become.

Ai makes the gap between average and exceptional engineers much bigger.
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When you spend 4 years studying hard for an IT degree only to become a nurse because AI took your job before graduation
🌍 One map explains why geopolitics moves markets.

It shows each country’s number 1 export.

πŸ”ΉOil in the Middle East and Russia.

πŸ”ΉElectronics and machinery in China.

πŸ”ΉCapital goods, aerospace and telecom in the US.

πŸ”ΉCars and parts across Germany, Europe and Canada.

πŸ”ΉCopper in Chile. Coal in Australia. Crops, minerals and energy across Africa and South America.

The point is simple: globalization is not evenly spread.

It depends on a few critical nodes: energy, factories, metals, logistics and high-value industrial tools.

Disrupt one of them with tariffs, sanctions, war, shipping delays or export controls and the shock does not stay local.

It becomes inflation, commodity volatility and a global repricing of risk.

The next winners will not just be countries with resources.

They will be the ones that control processing, logistics, technology and supply-chain redundancy.
A list of useful AI workflows to tackle this weekend (pick a couple):

β€’ Hermes agent setup
β€’ Second-brain via Claude Code x Obsidian
β€’ TradingView MCP connection (for traders)
β€’ Deep financial research via perplexity finance
β€’ Personal OS dashboard w/ Fable 5
β€’ Learn loop engineering (full article on this page)
β€’ NotebookLM for research *any topic*
β€’ Set up Claude Skills for your repetitive workflows
β€’ Build Notion database as your central hub (then insert agents to manage it)

SO much to do in AI right now.
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πŸ‡¨πŸ‡­ Global One SI - Prompt
How to build a self-evolving AI brain with Hermes agent x Obsidian
This Anthropic engineer ( #RLanceMartin ) recently shared his full guide on how to run /loops with Fable 5.

If you're new to loop engineering and want to run fully autonomous Fable workflows, take notes
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πŸ‡¨πŸ‡­ Global One SI - Prompt
GMKtec EVO-X3 launches July 6. 3rd-Gen Local AI Supercomputing Mini PC. AMD Ryzen AI Max+ 395 APU. 4TB stock storage. Native offline Qwen3 235B support. OCuLink eGPU expansion. GMKtec Claw AI Suite. The new EVO-X3 is getting ready for release. What eGPU…
If anyone is looking to build a multi-card rig for Local AI, current price ranges for working and new boards on Ebay show price stabilization. Deals can be found.

πŸ”Ή RTX-5090 (32GB) $3,599 - $5,199
πŸ”Ή RTX-4090 (24GB) $2,099 - $4,499
πŸ”Ή RTX-3090 (24GB) $1,100 - $2,000
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πŸ‡¨πŸ‡­ Global One SI - Prompt
How to build a self-evolving AI brain with Hermes agent x Obsidian
This is the prompt Yale and Univ of Chicago researchers used when asking LLMs for new research ideas.

Feed LLMs prior work, ask for ideas, then measure how repetitive the ideas get.

The surprising finding is that LLMs often treat research ideation as connecting what already exists, while humans use a wider set of problem-finding moves.

LLM-generated ideas reveal a bias toward safe bridge-and-combine proposals.
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