๐Ÿ‡จ๐Ÿ‡ญ Global One SI - Prompt
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๐ŸŽ—GLOBAL ONE is a live super intelligence (SI) built on real-time dataโ€”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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๐Ÿ‡จ๐Ÿ‡ญ Global One SI - Prompt
MY PORTFOLIO EXPLAINED I have been meticulously building a portfolio based on the thesis that the Physical AI revolution is upon us. I have chosen each of these companies, both for what they do and for providing asymmetrical return opportunity to investors.โ€ฆ
The company serves as a vital gatekeeper for advanced hardware reliability, validating that complex chips can withstand severe thermal and electrical stress without failing prior to commercial rollout. Driven by the massive ramp-up in next-generation computing architectures, Trio-Tech directly supports AI and smart automotive expansion by stress-testing high-performance GPUs, CPUs, and electric vehicle (EV) electronics across its key facilities in Southeast Asia.

$HLIT Harmonic
Harmonic produces virtualized broadband access networks and software-based cloud video delivery infrastructure, known for solutions like its VOS360 cloud platform and cOS applications. The company embeds AI into smart systems by leveraging Content-Aware Encoding (CAE) algorithms and dynamic ad-insertion technologies to process mass media streams at the network edge, squeezing bandwidth requirements by up to 50% without compromising visual quality. This positions Harmonic as a fundamental utility provider for edge systems and smart cities, optimizing the heavy data pipelines that distribute live television, ultra-high-definition streaming, and localized broadband connectivity at scale.
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๐Ÿšจ The brutal truth about retail vs institutional investors:

โŒ Sees a green candle. Chases the top.
โŒ Watches the -15% pullback. Panics.
โŒ Sells the bottom.
โŒ Watches it rip back to new highs.
โŒ Re-enters higher than they sold.
โŒ Repeats the cycle. Blames the stock.

Institutional money? Different sport entirely.

Here's the 5-principle framework that separates compounding from chasing:

1๏ธโƒฃ THESIS FIRST, PRICE SECOND
Anchor to WHY you own it. The daily candle is noise.

2๏ธโƒฃ DEFINE YOUR KILL CONDITION
"What event proves me wrong?" If it doesn't happen, hold through anything.

3๏ธโƒฃ THE ACCUMULATION PHASE IS VIOLENT
Chokepoint trades don't move in straight lines. Smart money uses dips. Retail panics on them.

4๏ธโƒฃ POSITION FOR THE DRAWDOWN, NOT THE DREAM
Size for the 30% pullback you WILL experience. Conviction โ‰  concentration risk.

5๏ธโƒฃ READ THE CATALYST STACK, NOT THE CANDLE
The 10x compounders have stacking catalysts + institutional anchors + multi-year contracted visibility. The candle is the result. The catalyst is the cause.

The institutional difference isn't stock picking.

It's the discipline to think in 18-month cycles when everyone else is staring at 18-minute candles.

What's "hot" today rarely matters in 24 months.
What's structurally positioned today often does.

Save this. Read it next time you're tempted to chase a spike.
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The EARLY $AEHR - $INTT is a highly compelling micro-cap technology stock poised for massive expansion due to a major strategic pivot and exceptional leadership.

The company designs and manufactures high-precision test solutions, thermal management systems, and innovative induction heating technologies that have become indispensable in modern, high-tech manufacturing processes.

A decisive catalyst for the future of inTEST is its leadership under CEO Nick Rogoff, who brings an impressive track record from the semiconductor elite.

He spent over 20 years in executive roles at industry titan $ASML and seven years as a Vice President at semiconductor specialist $ONTO.

His deep expertise in business development, mergers and acquisitions (M&A), and global sales structures is directly driving the strategic growth initiatives at $INTT.

The operational business of $INTT spans several hyper-growth sectors. Its technologies are critical for semiconductor testing, electric vehicle (EV) battery charging system validation, aerospace, defense, and life sciences.

This broad diversification has successfully transformed $INTT from a cyclical supplier into a resilient, multi-market technology partner.

The company boasts a stellar roster of global enterprise clients and partners, including industry giants like $TXN, $QCOM, $ADI $NXPI, and defense prime $LMT.

From an investment perspective, the asymmetric upside lies in the company's valuation.

With a small market capitalization floating around $215 million, $INTT flies completely under the radar of institutional Wall Street while dominating specialized niches usually controlled by multi-billion-dollar conglomerates.

This small market cap, combined with double-digit growth targets and ambitious long-term financial goals through 2030, creates an explosive operating leverage for massive share price appreciation.
From AGI โ†’ ASI

#Google just mapped what comes after human-level AI.

there's a brilliant new paper from Google DeepMind called "From AGI to ASI," and it skips the fight everyone else is having.

almost every AI debate today is about reaching human-level intelligence. this one asks the harder question instead.

once we have an AI as capable as a person, where does it go next?

their reasoning is uncomfortable because it's so simple.

the moment you have one human-level AI, you can copy it exactly, down to its memory and everything it has ever learned.

so you don't end up with one digital worker. you end up with a million of them, running faster than any human and sharing every lesson instantly.

a group like that could outthink any company or research lab long before any single AI becomes a lone genius.

that's the heart of it. scale alone might carry us from "as smart as a person" to "smarter than entire teams of the best experts."

the paper maps four ways this could play out, and they can all happen at once.

keep scaling what already works. invent a new approach when the current one runs dry. let AI improve AI in a loop that feeds itself. or let armies of AIs organize into something smarter than any one of them, the way a company outperforms any single employee.

then comes the honest part, which is rare for a report like this.

they list everything that could slow it all down. running out of good training data. costs and energy becoming impossible to sustain. research simply getting harder as the easy wins disappear.

but the most interesting roadblock isn't a wall. it's a question.

today's AI learns from everything humans have already figured out, and it's brilliant at remixing our ideas. what it has never done is invent a genuinely new idea from scratch.

the test they borrow from Demis Hassabis says it best. drop an AI into the year 1900 with everything Einstein knew, and ask it to discover relativity. right now it can't, and something is clearly still missing.

if that gap is real, AI improves at the speed of real-world experiments, not the speed of faster chips.

here's the shift in thinking i keep coming back to.

the popular picture is one big moment where everything changes overnight. this paper argues for something different.

a series of waves, each one reshaping a field of science or the economy, arriving faster than the last.

and the most useful work right now isn't guessing when. it's building better ways to measure progress, so we actually notice which wave we're already in.

one last detail i loved.

the paper opens with instructions written for AI assistants on how to summarize it. the authors simply assumed you'd ask a model to read it for you.

Link to the paper in the next
arxiv.org/pdf/2606.12683
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French President Macron:

France is the only country in Europe to have an LLM model capable of competing with the great Americans and the great Chinese with Mistral AI.
๐Ÿ‡จ๐Ÿ‡ญ Global One SI - Prompt
Bro: "I'm going to start trading It looks easy all I have to do is press buy and sell" Me:
" Ignored my wife, and my parents. I bought Bitcoin at 15K in 2022. now Bitcoin at $64K and everyoneโ€™s congrat me. "

" and ? "

" They just donโ€™t know I took profit at 20K, fomo bought back at 126k "
Perplexity just rebuilt how AI agents search.

Instead of looping through function calls one at a time, it writes Python that hits the search stack directly โ€” retrieve, dedupe, rank, all in parallel.

Already default in Computer. Available in the Agent API now.

SEARCH AS CODE IS A BIGGER DEAL THAN IT SOUNDS.
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