๐จ๐ญ 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.โฆ
$SEYE Smart Eye
Smart Eye makes computer-vision hardware and software platforms dedicated to Human Insight AI, tracking eye gaze, facial expressions, and head movements in real time. The companyโs primary footprint is in the automotive sector, where its edge-based Driver Monitoring Systems (DMS) and interior cabin sensing modules identify operator distraction, drowsiness, and cognitive load to comply with global safety mandates. This technology bridges the human-machine interface across smart transportation and autonomous vehicles, while its subsidiaries (like Affectiva) extend this technology into emotion AI, which is increasingly utilized in behavioral research, aerospace simulators, and interactive robotics.
$AMBA Ambarella
Ambarella builds ultra-low-power, high-efficiency system-on-chip (SoC) vision and radar processors built on its algorithm-first CVflow artificial intelligence architecture. Its chips, like the 4nm CV7 and the high-compute N1 series, serve as the localized brain for Edge AI, industrial robotics, and smart city infrastructure by running complex convolutional and transformer neural networks simultaneously. By integrating advanced image signal processing, hardware-accelerated video encoding, and native neural network computation on a single die, Ambarella allows security cameras, aerial drones, and autonomous mobile robots (AMRs) to execute edge-based multi-sensor perception, visual odometry, and real-time SLAM (Simultaneous Localization and Mapping) entirely disconnected from the cloud.
$OUST Ouster
Ouster designs and manufactures high-resolution 3D digital LiDAR sensors alongside integrated perception suites, following its strategic combination with Stereolabs' ZED camera technology. By embedding native color and precise spatial mapping directly onto its proprietary silicon architecture, Ouster creates an end-to-end sensing platform for Physical AI. This hardware acts as the primary sensory organ for humanoid robotics, warehouse automation, autonomous mining fleets, and smart city infrastructure (via its BlueCity traffic management software), delivering low-latency, resilient environmental data that allows machines to map, track, and safely navigate complex physical spaces.
$AMZN Amazon
Within the AI and robotics verticals, Amazon develops custom infrastructure siliconโsuch as its proprietary Trainium and Inferentia acceleration chipsโwhile engineering vast, automated logistics systems for its global fulfillment network. The company is a pioneer in warehouse robotics, deploying fleets of fully autonomous mobile robots like Proteus and intelligent manipulation systems like Sparrow to streamline its supply chain via machine learning and reinforcement learning. On the edge, Amazon implements localized AI and natural language processing through consumer ecosystems like Alexa, Ring, and the Astro home robot, establishing a ubiquitous presence across cloud AI architecture, industrial automation, and smart home systems.
$ELMT Elmet Group
Elmet Group fabricates precision-engineered components and high-power radio frequency (RF) or microwave equipment, operating through its Critical Materials Components and Engineered Microwave Products divisions. Specializing in the custom manufacturing of refractory metals like pure tungsten and molybdenum, Elmet supplies the foundational, high-durability hardware components required for advanced semiconductor fabrication, aerospace systems, and defense electronics. It fits into the advanced hardware and AI supply chain by delivering the critical thermal management substrates, ion implantation shielding, and robust RF distribution modules necessary to manufacture and run high-energy compute chips.
$TRT Trio-Tech International
Trio-Tech provides semiconductor back-end testing services and manufactures heavy-duty reliability equipment, including customized burn-in boards, wet process stations, and environmental testing chambers.
Smart Eye makes computer-vision hardware and software platforms dedicated to Human Insight AI, tracking eye gaze, facial expressions, and head movements in real time. The companyโs primary footprint is in the automotive sector, where its edge-based Driver Monitoring Systems (DMS) and interior cabin sensing modules identify operator distraction, drowsiness, and cognitive load to comply with global safety mandates. This technology bridges the human-machine interface across smart transportation and autonomous vehicles, while its subsidiaries (like Affectiva) extend this technology into emotion AI, which is increasingly utilized in behavioral research, aerospace simulators, and interactive robotics.
$AMBA Ambarella
Ambarella builds ultra-low-power, high-efficiency system-on-chip (SoC) vision and radar processors built on its algorithm-first CVflow artificial intelligence architecture. Its chips, like the 4nm CV7 and the high-compute N1 series, serve as the localized brain for Edge AI, industrial robotics, and smart city infrastructure by running complex convolutional and transformer neural networks simultaneously. By integrating advanced image signal processing, hardware-accelerated video encoding, and native neural network computation on a single die, Ambarella allows security cameras, aerial drones, and autonomous mobile robots (AMRs) to execute edge-based multi-sensor perception, visual odometry, and real-time SLAM (Simultaneous Localization and Mapping) entirely disconnected from the cloud.
$OUST Ouster
Ouster designs and manufactures high-resolution 3D digital LiDAR sensors alongside integrated perception suites, following its strategic combination with Stereolabs' ZED camera technology. By embedding native color and precise spatial mapping directly onto its proprietary silicon architecture, Ouster creates an end-to-end sensing platform for Physical AI. This hardware acts as the primary sensory organ for humanoid robotics, warehouse automation, autonomous mining fleets, and smart city infrastructure (via its BlueCity traffic management software), delivering low-latency, resilient environmental data that allows machines to map, track, and safely navigate complex physical spaces.
$AMZN Amazon
Within the AI and robotics verticals, Amazon develops custom infrastructure siliconโsuch as its proprietary Trainium and Inferentia acceleration chipsโwhile engineering vast, automated logistics systems for its global fulfillment network. The company is a pioneer in warehouse robotics, deploying fleets of fully autonomous mobile robots like Proteus and intelligent manipulation systems like Sparrow to streamline its supply chain via machine learning and reinforcement learning. On the edge, Amazon implements localized AI and natural language processing through consumer ecosystems like Alexa, Ring, and the Astro home robot, establishing a ubiquitous presence across cloud AI architecture, industrial automation, and smart home systems.
$ELMT Elmet Group
Elmet Group fabricates precision-engineered components and high-power radio frequency (RF) or microwave equipment, operating through its Critical Materials Components and Engineered Microwave Products divisions. Specializing in the custom manufacturing of refractory metals like pure tungsten and molybdenum, Elmet supplies the foundational, high-durability hardware components required for advanced semiconductor fabrication, aerospace systems, and defense electronics. It fits into the advanced hardware and AI supply chain by delivering the critical thermal management substrates, ion implantation shielding, and robust RF distribution modules necessary to manufacture and run high-energy compute chips.
$TRT Trio-Tech International
Trio-Tech provides semiconductor back-end testing services and manufactures heavy-duty reliability equipment, including customized burn-in boards, wet process stations, and environmental testing chambers.
๐จ๐ญ 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.โฆ
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.
$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.
โ1
๐จ The brutal truth about retail vs institutional investors:
โ Sees a green candle. Chases the top.
โ Watches the -15% pullback. Panics.
โ Sells the bottom.
โ Watches it rip back to new highs.
โ Re-enters higher than they sold.
โ Repeats the cycle. Blames the stock.
Institutional money? Different sport entirely.
Here's the 5-principle framework that separates compounding from chasing:
1๏ธโฃ THESIS FIRST, PRICE SECOND
Anchor to WHY you own it. The daily candle is noise.
2๏ธโฃ DEFINE YOUR KILL CONDITION
"What event proves me wrong?" If it doesn't happen, hold through anything.
3๏ธโฃ THE ACCUMULATION PHASE IS VIOLENT
Chokepoint trades don't move in straight lines. Smart money uses dips. Retail panics on them.
4๏ธโฃ POSITION FOR THE DRAWDOWN, NOT THE DREAM
Size for the 30% pullback you WILL experience. Conviction โ concentration risk.
5๏ธโฃ 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.
โ Sees a green candle. Chases the top.
โ Watches the -15% pullback. Panics.
โ Sells the bottom.
โ Watches it rip back to new highs.
โ Re-enters higher than they sold.
โ Repeats the cycle. Blames the stock.
Institutional money? Different sport entirely.
Here's the 5-principle framework that separates compounding from chasing:
1๏ธโฃ THESIS FIRST, PRICE SECOND
Anchor to WHY you own it. The daily candle is noise.
2๏ธโฃ DEFINE YOUR KILL CONDITION
"What event proves me wrong?" If it doesn't happen, hold through anything.
3๏ธโฃ THE ACCUMULATION PHASE IS VIOLENT
Chokepoint trades don't move in straight lines. Smart money uses dips. Retail panics on them.
4๏ธโฃ POSITION FOR THE DRAWDOWN, NOT THE DREAM
Size for the 30% pullback you WILL experience. Conviction โ concentration risk.
5๏ธโฃ 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.
๐ฟ1
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.
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
#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
โ1
๐จ๐ญ Global One SI - Prompt
Portfolio analytics with Monte Carlo simulations 100% open source. Get it here free: github.com/ranaroussi/quantstats
OpenBB: A free alternative to the $20,000 Bloomberg Terminal
Available 100% free on GitHub: github.com/OpenBB-finance/OpenBB
Available 100% free on GitHub: github.com/OpenBB-finance/OpenBB
โ1
๐จ๐ญ Global One SI - Prompt
๐จ The brutal truth about retail vs institutional investors: โ Sees a green candle. Chases the top. โ Watches the -15% pullback. Panics. โ Sells the bottom. โ Watches it rip back to new highs. โ Re-enters higher than they sold. โ Repeats the cycle. Blamesโฆ
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Bro: "I'm going to start trading It looks easy all I have to do is press buy and sell"
Me:
Me:
๐จ๐ญ 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:
" i heard people made millions of dollars from trading "
me:
me:
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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.
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.
๐จ๐ญ 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 everyoneโs congrat me. "
" and ? "
" They just donโt know I took profit at 20K, fomo bought back at 126k "
" and ? "
" They just donโt know I took profit at 20K, fomo bought back at 126k "
๐จ๐ญ Global One SI - Prompt
๐ฅ IRAN WAR - THE MOVIE๐ฅ
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US negotiators after israel blows the iran deal for the 60th time
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.
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.
๐1
๐จ๐ญ Global One SI - Prompt
US negotiators after israel blows the iran deal for the 60th time
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๐จ๐ญ Global One SI - Prompt
The Goldman Sachs prediction model for the FIFA World Cup is out: ๐ช๐ธ Spain: 26% ๐ซ๐ท France: 19% ๐ฆ๐ท Argentina: 14% ๐ง๐ท Brazil: 8% ๐ด๓ ง๓ ข๓ ฅ๓ ฎ๓ ง๓ ฟEngland: 5% Goldman Sachs has predicted Spain to win the 2026 World Cup using probabilities. github.com/ddm7018/Eloโฆ
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When you try to sleep after losing your bet because some random guy scored in the 90+8th minute:
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US-Iran signing deal