$QCOM
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$QCOM — The Phone Chip Company That’s Actually a Robot Chip Company The market still prices Qualcomm as a smartphone play. Qualcomm’s Dragonwing IQ10 SoC enables low-power decision-making for drones, robots, and AVs beyond the cloud. When Physical AI re-rating hits this ticker, the gap closes fast.
10 AI Infrastructure Stocks I’m Watching for the Long Game 1. $MU — Memory Is Now a Strategic Asset Micron posted record Q2 FY2026 revenue of $23.86B — nearly 3x the same quarter last year — with record gross margins, EPS, and free cash flow.  HBM capacity is completely sold out through calendar 2026, with pricing locked in on the vast majority of that volume.  Memory is no longer cyclical commodity — it’s the bottleneck of the AI era. 2. $MRVL — The Custom Silicon Kingmaker Marvell delivered record FY2026 revenue of $8.195B, up 42% YoY, with custom AI chip wins at Amazon, Microsoft, and Google anchoring its growth.  Its 800G and 1.6T optical DSPs have become the essential “plumbing” for hyperscale AI clusters.  The most underrated AI infrastructure name hiding in plain sight. 3. $CRDO — The High-Speed Connectivity Pure Play Management is guiding over 50% YoY revenue growth for fiscal 2027 as AI infrastructure scales rapidly.  Rothschild & Co Redburn just launched coverage with a Buy and a $206 price target tied to surging generative AI infrastructure spending.  Ultra-low power, ultra-high speed — exactly what AI data centers need. 4. $AAOI — America’s 800G Transceiver Champion AOI completed its first volume shipment of 800G products to a large hyperscale customer in Q1 2026 and is guiding for sequential revenue growth throughout the year, with significantly larger growth expected in Q3 as additional capacity comes online.  They’re building a 210,000 sq ft manufacturing facility in Sugar Land, TX with up to $300M in planned investment to become one of the largest domestic suppliers of AI datacenter transceivers.  5. $AXTI — The Indium Phosphide Supercycle AXT hit Q1 2026 revenue of $26.9M, up 39% YoY, with InP backlog exceeding $100M, and is doubling indium phosphide capacity in both 2026 and 2027.  Order demand for scale-out optics could grow 2x in 2026 and another 2x in 2027  — and every optical transceiver in every AI data center needs InP. This is the upstream pick-and-shovel few are talking about. 6. $INTC — The Turnaround Nobody Wants to Believe In Intel is partnering with Nokia and Dell to advance next-gen 5G edge infrastructure, with its Xeon 6 Granite Rapids-D SoC delivering enhanced AI capabilities for far-edge deployments.  Foundry ambitions, US manufacturing tailwinds, and a deeply reset valuation. High risk — but if the turnaround lands, the upside is asymmetric. 7. $AMD — The Challenger That Keeps Gaining Ground The iShares Semiconductor ETF is up 77% this year, with AMD among the key beneficiaries of AI infrastructure investment.  MI300X traction in inference, custom silicon partnerships, and a data center GPU roadmap that has Nvidia watching closely. The market keeps underestimating this one. 8. $QCOM — Beyond Phones, Into Physical AI Qualcomm posted $10.6B in Q2 FY2026 revenue with record quarterly QCT automotive revenues, and combined automotive + IoT revenues up 20% YoY.  Momentum across personal, industrial and physical AI is growing  — this is no longer just a smartphone chipmaker. Edge AI, autonomous systems, and robotics are the next chapters. 9. $NOK — The AI-Native Network Play Nokia is delivering advanced optical and IP data center connectivity to power AI computing across continents, while partnering with NVIDIA to define the next generation of global connectivity in the AI-native wireless era.  Deeply undervalued relative to its AI infrastructure footprint. Patient capital play. 10. $ARM — The Architecture Running AI Everywhere In March 2026, Arm made history by launching its first-ever production silicon — the Arm AGI CPU — a data center processor for agentic AI workloads, developed with Meta, delivering more than 2x performance per rack vs. x86 platforms.  Arm’s compute platform now supports AI workloads ranging from milliwatts to gigawatts — from edge to cloud.  Every AI chip runs on Arm’s architecture. The royalty engine of the AI age.
THE CPU RENAISSANCE THESIS The Structural Shift Nobody Priced In This isn’t cyclical. It’s architectural. The AI compute stack is undergoing a fundamental transition. Training workloads use 7–8 GPUs per CPU. Inference tightens that to 3–4 GPUs per CPU. And in agentic/multi-agent AI, the ratio could compress to 1:1 — or even flip in favor of CPUs.  Tool processing on CPUs can account for up to 90.6% of total latency in agentic workflows  — meaning GPU throughput improvements alone don’t solve the bottleneck. You need more CPUs. $AMD — The Real Winner Here AMD’s EPYC CPUs now command 46.2% of total server CPU spending in Q1 2026 — an all-time high — driven by rising AI and data center demand.  AMD CEO Lisa Su doubled the server CPU TAM forecast: “We now expect the server CPU TAM to grow at greater than 35% annually, reaching over $120 billion by 2030.” AMD expects server CPU revenue to grow more than 70% YoY in Q2 2026.  Why $AMD over $INTC long-term? Intel has supply constraints and manufacturing yield challenges. AMD is fabbed at TSMC — cleaner execution, faster ramp. Intel’s planned 2026 launches face in-house process yield issues that may accelerate AMD’s market share gains further.  $ARM — The Silent Monopolist This is the most underappreciated play in the entire theme. ARM’s market share of CPU compute now represents ~50% among top hyperscalers. Data centers are expected to require more than 4x current CPU capacity per gigawatt as agentic AI scales — creating a market opportunity of more than $100 billion by 2030.  ARM launched the Arm AGI CPU — its first production silicon purpose-built for agentic AI. It delivers more than 2x performance per rack vs. x86-based platforms, reducing AI data center CapEx by up to $10 billion per gigawatt. Meta is the lead partner and co-developer.  Customer demand for ARM AGI CPUs already exceeded $2 billion across FY2027–FY2028 shortly after launch.  ARM wins whether Intel wins, AMD wins, or custom silicon wins — because they license the architecture underneath all of it. It’s the IP royalty on the entire CPU renaissance. $INTC — Turnaround Optionality Intel CEO Lip-Bu Tan: “For the last few years, the story around high-performance computing was almost exclusively about GPU and other accelerators. In recent months, we have seen clear signs that the CPU is reinserting itself as the indispensable foundation of the AI era.”  $INTC is higher risk — manufacturing execution is the key variable. But if 18A yields hit mid-year targets and Xeon 6+ ramps, this is a multi-year re-rating story from deeply depressed levels. $NVDA — Still Wins, But Differently Beyond traditional server CPU vendors Intel and AMD, NVIDIA is now entering the server CPU market  via Arm-based Grace architecture. NVDA is vertically integrating — building CPU+GPU stacks together. Grace Blackwell is the proof of concept. Long-term this is bullish for NVDA but compresses their GPU-only moat. Physical AI / Edge Sleepers $ARM (again) + $QCOM for Physical AI Edge and physical AI systems are dominated by control logic, safety monitoring, and system coordination — all CPU-led roles. As AI moves from data centers into vehicles, robots, and machines operating under strict power and safety constraints, CPUs play the leading role.  Qualcomm’s Snapdragon platform is the dominant edge AI compute stack for automotive and mobile inference. As physical AI scales — humanoid robots, autonomous vehicles, smart infrastructure — $QCOM’s edge CPU/NPU stack becomes mission-critical. $AMBA (Ambarella) — The Dark Horse Ambarella posted a revenue record of $390.7M in FY2026, up 37% YoY, with ~80% of revenue attributed to edge AI applications. They’ve shipped 45 million edge AI SoCs.  Small cap, high-growth, pure-play edge AI inference silicon. Under the radar for most investors.
Play to watch in Physical AI 🤖 Robotics & Automation Humanoids, service robots, warehouse bots, field robotics Core Platforms & Robotics Builders $TSLA – Optimus humanoid platform $XPEV – Humanoid robotics + autonomy $HYMTF – Advanced humanoid R&D $RR – Service & field robotics $SERV – Last-mile delivery robots Warehouse & Logistics Automation $SYM – AI-powered warehouse robotics $AMZN – World’s largest robotics deployment $ZBRA – Vision, tracking, automation infrastructure 🚗 Autonomous Vehicles AI that drives, navigates, and makes real-time decisions Autonomy & Driving Intelligence $TSLA – Full-stack autonomy $XPEV – AI-driven autonomous driving $MBLY – Vision-based autonomy platform $QCOM – Edge AI compute for vehicles Perception for Autonomy $INVZ – Automotive LiDAR $LAZR – Long-range LiDAR $OUST – Digital LiDAR $ARBE – 4D imaging radar 🏭 Smart Factories Industrial robots + AI-driven production systems Industrial Robotics & Control $ABB – Industrial robots & automation $TER – Collaborative robots (cobots) $HON – Industrial controls & sensing $ROK – Factory software & automation Manufacturing Intelligence $PATH – Process automation bridging digital → physical $PLTR – AI-driven industrial decision orchestration 🏥 Healthcare Precision, repeatability, and high-margin Physical AI Medical Robotics & Surgical Systems $ISRG – da Vinci surgical robotics leader $PRCT – Next-gen robotic surgery $SYK – Robotic surgical instruments $MDT – Robotic-assisted medical devices 🛰️ Defense & Space Autonomous systems in high-risk, high-complexity environments Autonomous Defense Platforms $AVAV – Unmanned aerial systems $RCAT – Autonomous drones $UMAC – Tactical autonomous vehicles $ONDS – Secure AI communications Field, Extreme & Space-Adjacent Robotics $OII – Subsea robotics & offshore autonomy $FARO – 3D sensing, mapping & inspection $RR – Robotics for extreme environments 🧠 Foundational Layer (Powers All Categories) Brains behind Physical AI $NVDA – AI compute backbone $AVGO – Custom silicon + AI networking $QCOM – Edge AI processing Physical AI isn’t one sector. It’s a stack deployed across five massive industries, each monetizing autonomy in different ways. Most capital is still chasing software AI. Robotics + real-world deployment is the next leg. Not a financial advice, Like and share if you like .
Here are the robotics stocks grouped by segment Robot Automation $ROK – Rockwell Automation $ZBRA – Zebra Technologies $CGNX – Cognex $PATH – UiPath $PEGA – Pegasystems Medical Robotics $MDT – Medtronic $PRCT – PROCEPT BioRobotics $OMCL – Omnicell $SYK – Stryker $ISRG – Intuitive Surgical Industrial Robotics $TSLA – Tesla $HON – Honeywell $TER – Teradyne $LECO – Lincoln Electric Professional Robotics $OII – Oceaneering International $FARO – FARO Technologies Service Robotics $RR – Richtech Robotics Robot Software / AI $NVDA – NVIDIA $PTC – PTC Inc $PDYN – Palladyne AI $QCOM – Qualcomm Logistics Robotics $AMZN – Amazon $SYM – Symbotic $SERV – Servr Robotics $ATS – ATS Corp Defense Robotics $AVAV – AeroVironment $LMT – Lockheed Martin $BA – Boeing $TDY – Teledyne Technologies $TXT – Textron $ESLT – Elbit Systems $KTOS – Kratos Defense $NOC – Northrop Grumman $GD – General Dynamics $RTX – RTX Corp $LHX – L3Harris Technologies
If you’re looking to create generational wealth in 2026 then you must have these 8 stocks in your portfolio… 1. Rocket Lab ~ $RKLB 2. Nebius ~ $NBIS 3. Tesla ~ $TSLA 4. Nokia ~ $NOK 5. ServiceNow ~ $NOW 6. Qualcomm ~ $QCOM 7. CoreWeave ~ $CRWV 8. Ondas ~ $ONDS Don’t miss your chance on these setups before they’re long gone. Save this for later…
The Complete Semiconductor Playbook — AI Supercycle 2026 🤖 EDGE AI $QUIK · $CEVA · $SYNA · $QCOM · $INDI · $VLN · $SMTC → AI leaves the data center. Devices. Cars. Factories. Multi-year secular trend just getting started. 🏗️ AI INFRA $SGH · $SKYT · $AVGO · $NVDA · $ARM · $CRDO · $MRVL → The “Nvidia-only” era is over. The full stack is getting priced in. ⚡ POWER $POWI · $TXN · $MPWR · $VICR · $GANX · $AEHR → AI data centers are power monsters. Unsexy. Essential. Increasingly scarce. 🔬 FUTURE-TECH $LWLG · $AXTI · $POET · $TSEM · $GFS · $IPGP → Silicon photonics foundry capacity = national strategic asset. 🛠️ EQUIPMENT $AMAT · $LRCX · $KLAC · $ASML · $ONTO · $ACMR → Without these, nothing above gets built. Map the full stack. That’s where the alpha is. Not financial advice. DYOR
15. $QCOM - Qualcomm (Edge AI) Not all AI runs in the cloud. Qualcomm is the leader in on-device AI - putting inference directly on phones, PCs, cars, and IoT devices. Q2 revenue $10.6B with record automotive revenues. Snapdragon X2 is powering the next generation of AI PCs with always-on agentic experiences. As AI moves from the data center to the edge, Qualcomm owns that transition.
The full CPU stack: understands each layer, you can find many play Architecture - $ARM Design- $AMD $INTC $QCOM Foundry- $TSM $GFS Memory- $MU Storage- $SIMO Connectivity- $ALAB $TMBS Custom silicon- $AVGO $MRVL Future Architecture (RISC-V via Tenstorrent, $CAN)
TECH EARNINGS TODAY $MSFT — ✅ BEAT ✦ Cloud + AI demand staying strong, Azure delivered ➕ Revenue $82.9B (+18%) | EPS $4.27 vs $4.07 est  ➕ Azure +29% | Commercial RPO surged 99% to $627B  ➖ Capex acceleration commentary spooked $GOOG — ✅ MONSTER BEAT ✦ Google Cloud going parabolic — AI thesis fully intact ➕ Revenue $109.9B (+22%) | Cloud up 63% to $20.03B — crushed estimates  ➕ Operating margin expanded to 36.1% | Shares up ~4% AH  ➖ EPS of $5.11 inflated by $36.9B unrealized equity gains — clean operating picture still strong but headline overstates it  ➖ Capex guide raised again to $180–190B  $AMZN — ✅ BIG BEAT ✦ AWS back in acceleration mode — AI tailwind is real ➕ Revenue $181.5B (+17%) | EPS $2.78 vs $1.64 est — massive beat  ➕ AWS +28% YoY — fastest growth in 15 quarters | Ad revenue also accelerating  ➖ Free cash flow collapsed 95% to $1.2B on $44.2B capex — spending is enormous  $META — ✅ BEAT (w/ asterisk) ✦ Ad engine firing on all cylinders — but user growth and capex raise are the flags ➕ Revenue $56.31B (+33%) — fastest growth since 2021 | Q2 guided $58–61B  ➕ Ad impressions +19% | Avg price per ad +12% | Operating margin held at 41%  ➖ EPS $10.44 boosted by $8.03B one-time tax benefit — clean EPS closer to $7.31  ➖ DAP missed at 3.56B vs 3.62B est | QoQ user drop blamed on Iran internet disruptions  $QCOM — ✅ BEAT ✦ Diversification working — autos + data center offsetting handset weakness ➕ EPS $2.65 vs $2.55 est | Stock up ~4% AH  ➕ First data center silicon shipments to a hyperscaler — margin accretive | Auto run rate guided above $6B exiting FY2026  ➖ Chinese handset customers cutting inventory on memory pricing pressure — headwind expected to last through Q3  $VIAV — ✅ BLOWOUT ✦ Photonics + network test demand exploding — data center spending flowing through ➕ Revenue $406.8M (+42.8% YoY) | NSE segment up 54.4% | Stock up ~13% AH 🚀  ➕ Non-GAAP operating margin expanded 430 bps to 21% | Q4 guided $427–437M  ➖ Cash flow pressure noted by analysts — worth monitoring next quarter → Cloud is the clear winner across the board → AI capex still accelerating — no signs of pullback → FCF compression across hyperscalers is the emerging risk → User growth cracks at $META worth watching → $VIAV quietly one of the best prints of the night
$QCOM https://t.co/LdhEVAKPvN
@kapitonov_ivan So $SIVE doesn't handle capacity scaling, Win Semi does volume ramp. Win is massive. $AVGO, $LITE, $QCOM, Mediatek, $MTSI, $NXPI, all use them. They're in $AAPL, SpaceX supply chains too. So volume scaling for hyperscalers is derisked if you secure allocation and do it through Win.
The full CPU stack: check for details in post Architecture - $ARM Design- $AMD $INTC $QCOM Foundry- $TSM $GFS Memory- $MU Storage- $SIMO Connectivity- $ALAB $TMBS Custom silicon- $AVGO $MRVL Future Architecture (RISC-V via Tenstorrent, $CAN)
Overnight movers in tech are flashing risk-on. Semis are leading the tape with $INTC, $TSM, $QCOM all up 2%+ and $AMD pushing nearly 2% in overnight trading. Momentum is spreading beyond the mega caps: ⚡ $POET +11% — optical/AI infrastructure names heating up 📡 $NOK +2% — telecom + network infrastructure catching bids ☢️ $XE +2% — nuclear power stays hot after a massive +26% IPO debut Friday
The full CPU stack: Architecture - $ARM Design- $AMD $INTC $QCOM Foundry- $TSM $GFS Memory- $MU Storage- $SIMO Connectivity- $ALAB $TMBS Custom silicon- $AVGO $MRVL Future Architecture (RISC-V via Tenstorrent, $CAN)
CPU ecosystem map across every tier: TIER 1 — Pure CPU Giants $INTC — Intel. The turnaround is real. Q1 2026: revenue $13.58B, EPS $0.29 crushed $0.01 consensus. Data Center revenue +22% YoY. Stock surged nearly 25% in a single session. CEO Lip-Bu Tan declared: “The next wave of AI will bring intelligence closer to the end user — from foundational models to inference to agentic.”  Up 80%+ YTD before that gap. $AMD — EPYC CPU order book nearly sold out for 2026. Q4 2025 revenue $10.27B, up 34% YoY, with record Data Center revenue of $5.38B.  MI400 platform coming. 1-year return: +269%. The share-gainer. $ARM — The toll road of CPUs. Used in 99% of the world’s smartphone CPU cores.  In 2026, ARM announced the launch of its own CPU products on top of its existing royalty business.  Up +87% YTD before Intel’s earnings day gap. Capital-light, royalty compounder. TIER 2 — CPU-ADJACENT INFRASTRUCTURE $QCOM — Snapdragon X Elite attacking PC CPU market with ARM-based Oryon cores. Edge AI CPU momentum building across enterprise. Automotive + IoT CPU exposure via Snapdragon Cockpit Elite. $MRVL — Custom XPU + CPU silicon. 18+ socket wins. $75B design pipeline. Data center CPU-adjacent workloads = direct tailwind. $AVGO — Custom ASICs + CPU workload accelerators for hyperscalers. AI business grew 106% YoY to $8.4B last quarter. Projects $100B+ business by 2027.  The ASIC answer to x86. $TSM — Makes every CPU on the planet. TSMC fabs AMD EPYC, Apple silicon, Qualcomm Snapdragon. ~70% foundry market share. Trading 14% below Morningstar fair value of $428.  You can’t build a CPU without TSMC. TIER 3 — CPU ENABLERS & PICKS/SHOVELS $MU — Every CPU needs memory. Micron can only fulfill half-to-two-thirds of current medium-term demand. Revenue was $13.6B two quarters ago, $23.9B last quarter, guiding $33.5B next quarter.  Memory is the bottleneck. $SIMO — SSD controllers feeding CPU storage layers in AI data centers. 46% YoY revenue growth. PCIe Gen5 controllers showcased at NVIDIA GTC 2026. The quiet CPU enabler. $ALAB — PCIe + CXL connectivity silicon — the bus that CPUs talk to everything else on. 75%+ gross margins. Zero debt. Every AI CPU cluster needs Astera Labs. $RMBS — Rambus. Memory interface IP. LPDDR5X SOCAMM2 server memory chipset for AI CPUs. ~80% gross margins. Capital-light IP model — gets paid every time a CPU ships with their interface. $GFS — GlobalFoundries. Specialty foundry for RF, automotive, aerospace, and IoT CPUs. The mature-node CPU manufacturer for defense + industrial. TIER 4 — RISC-V REVOLUTION (THE FUTURE CPU WAR) Tenstorrent (private — Jim Keller’s company) — First-gen RISC-V CPU “Ascalon” delivers 10-20 SPECint2006/GHz, competing directly with ARM’s Neoverse V2.  IP licensees already include LG and Hyundai.  Backed by Hyundai, Kia, Samsung. Watch for IPO. $CAN — Canaan Creative. Launched the world’s first commercial edge AI chip based on RISC-V.  Public, listed, speculative. RISC-V + AI edge play in one ticker. SiFive (private) — The ARM of RISC-V. Intel tried to acquire for $2B. CPU IP licensing model. IPO candidate to watch. TIER 5 — HYPERSCALER CUSTOM CPUs (Own The CPU, Own The Cloud) $AMZN — Graviton ARM-based CPUs + Trainium AI chips. Trainium 2 and 3 at max capacity. Nearly all Gen 4 capacity already pre-sold 18 months out.  AWS custom CPU = lowest cloud compute cost. $GOOGL — TPU + custom ARM CPU for Google Cloud. Fastest-growing cloud CPU fleet. $MSFT — Azure custom ARM silicon + Cobalt CPU. AI inference at edge + cloud. Azure fastest-growing hyperscaler by AI workload. The GPU era is maturing. The CPU supercycle is just loading up. Every layer of this stack is a potential winner. Not financial advice.
The AI trade is evolving — and CPUs may be the next breakout. For the last two years, everyone chased GPUs. That made sense — training models needed massive parallel compute. But the next phase of AI looks different: - Agentic AI needs orchestration, memory handling, workflow execution, and sequential reasoning — CPU-heavy workloads. - Inference at scale isn’t just about GPUs. CPUs manage the stack, coordinate workloads, and keep AI systems moving. - Data center CPU demand is tightening, and supply constraints are starting to show. Names to watch: $AMD — EPYC demand remains strong, with enterprise and cloud adoption accelerating. Earnings could be a major catalyst. $INTC — Turnaround momentum is building. Better-than-expected guidance has put Intel back in the conversation. $ARM — The architecture behind modern computing. More AI devices = more royalty leverage. $MRVL — Custom silicon and infrastructure exposure make it a strong secondary AI beneficiary. $QCOM — Quietly building CPU momentum through Snapdragon and edge AI. Big picture: AI is shifting from training → inference → autonomous agents. Phase 1 rewarded GPU leaders. Phase 2 could reward CPU infrastructure. The market always rotates before the crowd notices. Keep CPUs on your radar.
Big earnings week ahead. Names on deck: $AMKR $CDNS $HOOD $SPOT $GLW $BE $ENPH $AMZN $MSFT $META $GOOGL $QCOM $SOFI $LMND $KLAC $VKTX $VIAV $AAPL $RDDT $RBLX $ZETA $RIVN $SNDK $WDC $ROKU $FSLR $TEAM $AXTI Plenty of market-moving catalysts across AI, tech, fintech, solar, biotech, and consumer. Expect volatility, sharp reactions, and opportunities. Stay selective. Trade the setup, not the hype.
$QCOM +11% today, earnings next week
$QCOM — Qualcomm The most overlooked mega-cap in semis. Trading at a P/E of just 27x vs. the semiconductor industry average of 48x , and DCF models suggest it’s undervalued by ~35% relative to fair value . The Apple dependency narrative is overhyped — automotive revenue hit $1.1B in Q1 FY26 with a >35% CAGR, backed by long-term deals with Volkswagen and Toyota . AI PCs, edge compute, and IoT are the next legs. Deeply discounted, massively diversified.
Physical AI play Silicon / Compute (The Brain) $NVDA — Owns the full AI stack $ARM — Royalties on every advanced chip $AMBA — Edge vision processing $QCOM — Low-power AI decision chips $NXPI — Control + sensor fusion backbone Sensing / Memory (Real-Time Awareness) $ADI — Converts physical signals into data $MU — High-speed memory for instant decisions $OUST — Affordable LiDAR enabling scale Materials (The Constraint) $MP — Rare earth monopoly = motor supply control Simulation (Build Before Reality) $CDNS — Every robot is simulated before deployment Proven Monetization $ISRG — Physical AI already generating recurring revenue Deployment Layer (Real-World Execution) $ONDS — Drone + defense infrastructure $SERV — Autonomous delivery at scale Software / Interface (Control Layer) $PATH — Orchestrating humans + AI + robots $SOUN — Voice + vision interface for machines
$ISRG — The Blueprint For How Physical AI Gets Monetized Surgical robotics is Physical AI that already prints recurring revenue. With an installed base exceeding 10,763 systems globally, da Vinci 5 continues gaining momentum with AI-powered force feedback and in-console video replay for real-time surgical decision-making. Every humanoid robotics company is trying to build what ISRG already has. $ONDS — Drones Are Physical AI. And Ondas Is Building the Sovereign Security Grid. Drones are the first large-scale deployment of Physical AI — whoever controls drone swarm technology controls the next generation of warfare and commercial autonomy. Management raised 2026 revenue guidance to $375M — an 840% YoY growth trajectory — driven by Roboteam ground robotics and drone-in-a-box deployments across UAE and Saudi Arabia. Most speculative on this list. Highest upside if execution holds. $PATH — The Orchestration Layer Between Human Workers and Robot Workers Maestro coordinates AI agents, software robots, and human workers across complex enterprise workflows — the central nervous system for autonomous business operations. 90% of U.S. IT executives see agentic potential, 77% plan investments in 2026, but only 37% are live. PATH is where PLTR was in mid-2023. The re-rating hasn’t happened yet. $SOUN — Every Physical AI Machine Needs a Voice. SoundHound Wants to Own That Layer. Robots need to take commands. AVs need to understand context. Machines need ears. At CES 2026, SoundHound unveiled Vision AI for vehicles — uniting visual with voice AI so an in-vehicle assistant can listen, see, and interpret the world simultaneously. Named a leader in the Aragon Research Globe for Agent Platforms 2026. Speculative — but 400+ patents and 217% revenue growth says the moat is real. $SERV — Jensen Huang Called Them Out By Name. The Robots Are Already Delivering. Not a concept. Not a demo. Serve has deployed over 2,000 robots across the U.S. — the nation’s largest sidewalk delivery fleet — completing thousands of deliveries weekly for Shake Shack, Little Caesars, Uber Eats, and DoorDash. The 2026 acquisition of Diligent Robotics expanded Serve into hospitals — Moxi operates in 25+ U.S. hospitals generating $200K–$400K annual revenue per deployment. Nvidia spotlighted. T-Mobile partnered. Real deployments, real data, real moat forming. Stack Map: → Silicon/Compute: $NVDA $ARM $AMBA $QCOM $NXPI → Sensing/Memory: $ADI $MU $OUST → Materials: $MP → Simulation: $CDNS → End Market: $ISRG → Deployment: $ONDS $SERV → Software/Interface: $PATH $SOUN Not financial advice. DYOR.
Physical AI Playbook-  Wave 1 was digital AI — data centers, GPUs, LLMs. Wave 2 is Physical AI — robots, drones, AVs. $NVDA — The God of Physical AI Every robot OS runs on Nvidia. Jetson Thor delivers 7.5x the performance of its predecessor — already adopted by Amazon Robotics, Boston Dynamics, Figure, and Caterpillar.  Simulation, foundation models, edge compute — Nvidia owns the entire stack. You don’t beat the platform. $ARM — The Invisible Tax On Every Robot Ever Built You’ll never see Arm’s logo on a robot. You’ll pay them every time one ships. Arm’s cores sit inside virtually every chip in edge AI — Nvidia’s Jetson, Qualcomm’s Dragonwing, NXP’s S32, Ambarella’s CVflow. As chips get smarter, Arm captures a larger royalty per unit.  Pure leverage play on the entire Physical AI buildout. $AMBA — Robots Need Eyes. Ambarella Makes Them. When a robot drops a glass, it can’t wait for a signal to go to the cloud and back. Ambarella makes low-power AI chips that process vision on the edge instantly.  Real-time edge vision is a hard engineering problem — Ambarella has the lowest power, highest accuracy solution. No vision, no robot. $QCOM — The Phone Chip Company That’s Actually a Robot Chip Company The market still prices Qualcomm as a smartphone play. Qualcomm’s Dragonwing IQ10 SoC enables low-power decision-making for drones, robots, and AVs beyond the cloud.  When Physical AI re-rating hits this ticker, the gap closes fast. $NXPI — The Unsexy Chip That Every Humanoid Robot Will Need Nobody talks about NXP. They should. In March 2026, NXP announced foundational robotics solutions developed with Nvidia — combining Nvidia’s Holoscan Sensor Bridge with NXP SoCs to enable sensor fusion, machine vision, and precision motor control for humanoid form factors.  NXP’s processors are purpose-built for the zonal architecture shift — from hundreds of isolated control units to a few centralized superchips. These hit volume production in 2026.  Once designed in, stays for a decade. $ADI — The Nervous System No One Is Investing In Every robot needs to feel the world before it can act on it. Analog Devices converts real-world pressure, motion, and temperature signals into data robots can use. ADI stands out for resilient profitability, dividend safety, and growth exposure to robotics.  The boring bottleneck with a blue-chip balance sheet. $MU — Speed Is Life When Your Robot Is Walking A robot walking and making a decision can’t afford a 1–2 second delay — a one-second lag means it drops something, crashes, or hurts someone.  Fast low-power memory at the edge closes that gap. LPDDR5X and HBM are Micron’s answer. Robotics demand here is structural, not cyclical. $MP — No Rare Earths, No Robot Motors. Full Stop. You can’t build a million robots without the magnetic materials that make their motors spin — and the rare earth supply chain is severely constrained. If the Pentagon wants U.S.-made robots, they need MP’s California mine.  The geopolitical moat is the thesis. $OUST — LiDAR Fell 99% in Cost. The Mass Deployment Era Just Started. Ouster is benefiting from a 99%+ cost decline in LiDAR since 2019, helping expand AV and robotics beyond R&D into real-world deployment.  Cheap LiDAR is the unlock — robots finally have affordable spatial awareness at scale. $CDNS — You Can’t Ship a Robot You Haven’t Simulated First Cadence’s $3.18B acquisition of Hexagon’s Design & Engineering business brings industry-standard multibody dynamics simulation tools essential for Physical AI and robotics development.  Every robot company is a Cadence customer before it ships a single unit. Invisible infrastructure, zero competition.
It’s funny a shower thought… Probably put $SIVE on the radar for $QCOM, $MRVL, $AVGO, AlChip, Mediatek, $AMZN, $META, $MSFT venture arms now? Since everyone publicly knows now Broadcom can just go and buy Marvell’s photonics chokepoint vulnerability (Amazon/Microsoft ASIC programs) for a rounding error of $350m… Or Qualcomm can do the same buying $SIVE then vertically integrate laser IP after Alphawave aquisition. Or maybe… hyperscalers figure out a way $SIVE remains independent by owning enough shares?
@kishore_sm_7 Yeah I somehow keep getting $QCOM wrong lol, my bad. I’ve done this like 10 times already haha
THE ROBOTICS STACK EXPLAINED: 1. $NVDA & $QCOM provide the vision processors, & compute silicon to allow robots to process data, & make real time decisions. 2. $GOOGL, $MSFT & $META supply the foundation models to give robots reasoning, perception, & interaction abilities. 3. $PLTR, $ORCL & $MSFT convert massive robot fleet data into actionable intelligence while $PANW & $CYBR secure the systems. 4. $ARM, $SNPS & $CNDS design the chips powering robot brains. 5. $MBLY & $TDY provide the vision systems, cameras, & perception sensors to allow robots to understand the world. 6. $MP supplies rare earth magnets used in electric motors to move robotic systems. 7. $ADI, $ON & $STM provide the analog semiconductors that connect digital AI systems to motors, sensors, & power electronics. 8. $ST, $RRX & $TKR manufacture the bearings, motors, & mechanical components for robots. 9. $HON & $ROK deliver the industrial automation platforms that integrate robotics into factories. 10. $TSLA, $AAPL, $BABA & $AMZN are building competing robotic ecosystems across manufacturing, logistic, and mobility applications. It’s clear the expansion within the robotics layer is wide, & many names are responsible for this sector boom…
I have written a full article on the AI chip supply chain. The supply chain is structured into 4 different phases with 13 layers: 1. Raw Materials: $SHECY, $SUOPY, GlobalWafers, $WAF.DE, $SHWDF, $AXTI, $IQE 2. Manufacturing Equipment: $ASML, $ASM.AS, $AMAT, $LRCX, $KLAC 3. EDA & Core Intellectual Property: $SNPS, $CDNS, $ARM, $RMBS 4. Chip Design: $NVDA, $AMD, $INTC, $QCOM 5. Foundries: $TSM, Samsung Semiconductor, $SMIC 6. Memory and HBM: SK Hynix, Samsung Electronics, $MU 7. Packaging and OSAT: ASE Technology, $AMKR, JCET Group 8. Server and Rack Integration: $SMCI, $DELL, $HPE, Foxconn 9. Networking Silicon: $AVGO, $MRVL, $CSCO, $ANET 10. Photonics and Optical Components: Ayar Labs, $ALAB, $CRDO, $COHR, $LITE 11. Power, Thermal management and Grid: $VRT, $MOD, $NVT, $SU.PA, $IREN, $CIFR 12. Hyperscalers: $AMZN, $GOOGL, $MSFT, $META 13. AI Storage, platforms and Data: VAST data, Weka, NetAPP, $PLTR, Blue Yonder, $KXSCF The article covers it all.
$QCOM management maintains its prior outlook that its modem share in $AAPL iPhone 18 will be ~20%, declining to 0% in iPhone 19. adios 😂
$TSM's N2P and A16 processes are both on track for mass production in the 2H26, with A16 slated to begin trial production as early as March 2026 per supply chain source. According to industry sources, $AAPL will adopt WMCM advanced packaging technology for its A20 chip, which will power the iPhone 18, with small-scale production starting in Q2 2026. $QCOM and MediaTek are close behind, adopting the N2P process for their next-generation mobile platforms. As the cost of developing advanced nodes continues to rise—and with memory prices climbing as well—flagship chip prices are expected to increase, pushing up overall chip ASPs. MediaTek noted that it will adjust pricing and strategically allocate capacity based on market conditions to maintain profitability and market stability. Analysts estimate that TSMC’s 2nm capacity will become a scarce resource: monthly output is projected to reach 15K–20K wafers by the end of this year and 45K–55K wafers by the end of next year, primarily serving $AAPL, $QCOM, MediaTek, and leading AI server chipmakers. With 2nm yields improving steadily, TSMC’s roadmap shows that N2P and A16 are both on track for mass production in the 2H26. However, some supply-chain sources indicate that N2P production has been moved ahead of schedule to align with Qualcomm and MediaTek’s flagship chip launches. MediaTek also confirmed that its first N2P-based chipset will debut by the end of 2026, targeting AI smartphones and flagship-tier devices. Industry observers believe that N2P volume production marks the maturity of TSMC’s 2nm family, laying the groundwork for the successful rollout of the A16 process thereafter.
@evrgn11112231 yeah, esepcially 2600. 2500 wasn't that good against $QCOM
China’s leading market regulatory agency SAMR has launched an antitrust investigation into $QCOM over its acquisition of Autotalks, citing failure to file the transaction under China’s Anti-Monopoly Law. https://t.co/JLsLScgvL5
Samsung Foundry reportedly cuts 2nm wafer prices by 30% to counter TSMC's 50% price hike—Digitimes According to reports first published by Korean outlets Business Post and g-enews, TSMC has set its 2nm wafer price at roughly US$30,000, a massive jump from the US$20,000 cost of its current 3nm technology. TSMC's confidence is backed by overwhelming demand. Speaking at the Goldman Sachs' Communacopia + Technology Conference earlier in 2025, KLA executive Ahmad Khan confirmed that about 15 major clients are already designing products on TSMC's 2nm process, with most focused on high-performance computing (HPC). With manufacturing yields reportedly hitting a solid 60% benchmark, TSMC feels little need to offer early-run discounts. Tech behemoths Apple and Nvidia have reportedly secured most of the initial supply for their next-generation iPhones and AI processors, leaving other players scrambling. Samsung has not disclosed its 2nm pricing but is reportedly offering wafers for about US$20,000, or one-third less than TSMC. The move has already won Tesla's AI6 chip orders, according to Shinyoung Securities, which estimated Samsung's discount at around 33%. The Korean giant has a track record of winning large contracts at competitive prices. In 2020, it secured production of Nvidia's RTX 3000 GPUs with an 8nm process, and in 2021 beat out TSMC to make Qualcomm's 4nm Snapdragon 8 Gen 1 application processors. While the Tesla contract may be less profitable for Samsung, analysts said the order provides valuable experience, bolsters yields, and ensures capacity utilization. The company is also positioning itself as a viable "second choice" for chipmakers unable to secure sufficient TSMC supply. Industry observers said Qualcomm is likely to follow Tesla in adopting Samsung's 2nm process, while other HPC and AI chipmakers racing to challenge Nvidia could also become clients. Shinyoung Securities said positive news on Samsung's new foundry customers could emerge as early as the fourth quarter of 2025. $TSM $QCOM $TSLA $NVDA $AMD
ICYMI $QCOM Snapdragon Summit. Keynote by Amon below
