$CDNS — FinTwit mentions on Surfaced

$CDNS — FinTwit mentions on Surfaced

Recent mentions

46 mentions

@ftr_investorsJul 17, 2026 · 2:28 PM

$SNPS and $CDNS are selling off after Kimi K3 designed a chip using AI 📉 It still relied on open-source EDA tools and used a 45nm academic library, many generations behind today's production-grade 3nm/2nm chips. I think today's sell-off is an overreaction 😉 https://t.co/eb9ipZ7VuN

@itsmichaelluuJun 6, 2026 · 2:30 PM

President Trump buying AI companies again. Last time this happened, $INTC $20 → $130 up 650% $DELL $235 → $470 up 200% $MU $320 → $1100 up 350% $IBM $220 → $330 up 150% This time he is buying (from his portfolio) $NOW #1 in his portfolio $ORCL $ONDS $PUSA (his son owns this one) $CDNS $BA $AVGO $MSFT It’s obvious everyone will be millionaires by 2030. https://t.co/PJD9kfG4nT

@analysisopJun 1, 2026 · 3:33 PM

Jensen is even giving you those names; don't put all the SaaS in the same basket 😉 $CDNS $CRWD $PLTR $NOW Said that, I'm not interested in Software as long as the hardware/data center situation continues scaling up (remember: it's still early). Memory, Photonics, Neoclouds...

@itsmichaelluuJun 1, 2026 · 11:12 AM

CEO $NVDA Jensen Huang says the market got it wrong on software stocks. This is CHEATSHEET for what Jensen wants you to buy right now: 1. $NOW — ServiceNow "We're working with Cadence and Crowdstrike and Palantir, SAP and ServiceNow." → Named enterprise AI toolkit partner 2. $MU — Micron "HBM4 memory from Micron, SK Hynix and Samsung." → Only US-listed HBM4 supplier for Vera Rubin 3. $TSM — TSMC "It starts with TSMC. The seven new chips that make up Vera Rubin take shape through hundreds of processing steps. 3 nanometer process." → Sole manufacturer of all Vera Rubin chips 4. $DELL — Dell "Congratulations to Dell and Coreweave as well for standing up their Vera Rubin MVL72 engineering rack." → Confirmed Vera Rubin deployment 5. $CRWV — Coreweave "Coreweave is worth 50, 60, 70 billion dollars and growing incredibly fast." → Flagship AI cloud partner, explicit valuation callout 6. $MSFT — Microsoft "Congratulations to Microsoft for their operational Vera Rubin MVL72 engineering rack." "Microsoft and Nvidia over the last three years reinventing the PC." → Deepest co-development partner across cloud + PC 7. $CDNS — Cadence "We're working with Cadence and Crowdstrike and Palantir, SAP and ServiceNow." → Only company given a full dedicated demo segment 8. $CRWD — CrowdStrike "We're working with Cadence and Crowdstrike and Palantir, SAP and ServiceNow." → Named enterprise AI toolkit partner 9. $PLTR — Palantir "We're working with Cadence and Crowdstrike and Palantir, SAP and ServiceNow." → Named enterprise AI toolkit partner 10. $SAP — SAP "We're working with Cadence and Crowdstrike and Palantir, SAP and ServiceNow." → Named enterprise AI toolkit partner 11. $ADBE — Adobe "Adobe have re-engineered the core of Photoshop and Premiere and they're going to release it for RTX Spark. It is twice as fast." → Full product re-architecture for Nvidia's new PC platform 12. $SHOP — Shopify "Cursor, the software coding company, World Labs, Revolute, the leading financial services AI company, and Shopify." → Named as Coreweave AI cloud customer 13. $GOOG — Google "This is Nscale, and their customers are British Telecom, Google. Google is using one of our AI clouds." → Google confirmed paying customer of Nvidia-powered AI cloud 14. $ICE — NYSE "Lynn Martin, the president of New York Stock Exchange, has been so gracious to partner with us. Vera CPU, six times faster." → Vera CPU deployed live for NYSE real-time stream processing 15. $IBM / $RHT — Red Hat "Red Hat, Canonical, Microsoft, it's going to be adopted everywhere." → Adopting Nvidia Open Shell enterprise runtime I watched $NVDA GTC in Taipei. I know exactly what to buy FIRST. ♻️ RESHARE this post and write 1 comment, I'll DM you what to buy top 3 first.

@techfund1May 24, 2026 · 1:11 PM

The data center CPU market is getting crowded, with large players looking to gain share: $AMD $NVDA $INTC $ARM $QCOM $AMZN $MSFT $GOOGL The most obvious ways to play the growth and increasing competition in this market: $TSM $SNPS $CDNS $ASML and $MRVL (ASIC partner)

@damnang2May 22, 2026 · 4:54 PM

I prefer companies that rise quietly and gradually, before everyone starts talking about them. $CDNS is one of those names. https://t.co/fnD1k4Pgtd

@stocksavvyshayMay 20, 2026 · 11:19 AM

$GOOGL I/O 2026 made it clear that Gemini is becoming the operating layer across Search, Android, Chrome, Workspace and agent workflows. If Google shows real AI Search monetization and external TPU demand then the reaction could hit the entire AI hardware stack: • ASIC Design: $AVGO • Networking: $ANET, $CIEN • Compute Hosting: $WULF, $CIFR • Foundry & Packaging: $TSM, $AMKR • Chip Design Tools: $ARM, $CDNS, $SNPS • Power & Cooling: $VICR, $VRT, $NVT, $PH • Optics & Fiber: $LITE, $COHR, $FN, $APH, $GLW • Connectivity: $MRVL, $ALAB, $CRDO, $RMBS, $SITM • Memory & Storage: $MU, $WDC, $STX, SK Hynix, Samsung

@itsmichaelluuMay 14, 2026 · 2:41 PM

All the stocks Trump bought are up 100%-200% so far. When he says to "BUY THE DIP" you do it if you want to retire before 40. 1/ NVIDIA $NVDA — AI compute is the oil of the 21st century. He knows. 2/ MICROSOFT $MSFT — Azure + OpenAI partnership. AI cloud dominance isn't slowing down. 3/ BROADCOM $AVGO — Custom AI chips. The picks-and-shovels play nobody talks about. 4/ SERVICENOW $NOW — Enterprise AI automation is printing cash every quarter. 5/ ORACLE $ORCL — Data center buildout + cloud contracts with the US government. Conflict? Maybe. Smart? Absolutely. 6/ AMAZON $AMZN — AWS is still the backbone of global AI infrastructure. 7/ APPLE $AAPL — $3T company. Boring? No. Safe, massive, and AI-integrated hardware is coming. 8/ BOEING $BA — He's been publicly pushing Boeing deals to foreign governments. Then bought the stock. 9/ CADENCE DESIGN $CDNS — Semiconductor EDA software. Every chip that gets designed needs Cadence. 10/ AXON ENTERPRISE $AXON — Defense tech + law enforcement AI. Right in Trump's policy lane. 11/ $VOO — Even the President keeps it simple with broad market exposure. 12/ TRANSDIGM $TDG — Defense aerospace parts monopoly. Wars are good for margins. Remember, Trump sets the policy then buys the stocks that benefit.

@stocksavvyshayMay 14, 2026 · 2:11 PM

President Trump’s latest 278-T filing reportedly disclosed 3,600+ transactions so far in 2026. The filing appears to show $1M+ positions in: • $NVDA • $AAPL • $ORCL • $AVGO • $NOW • $ADBE • $WDAY • $DELL • $BA • $UBER • $COST • $SNPS • $CDNS • $TXN • $PG https://t.co/BTK6i1mggc

@aleabitoredditMay 13, 2026 · 10:53 PM

“Robotics may be the biggest product category of all time” - $CDNS CEO. “The projection is $25 trillion. The whole GDP of the world is $110 trillion. So this is huge if this happens.” Extremely bullish on robotics/humanoids directionally. But maybe it’s time for $TSLA and America to really start prioritizing how we build it outside Chinese supply chains?

@stocksavvyshayMay 11, 2026 · 12:59 PM

THE MOST PROFITABLE AI SEMICONDUCTOR STOCKS Operating margin breakdown: • Best-in-class (50%+) | $NVDA, $TSM • Elite (40–49%) | $MU, $ANET, $KLAC, $AVGO, $SNDK • Strong (30–39%) | $ASML, $LRCX, $WDC, $CRDO • Solid (15–29%) | $CDNS, $AMAT, $ALAB, $ARM, $MRVL • Low margin (Below 15%) | $AMD, $COHR, $LITE, $ON

@investmentguru_May 9, 2026 · 8:14 PM

Watch: $VRT · $CDNS · $AWK · $XYL · $ARIS

@investmentguru_May 9, 2026 · 5:18 PM

COOLING / WATER: The Hidden Bottleneck in AI AI scaling isn’t just a chip problem. It’s a heat problem. The more compute you run, the more heat you generate — and heat kills performance. That makes cooling one of the most critical infrastructure layers in AI. A large data center can consume massive power and huge amounts of water just to stay operational. Why it matters: → More GPUs = more heat → More heat = more cooling demand → Cooling efficiency = higher margins & uptime Watch: $VRT · $CDNS · $AWK · $XYL · $ARIS The AI race isn’t only about faster chips. It’s about keeping them cool.

@stocksavvyshayMay 9, 2026 · 3:15 PM

10 WAYS ROBOTICS IS GETTING BUILT OUT ACROSS SECTORS 1. $NVDA infrastructure layer for robotics stack where humanoid robots from Optimus to Atlas can train in Nvidia’s Isaac Sim virtual environment before ever taking a real step 2. $PLTR & $ORCL turn robot fleet sensor data into operational intelligence while $PANW & $CRWD secure robot nervous system as fleets scale & attack surface grows 3. $GOOGL, $MSFT, $META & $BIDU provide foundation models that give robots ability to reason, see & act 4. $ARM, $SNPS & $CDNS design chips that power robot brains while $TSM manufactures silicon & $INTC contributes both design & fabrication capacity for edge compute 5. $AMZN, $AAPL, $XPEV & $BABA are building competing robotics ecosystems across consumer, logistics & automation applications 6. $HON & $ROK provide industrial automation & control systems that integrate robots into existing factory infrastructure at scale 7. $MP supplies the rare-earth magnets that power motors & actuators throughout the robot supply chain 8. $QCOM Dragonwing chips handle 5G connectivity & on-device AI for robot coordination while $MBLY & $AMBA provide vision & compute silicon enabling real-time perception 9. $ADI, $TXN, $ON, $STM & $OSS sit closer to physical edge of robotics from analog chips that convert sensor signals, manage power & control motors to rugged AI compute systems that process data in real time 10. $TSLA only company attempting humanoid robots at manufacturing scale with first-generation Optimus production lines being installed at Fremont right now designed for 1M robots/year & Gigafactory Texas being built out for 10M robots/year at a $20-30K target price

@thevalueistApr 28, 2026 · 12:49 AM

After listening to all the earnings calls today — $AMKR $CDNS $SANM $RMBS (yes, I actually listened to them all) — I don’t see any scenario where $NVDA isn't a $300 stock by 1/21/28. If you've been connected to me for some time, you know NVDA is my largest delta dollar position and has been since our Chat-GPT moment in November 2022. As always, I’m open to hearing the other side. Invest accordingly.

@investmentguru_Apr 25, 2026 · 9:27 PM

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.

@stocksavvyshayApr 25, 2026 · 3:43 PM

THE SUPER BOWL OF EARNINGS IS NEXT WEEK • Monday | $AMKR, $CDNS • Tuesday | $HOOD, $SPOT, $GLW, $BE, $ENPH • Wednesday | $AMZN, $MSFT, $META, $GOOGL, $QCOM, $SOFI, $LMND, $KLAC, $VKTX, $VIAV • Thursday | $AAPL, $RDDT, $RBLX, $ZETA, $RIVN, $SNDK, $WDC, $ROKU, $FSLR, $TEAM, $AXTI

@aleabitoredditApr 20, 2026 · 6:57 PM

Global Foundries photonics/CPO ecosystem list: 1. $GFS - $30.5B 2. $CDNS - $85.9B 3. $SEIGY - $217.2B 4. $SNPS - $84B 5. $KEYS - $57.3B 6. $ATEYY - $130.4B 7. RoboTechnik (ficonTEC) - $11.4B 8. $GLW - $141.2B 9. $LITE - $63.8B 10. $SIVE - $950m 11. $FN - $24.7B 12. $ASX - $63.3B For publicly traded names. Equal weighted long on the ecosystem from their presentation might not be a bad idea? I still find it funny how everything publicly listed is trading in the tens of billions. Then there's some small Swedish laser company there next to $LITE.

@investmentguru_Apr 19, 2026 · 11:51 AM

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

@investmentguru_Apr 19, 2026 · 11:42 AM

$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.

@investmentguru_Apr 19, 2026 · 11:42 AM

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.

@ftr_investorsApr 15, 2026 · 9:01 PM

$CDNS $NVDA Cadence and Nvdia expand their partnership to bring agentic AI, digital twins, and physics-based simulation into engineering 🤖 The goal: speed up chip design, robotics, and AI factories and cutting workflows by up to 100x 🚀 https://t.co/ngWUAQe5XW

@investmentguru_Apr 5, 2026 · 1:38 PM

Next wave of market leaders- Early innings. Big runway. Conviction required. 1. $COHR The vertically integrated photonics king. Coherent has delivered 9 consecutive double beats on top and bottom line, serving high-growth AI data center markets — and it ranks #1 out of 21 in electronic components by quant grade. As AI optical interconnects become critical infrastructure, COHR is positioned to own that supply chain. 2. $IONQ The quantum computing pure play. Quantum computing is expected to grow at a CAGR of 30%+ through 2035, and IonQ’s recent breakthrough in quantum networking could dramatically expand its long-term addressable market. Trapped-ion architecture = potential moat no one else has. 3. $LSCC The hidden gem inside every AI server rack. Lattice is the only public pure-play semiconductor company selling chips that manage critical data center functions like power, security, and sensor processing — with over 50 chips used per server rack. Its Comms and Compute business is projected to grow 20–40% in 2026. 4. $HIMS Disrupting healthcare delivery from the ground up. The platform connects patients to licensed providers digitally, ships medication to their door, and has built a subscription model with nearly 2.5M subscribers — now expanding GLP-1 treatments internationally. Telehealth + GLP-1 = massive TAM. 5. $SE Southeast Asia’s digital empire. Sea owns Shopee (SEA’s largest e-commerce marketplace), Garena (gaming), and Monee (fintech), with Q3 revenue up 38.3% to $6B — yet the stock has pulled back ~38% from 52-week highs, creating a potential entry point. 6. $ASTS Space-based cellular. Already covered — but this is also an emerging infrastructure leader, not just a speculative bet. The company is on track for 45 satellites in orbit by year-end and has contracted revenue commitments exceeding $1 billion from mobile network operators. 7. $AVGO The nervous system of AI. BofA calls Broadcom the “nervous system” of AI infrastructure, with 74% growth in AI semiconductor revenue and dominant market share — one of the top 6 stocks BofA expects to lead the semiconductor industry past $1 trillion in annual sales. 8. $CDNS Every chip designed today runs through Cadence’s EDA software. BofA specifically highlighted Cadence as a top semiconductor pick for 2026, citing dominant market share typically in the 70–75% range — the hallmark of a true category leader. AI chip complexity = more Cadence revenue, always. 9. $RKLB The commercial space infrastructure company that’s actually profitable at the launch level. While SpaceX is private, SpaceX has quietly filed confidentially for what could be the largest IPO in history at a $1.75 trillion valuation — validating the entire commercial space sector and lifting every player in it. RKLB is the best pure-play public proxy. 10. $PLTR The AI OS for governments and enterprises. Palantir was built specifically to address national security challenges — making it particularly attractive in an era of elevated geopolitical concerns — with analysts projecting 60% revenue growth in FY2026 and 40%+ in FY2027. AIP platform = the enterprise AI layer that wins regardless of which LLM dominates. Not financial advice. DYOR.

@aleabitoredditMar 31, 2026 · 12:35 AM

CPO Value Chain Summary from Mirae Asset: Laser Source: Coherent < $COHR > Lumentum < $LITE > Furukawa Electric (TYO: 5801) Yuanjie Semiconductor (SHA: 688498) Innolight Technology / Zhongji Innolight (SZSE: 300308) PIC Foundry: TSMC < $TSM > GlobalFoundries $GFS Samsung Electronics (KRX: 005930) Tower Semiconductor < $TSEM> EIC, Driver IC: Broadcom < $AVGO > Marvell < $MRVL > NVIDIA < $NVDA > ELS, Optical Engine Innolight / Zhongji Innolight (SZSE: 300308) TFC / Suzhou TFC Optical Communication (SZSE: 300394) O-Net Technologies Eoptolink Technology (SZSE: 300502) FAU (Fiber Array Unit): Senko Advanced Components (Private) Sumitomo Electric (TYO: 5802) TFC (SZSE: 300394) FOCI Fiber Optic Communications (TWO: 3363) FAU, Align Tools: ficonTEC (Private) All Ring Tech (TWO: 6187) ADST (Private) FAU, Engine Assembly: Fabrinet < $FN > Hon Hai / Foxconn (TWSE: 2317) ASE Technology < $ASX > FOCI (TWO: 3363) OSAT, Advanced Packaging: ASE Technology < $ASX > Amkor < $AMKR > Kyocera (TYO: 6971) Powertech / PTI (TWSE: 6239) Shinko Electric (TYO: 6967) Fabrinet < $FN > Connector, Ferrule: Senko Advanced Components (Private) Sumitomo Electric (TYO: 5802) US Conec (Private) T&S Communications (SZSE: 300570) Molex (Private) Browave (TWO: 3163) Fiber: Corning < $GLW > Sumitomo Electric (TYO: 5802) Nittobo / Nitto Boseki (TYO: 3110) E/O Testing: Keysight < $KEYS > Teradyne < $TER > FormFactor < $FORM > Chroma ATE (TWSE: 2360) Multilane (Private) Switch, System: NVIDIA < $NVDA > Broadcom < $AVGO > Marvell < $MRVL > Google < $GOOGL> EDA: Synopsys < $SNPS > Cadence < $CDNS > Ansys < $ANSS > Confused by some of names of the list, they might have conflated a few names like Innolight with laser source like $MTSI, Sumitomo, $SIVE, Luxnet, with the actual end module (unless there's something that's not public material or I missed)? But just for people interested in the landscape, this is a good high-level overview.

@stocksavvyshayMar 28, 2026 · 1:35 PM

THE SEMICONDUCTOR VALUE CHAIN Fabless Chip Designers • $QCOM mobile, automotive & edge AI chips • $NVDA AI accelerators & data center GPUs • $TSLA in-house FSD & Dojo AI training chips • $AVGO custom ASICs & AI networking silicon • $MRVL data center CPUs, ASICs & optical DSPs • $AMD CPUs & GPUs for AI training & inference • $MSFT Maia AI accelerators for Azure & Copilot • $GOOGL custom TPUs for Search, Cloud & Gemini • $AAPL in-house SoCs powering Apple Intelligence • $META custom training & inference accelerators for Llama Integrated Device Manufactures • $MU DRAM + NAND for AI memory infrastructure • $ON power semiconductors for EV & AI edge systems • $SNDK NAND flash for enterprise & consumer storage • $TXN analog & embedded chips for industrial & automotive Foundries • $GFS automotive & IoT foundry leader • $TSM world’s largest advanced-node manufacturer • $INTC Custom Foundry contract manufacturing division Testing & Packaging • $AMKR outsourced packaging & test • $TER automated test equipment leader • $AEHR burn-in & reliability test systems Manufacturing / Assembly Equipment & Fab Services • $LRCX etch & deposition equipment • $KLAC process control & metrology systems • $ASML lithography systems enabling advanced nodes • $AMAT deposition & etch systems for chip fabrication Design Software, R&D Tools & IP • $CDNS software for chip design & verification • $LSCC low-power FPGAs for edge & industrial use • $SNPS electronic design automation (EDA) software • $ARM processor IP licensing + first-ever in-house AGI CPU for agentic AI inference

@stocksavvyshayMar 22, 2026 · 3:30 PM

AI SEMIS KEEPING THE MOST OF EVERY DOLLAR Operating margin breakdown: • Best-in-class (50%+) | $NVDA, $TSM • Elite (40–49%) | $MU, $ANET, $KLAC, $AVGO • Strong (30–39%) | $ASML, $TXN, $LRCX, $CRDO • Solid (10–29%) | $CDNS, $AMAT, $ALAB, $ARM, $MRVL, $SNPS, $AMD • Low margin (Below 10%) | $COHR, $LITE, $ON

@bullofbritainMar 16, 2026 · 9:10 PM

$NVDA GTC - Quick Fire Long positions -> Fabs ($TSM, $INTC) -> HBM4 / Memory ( $MU, SK Hynix, Samsung) Feynman = die stacking with custom HBM. -> Co-Packaged Optics ( $TSEM, $LITE, $COHR, $MRVL) -> Optical Interconnects ( $AAOI, $AVGO, $CRDO) -> Networking ( $AVGO, $ANET, $CRDO) -> EDA / Design ( $CDNS, $SNPS) -> Fab Equipment ( $ASML, $AMAT, $LRCX, $KLAC) N -> Substrates / Materials ( $SOI.PA, $AXTI, $ENTG) -> Tungsten ( $EQR.AX, $ALT) -> Infrastructure ( $VRT, $ETN) -> CPU / Architecture ( $ARM) 16x more GPUs per rack. $1T+ demand. The supply chain isn't ready.

@stocksavvyshayMar 7, 2026 · 1:50 PM

10 WAYS ROBOTICS IS GETTING BUILT OUT ACROSS SECTORS 1. $NVDA is the infrastructure layer for the robotics stack where ever humanoid robot from Tesla Optimus to Boston Dynamics Atlas train in Nvidia’s Isaac Sim virtual environment before ever taking a real step. 2. $TSLA is the only company attempting humanoid robots at manufacturing scale with 1,000+ Optimus units already operating in factories & a long-term ~$25K target price. 3. $GOOGL, $MSFT, $META & $BIDU provide the foundation models that give robots the ability to reason, see & act. 4. $PLTR & $ORCL turn robot fleet sensor data into operational intelligence while $PANW & $CRWD secure the robot “nervous system” as fleets scale & the attack surface grows. 5. $ARM, $SNPS & $CDNS design the chips that power robot brains while $TSM manufactures the silicon & $INTC contributes both design + fabrication capacity for edge compute. 6. $XPEV, $BABA, $AMZN & $AAPL are building competing robotics ecosystems across consumer and logistics applications. 7. $HON & $ROK provide the industrial automation & control systems that integrate robots into existing factory infrastructure at scale. 8. $MP supplies the rare-earth magnets that power motors & actuators throughout the robot supply chain. 9. $ADI, $TXN, $ON & $STM provide the analog semiconductors that bridge the digital brain to the physical world by converting sensor signals, managing power & controlling motors with precision. 10. $QCOM Dragonwing chips handle 5G connectivity & on-device AI for robot coordination while $MBLY & $AMBA provide the vision & compute silicon enabling real-time perception.

@kaizen_investorMar 4, 2026 · 4:47 PM

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.

@jasonl_capitalFeb 26, 2026 · 9:35 PM

Big Tech just committed $650B+ in 2026 capex. Here's how that money flows through every layer of the AI stack: Compute: GPUs and Accelerators $NVDA - Blackwell shipping now, Rubin next $AMD - MI300/MI400 giving hyperscalers a second source Custom Silicon and Chip Design $AVGO - Custom AI chips and networking ASICs $MRVL - Interconnect and custom silicon for AI racks $ARM - CPU architecture powering hyperscaler fleets $CDNS - EDA tools behind hyperscaler chip programs $SNPS - Design software enabling next gen silicon Memory and Storage $MU - HBM and advanced DRAM feeding AI accelerators $SNDK - NAND flash across hyperscaler storage Networking and Connectivity $ANET - Switching infrastructure inside AI clusters $ALAB - Rack scale connectivity silicon $CRDO - High speed SerDes for AI interconnect $COHR - Photonics and lasers for optical networking $GLW - Fiber and optical materials connecting it all Servers and Infrastructure $DELL - AI server systems for enterprise and hyperscale $SMCI - Liquid cooled GPU racks, first to market on new chips $HPE - Enterprise AI servers and private cloud infrastructure Foundry, Equipment, and Packaging $TSM - Manufactures the chips everyone else designs $ASML - EUV lithography, no substitute $AMAT - Wafer fab equipment for leading edge nodes $LRCX - Etch and deposition for chip scaling $KLAC - Process control and yield management $AMKR - Advanced packaging and test $INTC - Domestic foundry bet, execution still unproven GPU Cloud and AI Infrastructure $CRWV - On demand GPU cloud for AI workloads $NBIS - Full stack AI infrastructure and developer tools $IREN - Vertically integrated power and compute $CIFR - Long-term hyperscaler data center leases Power and Energy $VRT - Cooling and power distribution inside data centers $CEG - Nuclear baseload for large clusters $VST - Dispatchable power for grid demand $BE - On site fuel cells, behind the meter $NEE - Renewable capacity for grid expansion $FSLR - Utility scale solar $EOSE - Long duration storage for 24/7 uptime $GEV - Turbines, transformers, grid hardware $OKLO - Next gen nuclear, early stage but Altman-backed $SMR - Small modular reactors, longest dated play here 40+ stocks. One thesis. $650 billion has to go somewhere. Which layer are you most positioned in?

@ftr_investorsFeb 25, 2026 · 11:29 AM

Morgan Stanley’s Top 25 Humanoid Robots 🤖 🧠 Brain (AI & chips) $BIDU $BABA $NVDA $TXN $AMD $ARM $SNPS $CDNS $SSNLF 👀 Eyes (sensors & vision) $SONY $MCHP $AMBA $ON $SSNLF 🦾 Body (power & motion control) $NXPI $STM $TXN $HSAI $RNECY $IFNNY $ROHCY $ALGM $MELE Which of these stocks are on your radar? 🚀

@ftr_investorsFeb 14, 2026 · 8:54 AM

Next week will be a bit quieter, but we still have some great companies reporting their latest earnings 📊 Think $PANW, $CDNS, $FIG, $WMT, and $BESI. Which one are you most excited about? 🤩 https://t.co/iwykrpS6y0

@stocksavvyshayFeb 9, 2026 · 3:52 PM

AI CHIP ECOSYSTEM Upstream • EDA, IP, & Design Tools | $ARM, $CDNS, $SNPS • Semiconductor Equipment | $ASML, $AMAT, $LRCX, $KLAC, $TER Midstream • Foundry & Advanced Packaging | $TSM, $INTC, $GFS, $AMKR • Compute | $NVDA, $AMD, $AVGO, $MRVL • Interconnect | $CRDO, $ALAB, $COHR, $CIEN, $APH, $LITE • Memory & Storage | $MU, $WDC, $SNDK, $STX • Power & Analog | $TXN, $ADI, $STM, $ON, $MCHP, $MPWR Downstream • OEMs & ODMs | $SMCI, $DELL, $HPE

@stocksavvyshayFeb 8, 2026 · 3:28 PM

$GOOGL, $MSFT, $META & $AMZN just confirmed $600B+ in 2026 CapEx. Here’s how that money flows through the AI stack: GPUs, Accelerators • $AMD provides second source AI GPUs with MI300 & MI400 series • $NVDA powers the AI accelerator layer with Blackwell shipping & Rubin in production ASICs, TPUs, Design Services • $MRVL provides interconnect & custom silicon for AI racks • $ARM supplies CPU architecture across hyperscaler server fleets • $CDNS enables hyperscaler AI chip development through EDA tools • $AVGO builds custom AI silicon & networking ASICs for hyperscalers • $SNPS powers hyperscaler silicon roadmaps with chip design software Memory • $MU supplies HBM & advanced DRAM for AI accelerators • $SNDK supplies NAND flash for hyperscaler storage layers • $WDC provides high capacity storage for AI data pipelines Networking • $CRDO supplies high speed SerDes for AI interconnect • $COHR provides lasers & photonics for optical networking • $ALAB delivers connectivity silicon for rack scale AI systems • $ANET powers high speed switching inside hyperscaler AI clusters • $GLW supplies fiber & optical materials for data center connectivity Foundry & Advanced Packaging • $KLAC process control for yield & reliability • $LRCX etch & deposition tools for chip scaling • $TSM advanced logic manufacturing for AI chips • $AMAT wafer fab equipment for advanced nodes • $ASML EUV lithography enabling leading edge nodes • $AMKR advanced packaging & test for AI accelerators • $INTC domestic foundry & advanced logic manufacturing for AI chips AI Utility Layer • $IREN builds down into power + compute • $NBIS builds across the software + developer layer • $CIFR rents out the physical layer through long-term leases • $CRWV provides on demand GPU cloud capacity for AI workloads Energy & Power • $FSLR adds incremental utility scale solar capacity • $CEG delivers nuclear baseload for large data center clusters • $NEE builds large scale renewable capacity for grid expansion • $VRT controls cooling & power systems inside AI data centers • $VST supplies dispatchable power for hyperscaler grid demand • $BE provides on site power that bypasses the grid for AI clusters • $EOSE enables long duration storage for 24/7 data center power • $SMR develops small modular reactors for future nuclear buildouts • $OKLO provides “local nuclear plant” that the AI economy will require • $GEV supplies turbines, transformers & grid hardware for grid rebuild

@techfund1Feb 4, 2026 · 7:42 AM

$CDNS & $SNPS down 8%, yet their biggest customer - $NVDA's Jensen - says yesterday he's investing as much resources in these tools as they need. https://t.co/sCj63TngYL

@stocksavvyshayJan 25, 2026 · 2:12 PM

THE SEMICONDUCTOR VALUE CHAIN The AI Brain • $NVDA data center & AI accelerators • $META custom inference silicon for AI • $MSFT AI acceleration silicon for Azure • $QCOM mobile, edge & automotive SoCs • $AMD CPUs and GPUs for compute and AI • $AAPL in-house SoCs for consumer devices • $TSLA in-house vehicle compute & FSD chips • $GOOGL custom TPUs for cloud AI workloads • $MRVL data center, storage & networking silicon • $AVGO networking, connectivity & custom ASICs The AI Factory • $UMC mature-node & specialty processes • $INTC internal manufacturing & foundry services • $TSM world’s largest advanced-node manufacturer • $GFS specialty, automotive & defense-focused foundry The AI Testing & Packaging • $TER automated test equipment • $AEHR burn-in & reliability testing • $AMKR outsourced assembly and test The AI Blueprint • $SNPS EDA software & silicon IP • $ARM processor IP & architectures • $CDNS chip design & system verification The AI Equipment • $KLAC process control & metrology • $LRCX etch & wafer fabrication tools • $AMAT deposition & materials engineering • $ASML lithography systems enabling advanced nodes The AI Executors • $MU DRAM & NAND memory • $ADI high-performance analog & signal processing • $STM microcontrollers, power & mixed-signal chips • $NXPI automotive & industrial embedded platforms • $TXN analog & embedded chips for industrial & automotive

@stocksavvyshayJan 11, 2026 · 3:36 PM

$MU just announced the largest semiconductor manufacturing facility in U.S. history with a $100B advanced memory megafab in New York. Memory is only one layer, so here’s what AI onshoring looks like across the full stack: AI Chip Design • $NVDA defines the default architecture for AI training & a growing share of inference • $AMD provides the critical second GPU stack that prevents the AI economy from relying on one supplier • $GOOGL designs TPUs to internalize AI workloads and defend margins • $AMZN builds Trainium & Inferentia to control inference costs inside AWS • $INTC designs CPUs &accelerators while pushing to re-establish domestic manufacturing relevance • $MSFT designs custom silicon to optimize Azure’s AI stack end to end AI Chip Co-Designers • $AVGO co-designs custom silicon with hyperscalers tying compute, memory & networking into workload-specific AI systems • $MRVL enables custom accelerators & high-speed interconnects tuned for AI training & inference Edge AI • $AAPL embeds inference directly into consumer devices • $QCOM scales low-power AI across mobile & edge endpoints EDA & IP • $SNPS, $CDNS supplies the design tools every advanced AI chip must pass through before it can exist • $ARM licenses the CPU architectures embedded across data center, edge & mobile AI systems Foundries • $TSM is the factory that manufactures the chips the entire AI stack depends on • $INTC is the strategic second source attempting to reshore advanced chip manufacturing Wafer Fab Equipment • $ASML is the AI kingmaker since every advanced node chip is built using its lithography machines • $LRCX enables deposition & etch processes that physically form modern AI transistors • $KLAC ensures yield & reliability so advanced AI chips can be produced at scale • $TEL provides the process equipment required to manufacture cutting-edge logic & memory Other Semicap & Equipment • $AMAT supplies critical tools across ion implant, materials & packaging steps • $TER enables testing and validation so AI chips can ship at scale Advanced Packaging • $AMKR sits at the packaging layer that turns GPUs & HBM into a single AI compute system

@stocksavvyshayDec 28, 2025 · 4:26 PM

THE INFRASTRUCTURE BEHIND THE $GOOGL AI EMPIRE AI Chips • $AVGO helps Google design custom TPUs so it can lower AI chip costs & avoid $NVDA pricing • $TSM only foundry currently capable of producing Google’s leading-edge TPUs at scale with acceptable yields. • $ARM licenses the CPU architecture Google uses alongside TPUs for AI inference & control • $CDNS sells the software Google uses to design each new generation of AI chips • $SNPS provides chip testing/ IP so Google can ship complex TPUs without failures • $AMKR packages TPUs + memory together so Google can run them at data-center scale AI Networking • $ALAB supports high-speed rack-level connectivity as Google scales TPU pods • $MRVL supplies custom networking chips inside Google’s AI data centers • $CRDO licenses data-transfer technology used inside Google’s AI hardware • $ANET supplies switches that route traffic inside Google’s AI clusters • $CIEN moves data between Google’s data centers over long distances AI Utility • $CIFR supplies energy-backed sites supporting large AI workloads • $WULF operates power-dense infrastructure where large-scale compute can be deployed AI Memory • $MU adds DRAM + HBM supply as Google expands AI inference • $WDC stores the massive datasets Google uses to train AI models AI Optics • $LITE supplies optical components used inside Google’s AI data centers • $COHR provides lasers needed for high-speed optical data transmission AI Power • $VRT provides cooling infrastructure that keeps Google’s AI hardware onlin

@rwang07Oct 28, 2025 · 12:28 PM

4) This part is important as well. Besides its "different" IP business, $CDNS Devgan also said not only they have 4 major foundry customers ( $TSM, Samsung, $INTC, Rapidus) in advanced nodes, but suggest that its IP business is well positioned and "PPA is comparatively better in design IP and a lot of customers want to shift over to Cadence." "So the customer demand, I think, is the third reason as our IP business strengthened that we are seeing strength in the IP business."

@rwang07Oct 28, 2025 · 12:28 PM

5) Taken together, and thinking $SNPS last call, $CDNS painted a quite different picture in IP business against $SNPS, which is facing new challenges (although I still think a 35% dip after call was overblown). Just judge from this earnings call, general audience could favor $CDNS position in IP business over $SNPS as of today. But of course, thing is volatile. https://t.co/OBYBVGUHjw

@rwang07Oct 28, 2025 · 12:28 PM

3) Devgan cited three reasons of success of its IP business. To start, he think $CDNS' IP business is "different" and it's "much more profitable"—which has "software-like profitability." "But a lot of the growth is coming in design IP. And the reason for that is our IP business is focused on AI and HPC at the most advanced nodes. Since we got started later in the IP business, we focused it where the future is going, which is AI, HPC and chiplet-based architecture. So a lot of the -- like SerDes and PCIe and HBM4 IPs."

@rwang07Oct 28, 2025 · 12:28 PM

1) There wasn't much discussion here bout $CDNS's call yesterday. But I think the call itself is very interesting and worth a post. $SNPS. To start, $ SNPS's last earnings call faces challenges in its IP business, particularly associated with two reasons: #1 Its major foundry customer, #2 China and EDA export control, and #3 IP business "reform."

@rwang07Oct 28, 2025 · 12:28 PM

2) Yet, on the other hand, $CDNS management seem quite confident on its IP business, and in someway implying their IP business is in fact strengthened. $CDNS CEO Devgan: "I'm actually quite pleased with the performance of our IP business....how we performed this year and what we see backlog and activity going into next year, overall IP business is performing quite well"

@rwang07Sep 24, 2025 · 7:40 PM

A very overlooked part of $MU's call. This part also reminds me of $CDNS's call on how AI has accelerated productivity overall and specific work on semis. $MU: "Micron delivered a strong quarter, surpassing expectations across key fundamentals, supported by the ongoing “memory supercycle” in DRAM and NAND, alongside continued momentum in its HBM business—positioning it as a key beneficiary of the rapidly expanding AI inference and broader compute demand."

@techfund1Jul 29, 2025 · 7:29 AM

"Plans for Moore's Law to continue until 2042" - $CDNS CEO https://t.co/ROoeGKYPz4

@techfund1Jul 29, 2025 · 7:09 AM

Agentic AI will design semis - from $CDNS: https://t.co/IpJlzq6xlF