$CDNS

@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.

@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.

@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.

@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.

@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.

@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

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

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

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"

@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."

@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."