"Patience is a Super Power" - "The Money is in the waiting"
Showing posts with label space. Show all posts
Showing posts with label space. Show all posts

Monday, December 15, 2025

Quantum Technology, Where, how and why I am invested in this cutting edge technology of the future!

 If I were coming into quantum new but doing institutional-grade diligence, I’d usually force myself to own a “barbell”: (1) one scaled incumbent with a credible roadmap and ecosystem, plus (2–3) focused pure-plays where upside is most asymmetric.


My top three picks

1) IBM (IBM)

Why it makes the cut: IBM is one of the few players with an end-to-end stack (hardware + software + enterprise distribution) and a roadmap explicitly centered on scaling performance through its System Two architecture and the Heron processor family. IBM+1
Investment logic: as a seasoned investor, IBM is the “quantum exposure with survivability”—you’re not underwriting a single technical bet, and IBM can fund long timelines while commercializing along the way (software, services, hybrid workflows).

Key diligence items to track: roadmap execution (processor performance, error rates, scaling), enterprise adoption, and whether quantum contributes meaningfully to broader IBM growth rather than remaining a perpetual R&D line item. IBM+1


2) IonQ (IONQ)

Why it makes the cut: among the public pure-plays, IonQ is combining (a) trapped-ion positioning with (b) aggressive balance-sheet and ecosystem building. In Q3 2025, IonQ reported $39.9M revenue (222% YoY) and highlighted $1.5B cash as of Sept 30, 2025 and $3.5B pro-forma after an October equity offering—i.e., meaningful financial runway for a long R&D cycle. IonQ+1
They’re also expanding beyond compute into networking / infrastructure via acquisitions (e.g., Lightsynq and Skyloom), which matters if distributed quantum / quantum-secure comms becomes a real value layer. IonQ+1

Investment logic: IonQ is one of the clearest “platform roll-up” attempts in public markets—higher volatility, but potentially the most convex upside if they keep converting technical milestones into commercial contracts and ecosystem control. IonQ Investors+1

On a personal note, I believe IONQ is truly in the sweet spot of Quantum technology, however more volatile at this time. (I am adding at today's levels)

Key diligence items to track: dilution vs. strategic use of capital, conversion of bookings/contracts into repeatable revenue, and whether acquisitions create true integration advantage versus complexity. IonQ+1


3) D-Wave Quantum (QBTS)

Why it makes the cut: D-Wave is differentiated because it has been commercial for years and leans into annealing / optimization use cases (often closer to near-term ROI than fault-tolerant “universal” QC). In Q3 fiscal 2025, D-Wave reported $3.7M revenue (up 100% YoY) and very high non-GAAP gross margin (77.7%), while also showing improved adjusted loss metrics (even as GAAP net loss was distorted by warrant-related, largely non-operating items). dwavequantum.com+1

Investment logic: as a portfolio component, D-Wave can be a “commercial traction bet” in quantum—still high risk, but the story is less purely theoretical than many peers.

Key diligence items to track: whether bookings translate into durable recurring revenue, customer concentration, and how the company sustains growth without constant capital-market dependence. Barron's+1


Why I did not put Rigetti in the top three (even though it’s investable)

Rigetti is investable and has real technical progress, but for a strict “top three” list I usually prefer (a) an incumbent with scale (IBM), plus (b) the two pure-play profiles that are most distinct from each other (IonQ “platform roll-up” + D-Wave “commercial annealing”). Recent analyst coverage often groups IonQ/Rigetti/D-Wave together as the main pure-plays, which is directionally fair, but you asked for three. Barron's


Practical note (how I’d implement as a seasoned investor)

Quantum remains a long-duration, high-volatility theme. Even if these are your “best three,” I would treat them like venture-style public equities: smaller position sizes, staged entries, and explicit technical/commercial milestone checkpoints (not just price targets). Barron's

Below is a concise, investor-grade due-diligence scorecard for the three companies discussed. The intent is not to predict winners, but to clarify where each one wins, where risk resides, and what milestones actually matter for capital allocation.


Quantum Investment Due-Diligence Scorecard (Top 3)

Scoring Legend

  • 5 = Best-in-class

  • 3 = Adequate / developing

  • 1 = Weak / speculative


1) IBM (NYSE: IBM) — Incumbent / De-risked Exposure

DimensionScoreRationale
Core Technology4.5Superconducting qubits with the clearest published scaling roadmap (Heron, Condor, System Two).
Error Mitigation / Scaling Path4.5Leader in error mitigation, modular scaling, and quantum-classical integration.
Software & Ecosystem5.0Qiskit is the industry standard; deep developer and enterprise penetration.
Commercialization4.0Real enterprise pilots, but quantum is not yet a material revenue driver.
Balance Sheet / Runway5.0Effectively unlimited relative to pure-plays.
Dilution Risk5.0None.
Upside Asymmetry3.0Lower multiple expansion; upside is strategic, not explosive.

Role in a portfolio:
Foundation / anchor exposure to quantum with minimal existential risk.


2) IonQ (NYSE: IONQ) — High-Convexity Platform Bet

DimensionScoreRationale
Core Technology4.0Trapped-ion architecture with strong fidelity and coherence advantages.
Error Mitigation / Scaling Path3.5Fewer qubits today, but strong logical-qubit potential long term.
Software & Ecosystem3.5Cloud-first strategy via hyperscalers; expanding platform breadth via acquisitions.
Commercialization3.5Fast revenue growth, government + enterprise traction, still early.
Balance Sheet / Runway4.5One of the strongest cash positions among pure-plays.
Dilution Risk2.5Real and ongoing—must be justified by execution.
Upside Asymmetry5.0One of the highest payoff profiles if roadmap + ecosystem converge.

Role in a portfolio:
Primary upside driver—this is where outsized returns would come from if public quantum winners emerge.


3) D-Wave Quantum (NYSE: QBTS) — Near-Term Commercialization Bet

DimensionScoreRationale
Core Technology3.5Quantum annealing—narrower than gate-based QC but proven for optimization.
Error Mitigation / Scaling Path3.0Not pursuing universal fault-tolerant QC, but scaling annealers effectively.
Software & Ecosystem3.0Focused tooling aimed at optimization users.
Commercialization4.5Real customers, recurring revenue, strong gross margins.
Balance Sheet / Runway3.0Improved but still sensitive to capital markets.
Dilution Risk3.0Moderate; better than many peers, not trivial.
Upside Asymmetry3.5Less “moonshot,” more execution-dependent upside.

Role in a portfolio:
Revenue-led hedge—closest thing to an operating quantum business today.


Summary View (Investor Framing)

CompanyWhat You’re Really Buying
IBMSurvivability, ecosystem dominance, and quantum optionality inside a global enterprise.
IonQThe most credible pure-play asymmetric upside in public markets.
D-WaveEvidence that quantum can already generate revenue, even if not universal QC.

How a Seasoned Investor Would Size This

(Not advice—illustrative framework only)

  • IBM: 40–50% of quantum allocation (risk control)

  • IonQ: 30–40% (convex upside)

  • D-Wave: 15–25% (commercial execution bet)


Milestones That Actually Matter (Ignore the Noise)

  • IBM: Logical qubit demonstrations + enterprise workloads moving from pilot → production

  • IonQ: Sustained revenue growth without disproportionate dilution; successful integration of networking acquisitions

  • D-Wave: Expansion of recurring enterprise contracts and cash-flow trajectory improvement


Editors  Note

The next logical step 

  • Add Rigetti as a fourth comparator, or

  • Convert this into a 1–2 year milestone-triggered investment plan 

  • (what would make you add, trim, or exit each position).

  • Try not to get too confused by all the noise!


Sunday, February 9, 2025

Self Driving Vehicles, IOT, Ai, Space Technology. Hiding behind the curtain of these cutting edge technologies is Swiss multi national, STMicroelectronics (STM)



 
STMicroelectronics (STM) Investment & Business Report

Company Overview

  • Ticker: STM (NYSE, Euronext Paris, Borsa Italiana)

  • Headquarters: Geneva, Switzerland

  • Founded: 1987 (Merger of SGS Microelettronica and Thomson Semiconducteurs)

  • Industry: Semiconductors

  • Market Cap: ~$40 billion (as of recent data)

  • Key Customers: Tesla, Mobileye, Apple, NVIDIA, Qualcomm, Bosch, Continental, SpaceX


Financial Overview

  • Revenue (2023): $13.27 billion (23.2% YoY decline)

  • Gross Margin: 39.3% (down from 47.9% in 2022)

  • Operating Income: $1.68 billion (Operating Margin: 12.6%)

  • Net Income: $1.56 billion (63% YoY decline)

  • Cash Position: $3.16 billion net cash as of December 31, 2023

  • Capital Expenditures (2023): $2.53 billion

  • Free Cash Flow: $288 million

STM has revised its long-term revenue goal from 2027 to 2030, aiming to exceed $20 billion in annual revenue, reflecting industry-wide challenges in semiconductor demand.


Manufacturing Facilities & Expansion Plans

  • Current Plants: Italy, France, Malta, Singapore, China

  • Expansion:

    • New Silicon Carbide (SiC) facility in Italy for EV and self-driving tech

    • 300mm wafer production expansion in France

    • China Partnership: STM is collaborating with Hua Hong to ramp up MCU production for automotive customers, particularly in EVs and autonomous systems (Expected 2025)


Technological Leadership & Business Segments

1. Self-Driving Car Technology & Automotive Leadership

STM is a critical supplier of chips and sensors for autonomous vehicle technology, providing microcontrollers (MCUs), power electronics, AI processors, and sensor fusion technology.


Key Self-Driving Partnerships:

  • Tesla: Supplier of MCUs, power electronics, and SiC chips for Tesla’s self-driving EVs.

  • Mobileye (Intel): STM provides AI-enhanced camera sensors for Mobileye’s ADAS and self-driving systems.

  • NVIDIA: Collaborates on low-power AI processing chips for autonomous vehicles.

  • Geely & Volvo: Supplies ADAS and powertrain chips for Chinese and European autonomous vehicle projects.

  • XPeng & BYD: Provides LiDAR signal processing chips for leading Chinese EV makers.

Silicon Carbide (SiC) Leadership in EVs & Autonomous Cars:

  • STM is a top 3 global supplier of SiC power electronics, used to enhance battery efficiency and range in EVs.

  • SiC chips are essential for self-driving fleets, robotaxis, and AI-driven vehicle computing.

R&D Investments in Self-Driving Tech:

  • AI-powered microcontrollers with real-time neural network processing

  • Next-gen LiDAR and radar signal processing chips

  • Edge AI processors for in-vehicle computing

  • SiC-based power solutions for energy-efficient autonomous platforms

2. Internet of Things (IoT) & Edge Computing

  • Broad portfolio of MCUs, MEMS sensors, and connectivity chips for IoT applications.

  • STM’s chips are integrated into smart home devices, industrial automation, healthcare, and wearables.

3. Space Business & Aerospace Applications

  • STM provides radiation-hardened semiconductors for satellites and spacecraft.

  • Partnerships with SpaceX and European space agencies ensure a growing presence in the space sector.


Competitive Positioning

STM faces competition from Infineon, NVIDIA, and ON Semiconductor, but differentiates itself through: ✅ Leadership in automotive microcontrollers & SiC chipsStrong AI and sensor fusion R&D investmentsExpanding partnerships with Tesla, Mobileye, and top Chinese EV makersDiverse applications in space, IoT, and AI-driven computing


Investment Outlook & Growth Potential

  • Self-Driving Boom: Autonomous vehicle sales expected to surpass $2 trillion by 2040.

  • Silicon Carbide Market Growth: Projected to hit $10 billion+ by 2030—STM is a major player.

  • AI-Enabled Vehicles: STM’s AI-enhanced MCUs and Edge AI processors position it for long-term success.

  • Expansion in China & U.S.: Ongoing investment in next-gen automotive and industrial chips.

Key Risks:Tesla’s in-house chip strategy may reduce reliance on STM in the long term. ⚠ Competition from NVIDIA and Infineon in high-performance ADAS chips. ⚠ Cyclical semiconductor demand could cause revenue fluctuations.


Final Verdict: A Key Player in the Future of Self-Driving & AI



STM is a leading semiconductor supplier for the self-driving and EV revolution, with strong positioning in ADAS, power electronics, and AI-driven automotive chips. Despite short-term revenue challenges, its SiC leadership, Tesla partnership, and investments in AI microcontrollers make it a high-potential long-term investment in the autonomous vehicle market.

ED Note:

For now, we are placing STM on our watch list as it's share price has been slipping recently due to some market turbulence and some financial re-adjustments.  We will look to take a position as these conditions improve in 2025 and beyond. 

Reasons why:  STMicroelectronics (STM) has recently adjusted its financial projections due to ongoing challenges in the semiconductor industry, particularly in the automotive and industrial sectors. The company now aims to achieve annual revenues exceeding $20 billion by 2030, a target previously set for 2027. An intermediate goal has been established, with revenues expected to reach approximately $18 billion and an operating margin between 22% and 24% in the 2027-2028 timeframe.

In the self-driving technology domain, STM continues to innovate, focusing on advanced microcontrollers (MCUs) and silicon carbide (SiC) power devices. The company has expanded its automotive MCU roadmap to support next-generation vehicles, emphasizing reduced complexity, improved efficiency, and enhanced safety and security standards.

Additionally, STM has introduced its fourth generation of SiC MOSFETs, which offer higher efficiency and are critical for electric vehicles (EVs) and autonomous driving applications.

Despite these advancements, STM has faced a downturn in demand from automotive clients, leading to a downward revision of its 2024 revenue forecast to $13.27 billion, marking a 23% decrease from the previous year. This adjustment reflects the broader challenges in the automotive semiconductor market, including high inventory levels and fluctuating demand.

In summary, while STM is actively developing technologies to support the self-driving car industry, it is also navigating significant market challenges that have impacted its financial outlook.

Robots and Automation - From factory bots to Robo Taxis and Humanoids. Who are the leading companies?

Wednesday, January 8, 2025

The Importance of LiDAR in Automation, Robotics, Robo-Taxis, and Aerospace

4D Lidar Technology

Executive Summary

LiDAR (Light Detection and Ranging) technology has emerged as a critical enabler for advancements in automation, robotics, robo-taxis, and aerospace. By providing high-resolution, real-time 3D mapping and environmental sensing capabilities, LiDAR allows systems to perceive, interpret, and navigate their surroundings with unparalleled accuracy. This report explores the significance of LiDAR in these industries and identifies key players driving its adoption.


1. The Role of LiDAR in Automation

1.1 Industrial Automation

  • Significance: LiDAR enhances safety and efficiency in automated factories and warehouses.

  • Applications:

    • Obstacle detection for Automated Guided Vehicles (AGVs).

    • Worker safety systems around robotic arms.

    • Dynamic path planning for warehouse robots.

  • Value Proposition: LiDAR’s ability to create real-time maps ensures seamless navigation in complex industrial environments.

1.2 Smart Cities and Infrastructure

  • Significance: LiDAR supports automation in traffic management, urban planning, and construction.

  • Applications:

    • Smart traffic lights and vehicle-to-infrastructure (V2I) systems.

    • Real-time 3D mapping for city planning and construction.

  • Value Proposition: LiDAR improves efficiency and safety in urban environments through precise data collection and analysis.


2. LiDAR’s Importance in Robotics

2.1 Industrial and Service Robots
Spot from Boston Dynamics uses Lidar in
certain situations for mapping terrain

  • Significance: LiDAR empowers robots to navigate and operate autonomously in dynamic environments.

  • Applications:

    • Autonomous cleaning robots in commercial spaces.

    • Security robots for perimeter surveillance.

    • Inventory management in warehouses.

  • Emerging Trends: LiDAR-driven Simultaneous Localization and Mapping (SLAM) enables robots to create and navigate maps in real time.

2.2 Consumer Robotics
Robo Mower using Lidar Tech

  • Significance: Affordable, miniaturized LiDAR systems make consumer robots more efficient and user-friendly.

  • Applications:

    • Home cleaning robots.

    • Personal assistance robots.

  • Value Proposition: LiDAR enhances obstacle detection and operational efficiency, ensuring widespread adoption in consumer products.


3. LiDAR’s Role in Robo-Taxis

3.1 Autonomous Vehicles

  • Significance: LiDAR is indispensable for achieving full autonomy in vehicles.

  • Applications:

    • High-resolution 3D mapping for vehicle navigation.

    • Object detection and trajectory prediction for pedestrian and vehicle safety.

    • Real-time data integration with other sensors (cameras, radar) for holistic situational awareness.

  • Value Proposition: LiDAR’s precision and reliability in diverse conditions (e.g., low light, adverse weather) make it a cornerstone technology for robo-taxis.

3.2 Safety and Regulation

  • Significance: Regulatory bodies favor LiDAR for its proven reliability in collision avoidance.

  • Value Proposition: Automakers partnering with LiDAR providers (e.g., Aeva with Volkswagen) are driving the adoption of autonomous technologies that prioritize safety.


4. The Critical Role of LiDAR in Aerospace

4.1 Terrain Mapping and Navigation

  • Significance: LiDAR enables precision navigation for aircraft, including Urban Air Mobility (UAM) vehicles like eVTOLs.

  • Applications:

    • Terrain mapping for takeoff and landing safety.

    • Autonomous navigation in crowded airspaces.

  • Value Proposition: Real-time mapping ensures safe operations in challenging environments.

4.2 Space Exploration

  • Significance: LiDAR is a key tool for planetary exploration and landing assistance.

  • Applications:


    • Mapping planetary surfaces.

    • Enabling safe landings for rovers and spacecraft.

  • Value Proposition: High-resolution 3D mapping allows for accurate navigation and data collection in extraterrestrial environments.

4.3 Drone Technology

  • Significance: LiDAR is critical for drones used in defense, surveillance, and logistics.

  • Applications:


    • Obstacle avoidance in dynamic conditions.

    • Precision mapping for agriculture and construction.

    • Real-time navigation in GPS-denied environments.

  • Value Proposition: Lightweight, low-power LiDAR systems enhance the performance and efficiency of drones.


5. Key Players Driving LiDAR Adoption

5.1 Aeva Technologies

  • Strengths:

    • 4D LiDAR technology integrating velocity data for richer environmental insights.

    • Partnerships with automotive leaders like Volkswagen.

  • Importance: Aeva’s advanced 4D-FMCW capabilities make it a leader in dynamic, real-time applications across multiple sectors.

5.2 Hesai Technology

  • Strengths:

    • High-volume production capacity for automotive and industrial LiDAR systems.

    • Dominant presence in the Asian market.

  • Importance: Hesai’s cost-effective solutions and diverse product offerings make it a key player in automotive and robotics applications.

5.3 Luminar Technologies


  • Strengths:

    • Long-range LiDAR tailored for automotive-grade safety systems.

    • Collaborations with automakers like Volvo and Daimler.

  • Importance: Luminar’s focus on highway-speed autonomy ensures its relevance in the robo-taxi market.

5.4 Ouster

  • Strengths:

    • Digital LiDAR for industrial automation, robotics, and smart cities.

    • Cost-efficient systems enabling scalability.

  • Importance: Well-suited for non-automotive markets, including logistics and public infrastructure.

  • Merger: The combination of Ouster and Velodyne expanded Ouster's reach in the LiDAR market by uniting complementary product portfolios, enhancing operational efficiencies, and strengthening its presence across diverse industries, including automotive, robotics, industrial automation, and smart cities.

5.5 Innoviz Technologies

  • Strengths:

    • Solid-state LiDAR for affordable automotive applications.

    • Key contracts with BMW and other OEMs.

  • Importance: Innoviz’s focus on affordability drives adoption in mainstream autonomous vehicles.

5.6 Velodyne (Ouster)

  • Strengths:

    • Diverse product portfolio for automotive, robotics, and industrial automation.

    • Established partnerships with tech leaders like Baidu.

  • Importance: Velodyne’s broad application range ensures it remains a significant player in LiDAR technology.


6. Conclusion: LiDAR’s Transformative Impact

LiDAR’s role in enabling automation, robotics, robo-taxis, and aerospace technologies underscores its transformative impact. By delivering precise, real-time 3D mapping and environmental data, LiDAR accelerates the development of autonomous systems across industries. As costs decline and applications expand, LiDAR’s adoption will continue to grow, shaping the future of these critical technologies.

Key Takeaway

Companies like Aeva Technologies, Hesai, Luminar, Ouster, Innoviz, and Velodyne are at the forefront of LiDAR innovation, driving its adoption across automation, robotics, transportation, and aerospace sectors. Their contributions are paving the way for safer, more efficient, and smarter autonomous systems.

As a clear example, Waymo, (owned by Alphabet (GOOG), who uses it's "in house" lidar tech in it's stack, reports it made more than 4 million fully autonomous Waymo rides served in 2024 (and 5M all-time)

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