Trends in Electronics Technology

AI holds great potential for the semiconductor industry and will kick-start the next round of innovation for faster, cheaper and more energy-efficient computation – that was my message today at SPIE Advanced Lithography + Patterning. I discussed the potential and the challenges that AI holds for our industry.   The potential is clearly huge. AI is rapidly integrated into applications, and high-performance compute is expected to underpin growth towards $1 trillion of semiconductor sales by 2030. The challenges are around the computing needs of AI models and related energy consumption. The compute workload of training a leading AI model has increased 16x every 2 years in recent years – much faster than the increase in computing power delivered by Moore’s law, which is about 2x every 2 years. The energy needed to train a leading model has not grown so steeply but still rose 10x every 2 years. This computing need has been met by building supercomputers and massive data centers. If you extrapolate these trends, training a leading AI model would need the entire world-wide electricity supply in about 10 years. That’s clearly not realistic, so the trend has to break, by training algorithms becoming more efficient and by chips becoming more efficient. In other words, the needs of AI will stimulate immense innovation in chip design and manufacturing – and the potential value of AI to our society will put urgency and funding behind that drive. As a consequence, chip makers are pulling all levers to accelerate semiconductor scaling. This includes lithographic “2D” scaling: shrinking the dimensions of transistors to pack more into a square millimeter. It will also include “3D” integration, with innovations like backside power delivery, transistor designs like gate-all-around, as well as stacking chips in the package, where holistic lithography will play a critical role to deliver performance requirements. ASML will support these trends through a comprehensive, holistic lithography portfolio. Our 0.33 NA/0.55 NA EUV lithography systems allow chip makers to shrink dimensions at the lowest possible cost on their critical layers, while tightly matched and highly productive DUV systems will continue to reduce cost. More than ever, metrology and inspections tools – whose data is fed into lithography control solutions that keep the patterning process operating within tight specs to deliver the highest possible production yields – will be essential to deliver 2D scaling and 3D integration processes. 3D integration requires wafer-to-wafer bonding, and we have demonstrated the capability to map the stresses and distortions that bonding creates and to compensate for them, reducing overlay errors for post-bonding patterning by 10x or more.   It was a pleasure catching up with the industry’s lithography and patterning experts in San Jose. I’m excited to see our collective innovation power having a go at these challenges. Together, we will push technology forward.

Rebuilding U.S. manufacturing has quietly begun, and the scale may surprise you. For decades, the U.S. offshored semiconductor and electronics manufacturing to Asia. Over time, China absorbed a large share of that capability. What we face today isn’t theoretical — it’s an economic and national security risk. Reversing that dependency is extraordinarily difficult. We didn’t just move factories overseas. We lost skills, supplier depth, process knowledge, and an entire manufacturing ecosystem. Rebuilding that capability in the U.S. means recreating decades of industrial expertise at speed. This effort began accelerating in 2022 with the CHIPS and Science Act and has compounded rapidly. Based on announced commitments from 2022–2026, semiconductor and electronics investments now total ~$1.7 trillion. ⸻ Who is rebuilding America’s semiconductor & electronics ecosystem Foundry & leading-edge logic (the fabs) 🔹 TSMC: $165B | 2nm–4nm logic, Arizona six-fab cluster 🔹 Intel: $100B+ | U.S. foundry strategy (Ohio + Arizona) 🔹 Samsung Electronics: $45B | Advanced logic & packaging, Texas Memory & AI compute 🔹 Micron Technology: $200B | DRAM & HBM hubs (Idaho, New York) 🔹 SK Hynix: $14B | Advanced AI-memory packaging, Indiana U.S. electronics & silicon anchor customers 🔹 Apple: $600B | U.S. silicon, AI servers, advanced packaging 🔹 Foxconn: $2B+ | AI-server manufacturing for U.S. cloud providers Foundational chips (automotive, industrial, defense) 🔹 Texas Instruments: $60B | Analog & embedded chips 🔹 GlobalFoundries: $12.5B | Secure, automotive, aerospace semiconductors Advanced packaging & integration 🔹 Amkor Technology, Inc.: $2B+ | U.S. back-end packaging, Arizona 🔹 Absolics: $600M+ | Glass substrates for next-gen AI chips Equipment, lithography & process control 🔹 Applied Materials: $4B+ | Process tools & R&D 🔹 ASML: $1B+ | High-NA EUV support (U.S. expansion) 🔹 Lam Research / KLA: $2B+ | Etch, deposition, yield control Materials, wafers & chemicals 🔹 GlobalWafers: $5B | 300mm wafers, Texas 🔹 Fujifilm / Entegris: $1.5B+ | Photoresists & ultra-pure chemicals 🔹 USA Rare Earth: $1.6B | Mine-to-magnet electronics materials Infrastructure that makes fabs possible 🔹 Linde / Air Liquide: $1B+ | Ultra-pure gases piped directly into fabs Geopolitical capital 🔹 Taiwan: $500B total ($250B in direct industrial investment to build fabs, packaging, materials, and suppliers in the U.S. Plus $250B in government-backed incentives to de-risk, accelerate, and anchor those projects long term) ⸻ What we need: 1. Revamp education to produce the ~88,000 engineers and technicians required to staff these future facilities. 2. Continue advancing automation and robotics to reduce labor intensity while increasing reliability and yield. 3. Build strong supply chains with allies for the components we can’t (or shouldn’t) manufacture domestically. #manufacturing #semiconductors #robotics #electronics

The biggest raise in sleep tech history. Eight Sleep just closed a $100M round. The company is calling its next phase an AI Sleep Agent, a personalized layer between your body and your environment that learns from your nightly data and adapts in real time. But the bigger story? They’re going after FDA clearance. That’s not just sleep optimization anymore, it’s a jump into regulated health tech. And it’s exactly the kind of wellness → healthcare convergence I’ve been talking about. Eight Sleep is just the latest, and one of the clearest, examples of this shift. For them, it unlocks clinical claims, physician adoption, and potentially employer or insurer channels. Why this matters... → 𝗙𝗿𝗼𝗺 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝘁𝗼 𝗶𝗻𝘁𝗲𝗿𝘃𝗲𝗻𝘁𝗶𝗼𝗻 Most sleep tools just report, but Eight Sleep is moving toward active adjustments and health monitoring. They say their system can already track cardiovascular and respiratory patterns with strong validation results. If proven, sleep becomes a measurable lever for metabolism, recovery, and cognition. → 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝘁𝗼 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 FDA approval would legitimize Eight Sleep with doctors and hospitals while creating new reimbursement pathways. Wellness brands rarely cross this line, if they succeed, it sets a template for other recovery tools. → 𝗙𝘂𝗹𝗹-𝘀𝘁𝗮𝗰𝗸 𝘀𝗹𝗲𝗲𝗽 𝗵𝗲𝗮𝗹𝘁𝗵 This isn’t just a mattress cover. It’s hardware + sensors, AI + software, and now a regulated pathway. That end-to-end stack could define how sleep is treated at home, in clinics, and in performance settings. → 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝗲𝘅𝗽𝗮𝗻𝗱𝘀 Plans include retail stores, international expansion (with China in focus), and new price tiers. If they pair clinical credibility with broader access, sleep tech could move from premium gadget to mainstream health utility. What to watch -> regulatory path (which clearances they pursue), clinical outcomes (not just dashboards), pricing and access, and how they handle sensitive biometric data. TLDR: If Eight Sleep can turn sleep into a regulated, personalized intervention, it upgrades the bed from comfort product to health platform, with ripple effects across recovery, cardiometabolic care, and longevity. ♻️ Repost this to share with anyone tracking recovery and longevity. Follow me at Delphine Le Grand for more.

Technology has come a long way—from being a tool of convenience to becoming the driving force behind transformation. Each year, we witness remarkable advancements that reshape industries, redefine possibilities, and address challenges we never thought possible. As we step into 2025, the pace of innovation continues to accelerate, bringing with it opportunities to create a smarter, and much more resilient world.    Here are 5 transformative #TechTrends that take the spotlight in 2025: 🚩 #CustomAI: Customized AI is becoming a game-changer, allowing organizations to create bespoke solutions for their unique needs. By using domain-specific data, businesses can solve niche problems with precision, opening doors for personalized experiences and industry-specific innovations. 🚩 The Rise of Agentic AI: Generative AI is entering a transformative phase of “agentification,” evolving from task-specific tools to specialized, interconnected AI agents. Soon, we will witness the emergence of “superagents,” orchestrating interactions between multiple AI systems to enhance collaboration, efficiency, and reliability.    🚩Future-Ready Supply Chains: Powered by AI, IoT, and blockchain, supply chains are becoming more agile, sustainable, and resilient. Technologies like low-earth orbit satellites are increasing connectivity, enabling real-time tracking and visibility, while regulatory frameworks push for greener, more transparent processes. 🚩#CleanTech: As we accelerate the shift towards renewable energy, AI will play a crucial role in optimizing systems and advancing technologies like Small Modular Reactors (SMRs) and nuclear fusion. This fusion of AI and clean tech promises better energy efficiency and a sustainable future. 🚩 #Cybersecurity: With AI-enhanced cyberattacks on the rise, cybersecurity is more critical than ever. AI-powered defenses, alongside advancements in Post-Quantum Cryptography, will ensure that businesses stay resilient and confident in their digital ecosystems, future-proofing their data security systems. These trends are a testament to how innovation can drive meaningful change, solve critical challenges, and empower industries to reimagine the future. As we stand on the brink of 2025, the question isn’t just about adopting these technologies but how we can harness them to create a smarter, more sustainable, and inclusive world. Surabhi Agarwal, The Economic Times

🚀 What Makes a Great EV Motor? A deep benchmarking study of 48 Motors from 31 EVs uncovers the engineering shifts. 🔍⚙️ 🧠 The Main Objective of this research is to identify key design and manufacturing trends in electric vehicle motors. The goal was to understand how EV motors have evolved in efficiency, structure, materials, and production processes. This was done using macroscopic (system-level) and microscopic (component-level) analysis of 48 motors from 31 electric vehicles. 🔎 Macroscopic View – System Level Trends 🏗️ Integrated Designs Are Winning Modern EVs now use integrated motor + gearbox + power electronics. Nearly 50% of the analyzed motors use this setup. ✅ Fewer parts, more compact, reduced cost, and weight. ⚡ Power Density is the New Benchmark Power Density = Power output (kW) / weight (kg) PMSMs (Permanent Magnet Synchronous Motors) lead in performance. But Induction Motors (IM) and Externally Excited Synchronous Machines (EESM) are catching up. 📉 From 2018 to 2023, all topologies show higher power-per-kg trends. 🔬 Microscopic View – Component-Level Insights 🌀 Stator Design Matters 80%+ motors use press/shrink fit for stator-housing attachment. Welded laminations are common but can cause eddy current losses. Bonded and interlocked stacks are rising in use for better performance. 🔧 Winding Technologies Flat wire tech = High fill factor, better cooling, more efficient. Round wire = Easier to make, but heavier and bigger winding heads. U-hairpin, I-pin, X-pin and Trim-cut pin designs optimize copper usage. 🧪 Why thinner wires and smaller windings? High RPMs (now reaching 20,000+) increase eddy currents. Smaller, segmented conductors reduce these losses. Also improves copper efficiency — power per kg of copper has doubled. 📦 Material Efficiency is Key Average stator weight reduced by 20–30% in five years. Outer stator diameters getting smaller; inner diameters stable (for torque). Copper usage is down, but performance per kg is way up. 🔚 Conclusion Electric motors in EVs are evolving fast and smart. Modern designs focus on compactness, high power density, and efficient manufacturing. PMSM motors still lead — but IM and EESM technologies are improving rapidly. Design is now a balance between electrical performance, thermal control, material cost, and ease of manufacturing. 📉 Copper usage is optimized. 📈 Power output is maximized. 🔁 Manufacturing is more scalable. This study sets a new benchmark for how to design, compare, and manufacture EV motors for the future. 🤔 Your thoughts? With 800V systems and high-speed drives becoming common, which motor type will dominate the next EV decade — PMSM, EESM, or IM? #EVTech #ElectricMotors #SustainableMobility #Motordesign Source: "Advances in electric motors: a review and benchmarking of product design and manufacturing technologies" - David Drexler · Achim Kampker · Henrik C. Born · Michael Nankemann · Sebastian Hartmann · Tobias Kulawik

🚨 Silicon Carbide (SiC) Shockwaves in Global Power Electronics 🚨 Silicon Carbide has become the supermaterial of choice for high-performance power applications: from EV powertrains and industrial drives to renewable energy inverters and grid transmission modules. Its superior thermal conductivity, voltage-handling, and frequency capabilities make it indispensable for tomorrow’s power infrastructure. But right now, the SiC ecosystem is in flux: 🇺🇸 Wolfspeed (Cree spin-off) — the U.S. powerhouse in SiC , has filed for Chapter 11, aiming to overhaul $4.6 billion of debt (~70%) with a pre-packaged restructuring deal involving lenders and Renesas. While their stock spiked (64‑80%), the core question remains: Can they emerge lean and competitive, or will this setback cede ground? 🇯🇵 Renesas Electronics — once ambitiously targeting SiC power chips, has scrapped and disbanded its SiC unit amid fierce pricing pressure from Chinese rivals. Japan’s retreat signals market consolidation and mounting global competition. 🇨🇳 China — meanwhile, is building full-stack SiC capabilities under “Made in China 2025.” Massive investments, joint ventures (e.g., ST Micro & Sanan in Chongqing), and aggressive R&D are propelling China toward self-sufficiency and global leadership in SiC. 🚩 Key Takeaways for Leaders & Investors: 1. Resilience ≠ Immunity: Wolfspeed’s Chapter 11 is a stark reminder that even market pioneers aren’t immune to financial pressures, especially with CHIPS Act uncertainties. 2. Competitive Drift: Renesas’s exit emphasizes how thin margins and supply chain dynamics can cripple latecomers in deep-technology domains. 3. China’s Strategic Surge: Anchored by national policy, China is closing the gap and in some sectors, pulling ahead on SiC fabs, EV integration, and energy systems. 4. Ecosystem Evolution: As Western and Japanese players regroup or retreat, China is building an end-to-end SiC infrastructure, from wafers to EVs to solar farms. 💎 As a Venture Capital and healthcare-tech investor, I’m watching this through a dual lens: • First, the strategic capital flow into advanced materials and power tech. Who has skin in the SiC game? Who’s positioned to partner or disrupt? • Second, the implications for energy-intensive healthcare infrastructure, especially in regions pivoting toward regenerative-wellness systems powered by renewables. ⚛️ Final thought: The SiC domain is entering a pivotal shapeshifting moment. U.S. innovators like Wolfspeed have hit turbulence, traditional standouts like Renesas are recalibrating, and China is using scale + policy to seize advantage. Investors, leaders, and innovators: this is the time to reassess your exposure, form purposeful collaborations, and reimagine power-electronics deployment, from electric ambulances to smart med-tech hubs.

Element 84 just released their 2025 Geospatial Tech Radar, and it provides a clear snapshot of where our industry is actually moving. What I love about work like this is that geospatial isn’t a single discipline anymore. It’s a stack. And these trends might look different depending on whether you’re doing EO, data engineering, or application development. A few themes stood out: - Agentic AI is now infrastructure, not a chat feature. With MCP, agents can plan tasks, call tools, and operate across workflows. For geospatial, this means AI becomes the glue layer not a replacement for engines, but a way to orchestrate spatial tasks end-to-end with humans designing the flow. - EO embeddings are maturing fast. Models like TESSERA and AlphaEarth introduce pixel level embeddings that unlock new ways to search, model, and understand imagery and made a big splash this year. These are in the Adopt bucket, and I think in the coming months we will see real use cases start to come from these. - Cloud-native geospatial is the default now. COG, GeoParquet, PMTiles, STAC: these aren’t "emerging" anymore. They’re the baseline. The real questions are now about indexing, engines, performance, and how we build systems on top of them. Make sure to check out how things are added or removed. This is one view and one specific stack, but an amazing framework for thinking about how to adopt, pilot, and use spatial technology. A radar like this gives all of us a shared map of what's stable and what's in motion. EO teams, data engineers, GIS analysts, and product teams will each see different opportunities but the direction of travel is becoming clearer. Great work by the Element 84 team. These radars are a real service to the community. Check out the full radar here: https://lnkd.in/e8UrA9Be 🌎 I'm Matt and I talk about modern GIS, earth observation, AI, and how geospatial is changing. 📬 Want more like this? Join 11k+ others learning from my newsletter → forrest.nyc

As we reach the atomic frontier of chip design, progress depends less on shrinking transistors and more on rethinking architectures, embracing new materials, and developing computing models inspired by nature. For decades, Moore’s Law guided the evolution of microprocessors with remarkable precision. Every two years, transistors became smaller, faster, and more efficient. Today, as we approach atomic distances of about 0.5 nanometers in silicon, physics begins to dictate its own boundaries. Quantum effects destabilize traditional designs, and the cost of further miniaturization grows exponentially. This shift invites us to change perspective. Instead of forcing the limits of scaling, we can explore distributed approaches such as chiplet architectures, which divide processors into smaller, cooperative units. At the same time, research on advanced materials like graphene and 2D semiconductors opens new paths for energy efficiency and performance. Beyond materials, the inspiration from the human brain drives the rise of neuromorphic chips, capable of learning and adapting with minimal energy. Quantum computing adds another dimension, using superposition and entanglement to solve problems that classical systems cannot handle efficiently. Innovation in microelectronics is entering a new phase where creativity, physics, and computation intersect. The question is no longer how small we can go, but how intelligently we can redesign the future of computing. #Semiconductors #QuantumComputing #ChipDesign

In Deloitte's 16th annual Tech Trends report, AI emerges as the unifying thread across nearly every trend, poised to become an integral part of the foundational fabric of how we operate and innovate moving forward. 🤖✨ Here's a snapshot of the innovations that are set to redefine the way businesses operate: • ⚡ AI as an Essential Utility: Much like electricity, AI is becoming an indispensable part of daily operations, reshaping the way businesses function and innovate. What's next for AI? Leverage tailored AI models, from small language models to agentic AI, to optimize specific business needs efficiently. • 💻 Hardware is eating the world: Invest in advanced chips to power AI workloads and enable smarter IoT devices and robotics across industries. • 🚀 IT, amplified - AI elevates the reach (and remit) of the tech function: Transform IT into a strategic enabler by automating tasks and innovating across infrastructure, talent, and delivery. • 🔒 Solving cryptography in an age of quantum: Prepare now for quantum-driven cybersecurity threats with post-quantum encryption and updated cryptographic practices. • 🛠️ AI changes everything for core modernization: Core systems providers have invested heavily in AI, rebuilding their offerings and capabilities around an AI-fueled or AI-first model. 📖 Explore the full report for a deep dive into these trends: Deloitte Tech Trends 2025 (https://lnkd.in/gWz84WwJ) Let's shape the future together—how is your organization preparing for these tech transformations? Share your thoughts in the comments! 💡👇 #TechTrends2025 #GenerativeAI #DigitalTransformation #Innovation #FutureOfWork #DeloitteInsights