ELE Times

Manufacturing today depends on processes that balance speed, precision, and scalability. Among them, injection molding has become indispensable for industries ranging from healthcare to consumer goods. Its ability to deliver identical, high-quality parts in massive volumes makes it one of the most reliable and cost-effective production methods. But what makes this process so vital, and how exactly does it work?

Understanding Injection Molding

Fundamentally, injection molding is about thrusting molten material into a precisely crafted mold, where it solidifies and takes on its final shape. Plastics are the stalwart of the operation, but producers also apply it to metals and testing uses in new industries. The greatest strength of injection molding is consistency and efficiency once a mold has been made, it can be used to churn out hundreds of thousands of duplicate parts with little deviation.

Unlike subtractive methods such as CNC machining, injection molding is less wasteful of material and can be more flexible in terms of design, with the ability to create everything from small medical devices to large automotive panels.

Industries that Depend on Injection Molding

• Food and Beverage

From yogurt cups to condiment containers, the packaging business relies heavily on injection molding for its light, disposable products. Moving beyond packaging, researchers at one of the University are testing whether this process can be used to mass-produce plant-based meat substitutes, demonstrating how versatile the method can be. In contrast to 3D printing, injection molding offers cost savings and is able to maintain taste and texture in food applications.

• Healthcare and Medical Devices

The medical sector applies injection molding in the production of syringes, implants, and wearables. Due to the stringent regulatory conditions, manufacturers tend to include sensors within the mold to check for temperature and pressure, allowing for perfect outcomes. Robotic equipment is also utilized, which removes faulty components automatically to ensure high levels of safety in patient-care products.

• Sporting Goods and Consumer Products

Leisure goods used daily picnic tableware, coolers, and even high-precision golf clubs are produced with this process as well. Metal injection molding enables golf club manufacturers to create products that improve performance and feedback. Molding single-piece coolers thinner but stronger walls speaks to the process’s efficiency and resilience.

The Injection Molding Process

In any industry and whether small, medium, or large, the injection molding process adheres to a systematic approach:

1. Material Selection – Companies select metals or polymers according to strength, flexibility, durability, or resistance characteristics. Polypropylene is suitable for packaging food, while polycarbonate resists UV exposure for use outside.
2. Design of Mold – Designers make precise steel or aluminum molds with orientation, core, cavity, and mold base in mind. CNC machining is usually employed to cut the mold exactly.
3. Clamping – A clamping mechanism provides pressure to keep the mold halves tightly closed, preventing any leak during the process of injection.
4. Injection – Pellets are melted into molten form, blended by a reciprocating screw, and injected into the mold at regulated velocities and pressures.
5. Dwelling – Pressure is held for a temporary period to guarantee the molten material fills all the cavities of the mold.
6. Cooling – The part solidifies within the mold, a phase often constituting the bulk of cycle time.
7. Opening and Removal – After cooling, the mold is opened and ejector pins force the part out. Any remaining flash material is removed and sometimes recycled.
8. Inspection – Finished parts are visually inspected and tested to detect defects, maintaining consistent quality control.

Why Injection Molding Remains Essential

The scalability, accuracy, and versatility to perform in various industries of the process make injection molding a corner stone of contemporary manufacturing. From life-saving medical technologies to common consumer products, the process continues to transform with automation, robotics, and intelligent sensors, which guarantee ever-greater levels of quality and efficiency.

As industries seek faster, more sustainable, and more innovative ways to produce goods, injection molding remains a cornerstone technology that bridges traditional manufacturing with future possibilities.

(This article has been adapted and modified from content on Revolutionized.)

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The world of manufacturing is changing very fast with digital intelligence merging with the conventional industrial processes. Physical AI lies at the heart of this revolution, bringing together sophisticated algorithms and machinery such as robotic arms, autonomous guided vehicles (AGVs), and CNC machinery. For these systems based on AI to function optimally, they depend on real-time information from industrial sensors. Serving as the “eyes and ears” of machines, sensors today do much more than make measurements they allow AI systems to learn, adapt, and optimize processes to enhance productivity, safety, and efficiency.

The two-part series addresses how industrial sensors enable physical AI applications. The first part discusses sensor types and functions in smart factories, while the second part will discuss innovations and trends that will dominate next-generation physical AI-powered industrial systems.

How Industrial Sensors Enable Physical AI

Industrial sensors measure physical parameters like motion, distance, pressure, temperature, or flow into electrical signals that undergo parameterization. These signals find their way into PLCs, CNC machines, and edge AI devices that carry out real-time decision making.

A typical sensor has some or all of these components: sensing element, operational amplifier OpAmp, ADC, processor, interface, and power management. All these or some of them constitute the sensor acting as a bridge between AI algorithms and the physical world, much like the nervous system transmitting information to the brain.

With a modern smart factory, there is an increase in the deployment of AI at the edge, embedding algorithms in sensors, robots, and controllers themselves. This obviates decision making in real-time being made on cloud-based IT systems alone.

Key Industrial Sensor Types

Vision (Image) Sensors: Cameras used to capture product images for machine vision, inspection, and quality control. They recognize orientation, defects, and positioning in real time. Next-generation short-wave infrared (SWIR) and low-power image sensors provide high dynamic range and low-light capabilities in demanding industrial settings.

Position & Torque Sensors: Hall-effect, optical, and inductive sensors are used to detect motor position and torque. Latest inductive PCB-based sensors combine analog front-ends and controllers to make mechanical design easier while providing improved temperature tolerance and contamination resistance.

Ultrasonic Sensors: Detect distance by emitting ultrasonic waves. Suitable for detecting transparent objects, ultrasonic sensors are widely applied in autonomous robots for navigation and obstacle detection and in process automation for flow and level measurement.

Photoelectric Sensors: Capture objects using light-based technologies infrared or laser and come in through-beam, retroreflective, and diffuse-reflective configurations. They are non-contact, flexible, and accommodate long detection ranges.

Proximity Sensors: Sense metallic objects using electromagnetic induction without contact. They are durable in harsh environments and can be used in conjunction with ultrasonic or photoelectric sensors to detect non-metallic objects.

Pressure Sensors: Condition clean-room environments and pneumatic or hydraulic systems. They deliver accurate voltage readings that represent system pressure using strain gauges or force resistors.

Temperature Sensors: Monitor and control temperature in various industries. Thermocouples, RTDs, and semiconductor temperature sensors protect machinery and stabilize processes.

Environmental Sensors: Add gas, chemical, rain, and light sensors to measure environmental conditions and workplace safety. For example, electrochemical sensors can measure chemical currents at low power consumption, providing constant monitoring.

Selecting the Correct Sensors for Intelligent Manufacturing

When designing industrial systems with AI, engineers should keep in mind:

1. Application Response Speed & Accuracy: Response speed and accuracy should be suited to the job, from control of robots to quality inspection in real time.
2. Data Reliability: Sensors need to deliver high-quality data reliably to enable AI learning and analytics.
3. Integration & Interoperability: Sensors need to integrate seamlessly with PLCs, field buses, and other industrial automation.
4. Data Privacy & Cybersecurity: Preserving sensitive operating data is essential, particularly as sensors communicate data through networks.
5. Energy Efficiency: Sensors with low power consumption allow widespread deployment without exceeding power budgets.

Conclusion:

Industrial sensors are critical to enable physical AI in the smart factory spaces. By sensing the physical world accurately and interpreting it, these sensors enable AI systems to make quicker, wiser, and more secure decisions. With advancements in sensor technologies, they will further propel more intelligent, adaptive, and more sustainable industrial activities, leading the way to Industry 5.0.

With its extensive sensor portfolio and application know-how, Onsemi continues to be the leader in intelligent sensing, assisting manufacturers to unlock the full value of physical AI.

(This article has been adapted and modified from content on Onsemi.)

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A breakthrough in wearable technology is redefining what smart glasses can do: generative AI running entirely on the device, without the need for a phone or cloud connection. Powered by the new Snapdragon AR1+ Gen 1 platform, the glasses allow an AI to interact seamlessly in every day scenarios-from shopping or any home tasks.

AI Fitting Inside Glasses

In a live demonstration, a generative AI assistant operated directly on smart glasses using a compact language model (SLM). During a simulated grocery trip, the assistant helped with a recipe, delivering audio guidance and text directly on the lenses all without any external device. This is a strong demonstration of what is going on with smart glasses from mere accessories to full-blown, standalone AI tools.

Snapdragon AR1+ Gen 1

The Snapdragon AR1+ Gen 1 processor, 26% smaller than previous generations, brings enhanced power efficiency, improved image quality, and the ability to run small language models directly on the glasses. These improvements are crucial for thinner, lighter frames that don’t compromise performance or functionality.

Flexible XR Ecosystem

Next-generation smart glasses will be available in various form factors. Some will be standalone, and others will be linked to nearby devices like smartphones, tablets, or portable computing “pucks.” This modular system provides flexible, high-performance experiences across various configurations while keeping AI interactions speedy, private, and responsive.

Improved Vision and Multimodal Inputs

Sophisticated camera features enable glasses to record and perceive the world in rich detail, enabling proactive suggestion and context-sensitive help. Even when not connected to other devices, these glasses can be paired with other wearables like smartwatches or rings, enabling new forms of interaction and input.

Conclusion

This demonstration represents the beginning of a new era in wearable AI, in which intelligent glasses have the capability to provide tailored, real-time support on the move. Powered by the Snapdragon AR1+ platform, Qualcomm is making some of the thinnest, cleverest, and most powerful glasses possible that might change the way we engage with technology in our everyday lives.

(This article has been adapted and modified from content on Qualcomm Technologies.)

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The hardware, software and  Intelligent Factory concept presented by market and technology leader ASMPT drew strong interest from trade visitors at this year’s productronica India.

At the joint booth with long-standing distribution partner Maxim SMT, the spotlight was on the fast, precise, and process-stable DEK TQ solder paste printer platform and the SIPLACE TX high-speed placement solution. The SIPLACE CP20 and SIPLACE CPP placement heads on display also proved particularly well suited to the high-volume production that characterizes the Indian market, offering manufacturers maximum flexibility and productivity in demanding high-volume production.

Integrative concepts for high-volume production

Many visitors took the opportunity to gain a detailed understanding of a complete ASMPT production line in personal technical discussions. Of particular interest was the integrated concept of the intelligent factory, where standardized interfaces across all ASMPT machines continuously collect and process data, making it available where it can be used to enhance quality, prevent errors, and eliminate production bottlenecks.

Comprehensive software portfolio

ASMPT’s extensive software portfolio attracted strong interest from the expert audience. At the core is the WORKS Software Suite, which supports all line-related processes, complemented by the Factory Solutions for holistic optimization across the entire manufacturing environment – including critical areas such as material intralogistics. Live demonstrations featured WORKS Optimization, the intelligent inline expert system for end-to-end process improvement; the Factory Equipment Center, an integrated asset and maintenance management system; the Material Flow Optimizer, ensuring efficient intralogistics and smooth material supply; and SMT Analytics, providing in-depth analysis of the entire SMT production process across all lines.

“We were very pleased with the strong interest shown in our insights and the solutions we showcased for state-of-the-art electronics manufacturing,” summarized Neeraj Bhardwaj, General Manager for India at ASMPT SMT Solutions. “The lively response confirms that we are on the right track in this important growth market.”

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New digital micromirror device with real-time correction enables equipment manufacturers to achieve high-resolution printing at scale, maximizing throughput and yield

What’s new

Texas Instruments is enhancing the next generation of digital lithography with the introduction of the DLP991UUV digital micromirror device (DMD), the company’s highest resolution direct imaging solution to date. With 8.9 million pixels, sub-micron resolution capabilities and a data rate of 110 gigapixels per second, the device eliminates the need for expensive mask technology while delivering the scalability, cost-effectiveness and precision needed for increasingly complex packaging.

Why it matters

Maskless digital lithography machines – which project light for etching circuit designs on materials without a photomask or high-end stencil – are becoming increasingly popular for the manufacturing of advanced packaging. Advanced packaging combines multiple chips and technologies into a single package, enabling high-computing applications, such as data centers and 5G, to have systems that are smaller, faster, and more power-efficient.

With TI DLP technology, system assembly equipment manufacturers can leverage maskless digital lithography to achieve the high-resolution printing at scale necessary for advanced packaging. The new DLP991UUV acts as a programmable photomask, offering precise pixel control with reliable high-speed performance.

“Just as we redefined cinema by enabling the transition from film to digital projection, TI’s DLP technology is once again at the forefront of a major industry shift,” said Jeff Marsh, vice president and general manager of DLP technology at TI. “We’re enabling the creation of maskless digital lithography systems that empower engineers around the world to breakthrough the current limits of advanced packaging and bring powerful computing solutions to market.”

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Anritsu Corporation will participate in the upcoming India Mobile Congress (IMC) 2025, taking place in New Delhi, India, from October 8 to October 11, to showcase its latest innovations in communications test and measurement solutions.

As the mobile and connectivity industry continues to expand with the rapid adoption of 5G, IoT, and emerging technologies such as AI-driven services, cloud computing, and immersive XR applications, the demand for robust, reliable, and efficient test solutions has never been greater. At IMC 2025, Anritsu will highlight its comprehensive portfolio designed to meet these evolving needs, supporting operators, device manufacturers, and ecosystem partners in accelerating their technology development and deployments.

Virtual Signalling Tester

5G Network Simulator, a software-based solution for 5G IoT chipset and device testing. It enables virtual 5G network simulation on a PC, supporting RedCap tests and efficient device verification.

Radio Communication Test Station MT8000A

All-in-One Support for RF Measurements, Protocol Tests and Applications Tests in FR1 (to 7.125 GHz) and FR2 (Millimeter-Wave) Bands. MT8000A is used by Mobile Chipset, Mobile Handset, IoT Device, 5G base Station R&D and manufacturing companies.

Field Master Pro MS2090A

Handheld Spectrum Analyzer delivers the highest continuous frequency coverage up to 54 GHz and real-time spectrum analysis bandwidth up to 150 MHz to address current and emerging applications such as 5G &LTE Base Station Measurement, Satellite System Monitoring, Interference Hunting, EMF measurement and much more.

Anritsu Collaborates with Altair to Demonstrate Integration of Anritsu Monitoring Systems with Spectrum Management Software WRAP.

Altair WRAP integrates georeferenced data from Anritsu spectrum analyzers to validate coverage, interference, and spectrum compliance with field reality.

VectorStar Broadband VNA ME7838

The VectorStar ME7838 Series broadband VNA offers the widest available 2-port single frequency sweep from 70 kHz to 110, 125, 145, and 220 GHz with mmWave bands up to 1.1 THz. Vector Star is a cost-effective solution for OnWafer Measurements, RIS, Novel Channel Sounding applications along with active and passive devices measurement supporting 5G and 6G technology.

Optical Spectrum Analyzer MS9740B

MS9740B offers Single mode and Multimode Fiber application and high-speed optical devices such as optical transceivers, VCSEL, and DFB light sources testing R&D and production.

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The industrial scenery is getting reshaped by digital twins and physical AI. These virtual replicas of factories, facilities, or even processes were once mainly conceived for planning purposes and now have become more operationally oriented, mainly concerned with training autonomous robots, AI-powered machinery, and operational systems to perform their tasks safely and efficiently in the real world. High-tech OpenUSD, immersive simulation tools, and AI-driven modeling are helping developers create high-fidelity digital twins at scale, removing most of their manual labor and fast-tracking industrial AI deployment.

Scaling Industrial AI and Physical AI with Digital Twins

Digital twins provide a virtual environment within which physical AI agents such as autonomous robots or smart factory systems can learn and adapt before deployment. Simulations of a finer quality came at the cost of much manual effort. Today, with advanced OpenUSD, neural reconstruction, and world foundation models (WFMs), developers can now set about constructing these complex digital replicas far more rapidly.

Key developments include:

SDKs bridging between simulators: They allow people to simulate robots and systems in diverse simulators, thus virtually providing access for robotics developers anywhere in the world.

• Neural rendering and 3D reconstruction libraries: These allow the capture and reconstruction of sensor data from the real world, simulation, and photorealistic rendering.
• Open-source robotics frameworks: Offer readymade environments and schemas for robots and sensors to help reduce the simulator-to-reality gap.
• World foundation models (WFMs): Used to create synthetic datasets and to carry out higher-order reasoning on these datasets for the benefit of physical AI applications.
• Advanced rendering and AI-assisted material modeling: Provide scalable ways to create industrial-grade digital twins.

OpenUSD: Powering the Future of Industrial 3D Innovation

OpenUSD constitutes the backbone of industrial 3D workflows, having become a standard for digital twin creation with interoperability between industrial and 3D data. By now, the Alliance for OpenUSD (AOUSD) has been extended to include Accenture, Esri, HCLTech, PTC, Renault, and Tech Soft 3D, thus showing great endorsement of OpenUSD and present objectives of uniting industrial 3D workflow.

To support this growing ecosystem, NVIDIA has introduced an industry-recognized OpenUSD development certification and a digital-twins learning path, helping developers gain the skills needed to build the factories and industrial systems of tomorrow.

Industry Applications Driving the Future:

Some of the global leaders use digital twins and OpenUSD for transforming industrial operations:

• Siemens: Teamcenter Digital Reality Viewer allows working with large-scale digital twins for visualization and collaboration, thereby reducing physical prototyping and faster time-to-market.
• Sight Machine: Operator Agent platform amalgamates live production data with AI-driven recommendations and digital twins for better plant visibility and faster decision-making.
• Rockwell Automation: Emulate3D Factory Test creates physics-based digital twins from simulation to optimize automation and autonomous systems.
• EDAG: Uses digital twin for project management, production layout optimization, worker training, and data-driven quality assurance.
• Amazon Devices & Services: Uses digital twin environments to train robot arms for assembly, testing, packaging, and auditing, all with no physical intervention.
• Vention: Offers plug-and-play digital twin and automation solutions so intelligent manufacturing systems can be deployed more speedily.

Conclusion:

The combination of OpenUSD, digital twins, and AI-driven simulation is transforming industrial operations on the ground. By proving the exact, scalable virtual environment, they allow manufacturers, robot developers, and physical AI engineers to innovate faster, cut down expenses, and systematize safer and smarter solutions faster than ever before.

(This article has been adapted and modified from content on NVIDIA.)

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The global energy sector is at a historic turning point. Renewable energy integration, EV promotion, and AI-driven consumption create more demand on already complex grids. The transformation calls for a new era of energy professionals who can build a bridge between traditional engineering and digital technologies-the infrastructure upgrades alone cannot solve the equation.

The Digital Shift in Energy Systems

Modern power systems evolve into interconnected, intelligent networks. Smart grids, real-time balancing, and consumer-driven energy management are redefining how electricity flows. Still, the digital revolution carries many challenges requiring upskilling and interdisciplinary knowledge to solve.

Top Challenges Facing the Next Generation Workforce:

1. Dual-Skill Gap

Engineers today need expertise in network-relevant issues and traditional grid operations, plus in cybersecurity matters. Still, there are few professionals with an engineering background and digital expertise; this scarcity leads to inefficiency in troubleshooting and system reliability.

2. A Shift Toward Virtualization

Careful changes from hardware-based to software-driven operations have increasingly taken protection and control functions onto a virtual platform. Hence, engineers will have to embrace digital tools with data analytics and server technologies that are not traditional to the power area.

3. Cross-system Collaborations

Data exchanges must be smooth as renewable assets such as solar and battery storage interfacing with distribution and transmission networks. Therefore, engineers must manage various protocols and formats, settling voltage, frequency, and power flows after the interface in real time.

Building the Workforce of Tomorrow

Such challenges require: Full-training in digital communication, grid standards such as IEC 61850, and advanced networking.

Simplified Tools and Platforms that reduce technical complexity and enable engineers to focus on system optimization.

Collaborative Ecosystems where power engineers, IT experts, and operators work together to maintain resilience across distributed networks.

Conclusion:

The future of energy will be shaped as much by people as by technology. Companies that invest in digital skills, upskilling programs, and collaborative frameworks will lead the transition to resilient, intelligent grids. Industry leaders such as Moxa, with their training initiatives and global expertise, are playing a vital role in equipping professionals to thrive in this new era ensuring the workforce is ready to power the grids of tomorrow.

(This article has been adapted and modified from content on Moxa.)

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ANRITSU CORPORATION has developed and launched its new 60 GHz optical sampling oscilloscope MP2110A-080 option for the BERTWave MP2110A. This option verifies the performance of 200G/Lane optical transceivers forming the foundation of faster data-center communications and growing AI deployment. It delivers high PAM4 TDECQ evaluation accuracy and measurement productivity for next-generation high-speed optical transceivers, such as 1.6T and 800G, supporting strong quality assurance of large-capacity, high-speed communications infrastructure.

This test solution was exhibited as a reference at the China International Optoelectronic Exposition (CIOE 2025) on September 10, 2025, and will also be showcased at the European Conference on Optical Communication (ECOC 2025), one of the world’s leading international conferences in the field of optical communications, to be held in Copenhagen, Denmark, from September 29 to October 1, 2025.

Development Background
With the growth of AI data centers, optical communication speeds are increasing from 800G to 1.6T, and transmission rates are shifting from 50 Gbaud (100G/Lane) to 100 Gbaud (200G/Lane). As transmission speeds increase, there is a growing need for wideband sampling oscilloscopes capable of evaluating higher frequency components in optical transceiver signals.

Product Features
The all-in-one MP2110A solution integrates the necessary functions for physical-layer evaluation of optical transceivers during development and manufacturing. This new 60 GHz oscilloscope MP2110A-080 option enables evaluation and analysis of next-generation high-speed 200G/Lane communication standards.

• High-Accuracy PAM4 TDECQ Measurement: With the performance of a reference receiver supporting PAM4 signals up to 120 Gbaud, the MP2110A offers reliable TDECQ evaluations by leveraging the high measurement accuracy of existing models.
• Improved Efficiency with Simultaneous 4-Channel Measurement: By measuring four optical signals simultaneously, the MP2110A cuts measurement time and improves operation efficiency. Batch evaluation of multiple channels simplifies measurement systems and processes to enhance productivity.
• Further Productivity Gains with Faster Measurement: Increasing the MP2110A sampling speed fourfold compared to previous models shortens measurement times even further. Stable operation with a built-in PC improves R&D and manufacturing efficiency.
• Cost-Effective 4-Channel Software Upgrade Option: With a software upgrade path to 4-channels, the 2-channel option lowers initial costs, allowing flexible deployment supporting future expansion matching budget and evaluation environment.

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When we ask if AI knows anything, we are, in the strictest sense, not referring to memory or experience as humans would. Instead, we are exploring a very complex mathematical domain in which AI predicts what comes next in a language. Upon realization, AI is not a particular source of truth; it is a system that simulates understanding through patterns, probabilities, and memory architecture. This article attempts to unravel the puzzle of how AI converts text into knowledge-like predictions, from tokens and embeddings to the machines that carry out these operations.

From Words to Tokens

AI does not interpret after human fashion. Upon encountering the sentence “The moral of Snow White is to never eat …,” it first converts it into some string of tokens-the smallest units it can process. Tokens can be whole words, parts of words, punctuations, or spaces. For example, the sentence above would be tokenized as:

[“The” | ” moral” | ” of” | ” Snow” | ” White” | ” is” | ” to” | ” never” | ” eat”]

This conversion is only the initial step of a highly structured process that takes human language and converts it into something an AI can work with.

Embeddings: From Tokens to Numbers

Upon tokenization, each token is mapped to an embedding-an abstract numerical representation revealing the statistical relationship S-theory between words. These embeddings exist in a high-dimensional embedding space-theoretical map of word associations learned after the analysis of great volumes of text. Words that appear in similar contexts cluster together-not really because the AI “understands” them in the human sense-but because language-based hypothesis-building patterns suggest they are related. For instance, “pirouette” and “arabesque” might cluster together, just as “apples” and “caramel.” The AI does not comprehend these words in human terms; it simply recognizes patterns of their co-occurrence.

Simulated Knowledge

Human beings derive meaning from experience, culture, and sensation. AI, on the other hand, simulates knowledge. So, when arguing for sentence completion, it invents statements: “food from strangers,” “a poisoned apple,” or simply “apples.” Each is statistically plausible, yet none comes from comprehension. AI is about predicting what is likely to be next, not what is “true” in a human sense.

The Abstract World of the Embedding Space

Embedding space is where AI’s predictions live. Each word becomes a point in hundreds or thousands of dimensions, having something to do with the patterns of meaning, syntax, and context. For example, in a simplified 2D space, “apple” might cluster near “fruit” and “red.” Add more dimensions, and it could relate to “knowledge,” “temptation,” or even “technology,” denoting its cultural and contextual associations.

Because such spaces are high-dimensional, they cannot be directly visualized, but serve as a backdrop against an AI’s scenario of language prediction. The AI does not consider concepts or narrative tension; it calculates statistically coherent sequences.

From Math to Memory

These embeddings are not just theoretical matrices; they require physical memory. The embedding of each token consists of hundreds or thousands of numerical entries, which are stored in various memory systems and worked upon by hardware. As the size of the AI model increases and it accords with more tokens, memory turns out to be one major issue, regarding the speed and complexity of predictions.

Originally created for scientific work, High-bandwidth memory (HBM) would be applied towards AI so models can efficiently handle overwhelming amounts of data. Memory is no longer merely a storage device; it determines the amount of context an AI remembers from training examples and how quickly it accesses this information to make predictions.

Looking Ahead

The knowledge base of an AI has always depended on what the AI can hold in-memory. As longer conversations or more complicated prompts would require more tokens and embeddings, so would the memory requirements. These limitations end up shaping the way the AI represents the context and keeps coherence in text generation.

Understanding AI’s statistical and hardware basis does not undermine the usefulness of AI; rather, it sets its interpretation to that of a very complex system of probabilities and memory, instead of some kind of conscious understanding.

(This article has been adapted and modified from content on Micron.)

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Beyond 300 Layers of Memory

The race to make denser, more-powerful 3D NAND flash memory has led to huge innovation but also new manufacturing challenges. Taller devices-three-hundred-plus layers-could be threatened in yield, performance, and reliability due to constructive-tier bending and material collapse. In this sense, these challenges come from stress mismatches in alternating stacks of silicon nitride (SiN) and oxide (TEOS) layers that constitute this memory structure.

To comprehend and solve the problem, the Semiverse Solutions team used SEMulator3D virtual Design of Experiments (DOE) to replicate, measure, and analyze stress-induced deformation in the fabrication process. The outcomes emphasize the very important consideration of stress management and material properties in realizing manufacturable high-layer-count NAND architectures.

Understanding How 3D NAND Is Built

It achieves higher densities in 3D NAND by stacking SiN and oxide layers vertically in a staircase arrangement. Contacts are etched through such tall stacks to reach underlying transistors, and slit etchings divide the structure into functional memory blocks.

Until SiN can be replaced by conductive metal, an oxide cantilever is temporarily formed: it is anchored at one end while being unsupported at the other end. This rather fragile structure increasingly becomes vulnerable as the number of layers grows, expanding from ~550 nm at 200 layers to ~700 nm at 300 layers. Various contributors to tier collapse are as follows:

• Stress and strain mismatches between SiN and oxide
• Surface tension during SiN removal
• Cantilever length and geometry

What the Virtual Studies Revealed

Using SEMulator3D’s stress analysis tools, the team conducted two DOE studies to characterize how stress may evolve with tier bending and collapse.

Key findings from the first DOE:

• SiN Stiffness (Young’s Modulus, Ey) and oxide thickness are the dominant variables influencing stress-based deformation.
• Present at low Ey values (70 GPa) due to minimal displacement.
• At 125 GPa, collapse occurred at longer cantilever lengths (700 nm), especially with thinner oxides.
• At 256 GPa, severe displacement and voiding occurred across all test conditions.
• Increasing oxide thickness improved resistance but did not eliminate failure risks.

The second DOE compared the effects of intrinsic SiN stress (compressive vs. tensile). Results showed compressive SiN caused larger displacements, widening the range of potential collapse.

The manufacturing implications

These studies present obvious engineer methods that can be employed to maximize yields in ultra-high-layer NAND:

• The SiN and oxide stress values need to be matched and hopefully reduced.
• Shorten cantilever length by designing an etch profile.
• If possible, increase oxide thickness to stabilize the stack.

Through virtual simulation of these interactions, SEMulator3D engineers have the ability to realize the process changes that actually matter without being solely reliant on expensive experimental work on the actual silicon.

Conclusion

With NAND flash closing in on 300 layers and more, tier bending and collapse remain edge manufacturing threats. Stress analyses and virtual DOE studies by the Semiverse team have revealed that exacting control of material properties and stack geometry is key to both securing yields and shortening time to market.

With the SEMulator3D platform from Lam Research, chipmakers gain a powerful predictive lens helping transform potential failure points into opportunities for robust, scalable memory innovation.

(This article has been adapted and modified from content on Lam Research.)

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‘Nature Electronics’ Paper Details System That Blends Best Traits Of Once-Incompatible Technologies—Ferroelectric Capacitors and Memristors

Breaking through a technological roadblock that has long limited efficient edge-AI learning, a team of French scientists developed the first hybrid memory technology to support adaptive local training and inference of artificial neural networks.

In a paper titled “A Ferroelectric-Memristor Memory for Both Training and Inference” published in Nature Electronics, the team presents a new hybrid memory system that combines the best traits of two previously incompatible technologies—ferroelectric capacitors and memristors into a single, CMOS-compatible memory stack. This novel architecture delivers a long-sought solution to one of edge AI’s most vexing challenges: how to perform both learning and inference on a chip without burning through energy budgets or challenging hardware constraints.

Led by CEA-Leti, and including scientists from several French microelectronic research centers, the project demonstrated that it is possible to perform on-chip training with competitive accuracy, sidestepping the need for off-chip updates and complex external systems. The team’s innovation enables edge systems and devices like autonomous vehicles, medical sensors, and industrial monitors to learn from real-world data as it arrives adapting models on the fly while keeping energy consumption and hardware wear under tight control.

The Challenge: A No-Win Tradeoff

Edge AI demands both inference (reading data to make decisions) and learning (updating models based on new data). But until now, memory technologies could only do one well:

• Memristors (resistive random access memories) excel at inference because they can store analog weights, are energy-efficient during read operations, and the support in-memory computing.
• Ferroelectric capacitors (FeCAPs) allow rapid, low-energy updates, but their read operations are destructive—making them unsuitable for inference.

As a result, hardware designers faced the choice of favoring inference and outsourcing training to the cloud, or attempt training with high costs and limited endurance.

Training at the Edge

The team’s guiding idea was that while the analog precision of memristors suffices for inference, it falls short for learning, which demands small, progressive weight adjustments.

“Inspired by quantized neural networks, we adopted a hybrid approach: Forward and backward passes use low-precision weights stored in analog in memristors, while updates are achieved using higher-precision FeCAPs. Memristors are periodically reprogrammed based on the most-significant bits stored in FeCAPs, ensuring efficient and accurate learning,” said Michele Martemucci, lead author of the paper.

The Breakthrough: One Memory, Two Personalities

The team engineered a unified memory stack made of silicon-doped hafnium oxide with a titanium scavenging layer. This dual-mode device can operate as a FeCAP or a memristor, depending on how it’s electrically “formed.”

• The same memory unit can be used for precise digital weight storage (training) and analog weight expression (inference), depending on its state.
• A digital-to-analog transfer method, requiring no formal DAC, converts hidden weights in FeCAPs into conductance levels in memristors.

This hardware was fabricated and tested on an 18,432-device array using standard 130nm CMOS technology, integrating both memory types and their periphery circuits on a single chip.

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Microchip’s MCP9604 thermocouple conditioning IC reduces the cost and complexity of in-line production applications that operate in high and low temperature extremes

Precision four-channel temperature measurement is critical for production-line applications ranging from chemical and food processing, manufacturing process control and medical and HVAC equipment to refrigerated, cryogenic and other carefully controlled environments. With the introduction of the MCP9604 integrated thermocouple conditioning IC, Microchip Technology has overcome a thermal measurement and integration barrier with the first single-chip, four-channel  I2C thermocouple conditioning IC to deliver up to ± 1.5°C accuracy and provide an alternative to discrete and multichip thermocouple conditioning solutions that can introduce errors and add system design complexity.

“For more than two centuries, the thermocouple has been a critical tool for measuring extremely high temperatures, but the necessary precision and accuracy could not be achieved with the level of integration and cost-effectiveness that is required for today’s demanding production-line applications,” said Keith Pazul, vice president of Microchip’s mixed-signal linear business unit. “Our device now delivers a combination of precision, integration and cost-effectiveness, helping reduce the need for as many as 15 discrete components and associated system design challenges.”

The MCP9604 device delivers its advanced measurement accuracy at four thermocouple locations by using higher-order NIST ITS-90 equations rather than the single-order linear approximations of analog amplifier designs. As an example, it achieves ninth-order accuracy with K-type thermocouples, all in one integrated chip containing the ADCs, cold junction compensation temperature sensors, amplifiers and other components required for the signal chain, temperature measurement and math engine.

Removing the need for external components simplifies PCB design, reduces bill of materials costs, and can help eliminate the weeks of costly, time-consuming and complex unit-by-unit in-line validation and calibration that discrete solutions require in the thermocouple measurement signal chain before they can begin reporting data to the host system.

The MCP9604 also offers flexibility and versatility by supporting the eight most common thermocouple types including the J option as well as the K option for operating at temperatures as low as
-200°C. In addition to supporting a wide, -200°C to +1372°C temperature range across a diverse range of industrial applications, the MCP9604 also supports I2C communication to allow easy integration with microcontrollers and other digital systems.

Building on Earlier Advancements

The MCP9604 builds on the release of Microchip’s single-channel thermocouple conditioning IC, the first all-in-one device to deliver up to ± 1.5°C accuracy. The core competencies that made this device possible have paved the way for the company’s four-channel single-chip MCP9604 device that delivers its digital temperature reading with industry-high accuracy levels for an I2C thermocouple conditioning device.

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As cities move toward electric mobility and smarter infrastructure, seamless and safe power delivery is more important than ever. Shivam Rajput, Founder and CEO of ElectraWireless, is pioneering wireless electricity solutions that reduce EV downtime, extend fleet lifecycles, and power devices without cords or plugs. Combining advanced materials science, adaptive resonant coupling, and smart thermal management, his innovations aim to make wireless power scalable, safe, and efficient. In this conversation with ELE Times, he shares lessons from pilots, technological breakthroughs, and how India could benefit from cost-effective, large-scale wireless EV infrastructure.

Excerpts:

ELE Times:  What implications does wireless electricity have for EV adoption, safety, and the broader global energy transition?

Shivam Rajput: Wireless electricity isn’t just about convenience, it addresses real consumer challenges and can help the EV market thrive. EV adoption today is often slowed by downtime, manual charging, connector wear, and safety concerns. Consumers want simple, safe, and sustainable solutions, not just car features. Wireless electricity ensures EVs charge automatically at parking spots or even while moving, maintaining battery health and keeping vehicles ready at all times. Beyond EVs, homes, workplaces, and cities become safer with fewer exposed wires and connectors, reducing the risk of accidents and outages. This technology also minimizes energy waste, making it a crucial step in the global energy transition.

ELE Times: What are the key breakthroughs that have enabled high-power wireless electricity transmission through everyday surfaces like wood, quartz, or automotive-grade materials?

Shivam Rajput: Our system delivers power only when needed, without heating surfaces or wasting energy. Materials innovation allows seamless integration into wood, quartz, automotive-grade panels, and other common surfaces. Safety is ensured through foreign object detection, which automatically halts transmission if anything interferes. For autonomous systems, from robotics to EVs, devices no longer need to stop to plug in; they charge automatically wherever transmitters are installed. These breakthroughs make high-power wireless electricity scalable, safe, and efficient across multiple sectors.

ELE Times:  What lessons emerged from pilots in robotics, kitchens, and workplace environments, and how are they shaping your approach to scaling the technology?

Shivam Rajput: Pilots highlighted three critical lessons: seamless integration, safety, and efficiency. In smart kitchens, multiple appliances operated wirelessly without interference, showing the importance of modular design. Workspaces benefited from embedded, unobtrusive power, improving usability and safety. In robotics and autonomous systems, wireless charging dramatically reduced downtime, enabling continuous operation and boosting productivity. Eliminating manual plug-ins also reduces electrical faults, making devices safer for children and workplaces. These insights inform a scalable platform ready for enterprise-level and consumer applications.

ELE Times:  In what ways could wireless charging reduce downtime and extend the lifecycle of EV fleets?

Shivam Rajput: Wireless charging allows EVs to charge in motion or at strategically located parking spots, reducing wear on connectors and preserving battery health. Fleets can operate longer, with fewer interruptions, while maintenance costs decrease. This contactless approach accelerates operations and reduces total cost of ownership, making EV fleet management more efficient and sustainable.

ELE Times:  Can wireless power assist in building scalable, cost-effective EV infrastructure in countries such as India?

Shivam Rajput: India is one of the most promising markets for EV adoption. Our retrofit-friendly wireless system integrates with existing grids, lowering installation complexity and costs. By embedding chargers into roads, parking spots, or city infrastructure, EVs can charge seamlessly while driving or parked, what we call “monorail charging.” This approach enables large-scale adoption, ensures reliability, and reduces safety risks associated with exposed connectors. The system supports faster EV market growth while building a sustainable, energy-efficient infrastructure.

ELE Times: What technological advances from ElectraWireless enabled them to scale the transmission of wireless power from as low as 5W all the way up to 40kW?

Shivam Rajput: Adaptive resonant coupling, dynamic field shaping, and smart thermal management allow safe and efficient power delivery across surfaces, from small electronics to EVs. Foreign object detection ensures absolute safety during transmission. Precision energy delivery reduces waste and maintains high efficiency for continuous operation. These advances unlock a fully scalable wireless electricity ecosystem, enabling applications in robotics, kitchens, workspaces, and urban EV infrastructure.

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Satellites, spacecraft, and defense systems rely on increasingly complex software ecosystems that integrate open-source, third-party, and legacy components. Recent cybersecurity events have highlighted how vital it is to track, secure, and manage these software supply chains.

The Risk of Vulnerable Third-Party Components

At Black Hat 2025, some very serious vulnerabilities were discovered in some of the most commonly used platforms for satellite control: Yamcs, OpenC3 Cosmos, and NASA’s cFS Aquila. Such flaws-range from remote code execution, denial of service, weak encryption to manipulation of satellite operations-force criminals into changing orbital paths or stealing cryptographic keys, usually without even detection.

Even seeming-to-be-secure encryption libraries such as CryptoLib-which NASA uses-were found to harbor multiple critical vulnerabilities. Exploiting these, attackers could crash the onboard software, reset its security state, or compromise encrypted communications. These findings reinforce that third-party components remain among the easiest risks to exploit in aerospace and defense software.

SBOMs: Ensuring Transparency Across the Software Stack

Software Bill of Materials lists all components within a system involved. In practice, it finds vulnerabilities, manages risk, considers compliance, and goes into incident response. The SBOM can be only as good as its accuracy, completeness, or governance structure.

In other words, to improve security posture, an organization must hold centralized processes for the validation, enrichment, and continuous surveillance of SBOMs, so that both upstream ones (those from development) and downstream ones (those from deployed systems) are held accountable, validated, and acted upon.

Closing the Gaps

Modern SBOM platforms, such as Keysight’s solutions, enhance binary similarity checks and code emulation to detect components when source information is partial or missing. This allows SBOMs to be reliably created for firmware and software or for container images so that no single component-in whatever form it exists-goes untracked.

Hence, giving full visibility, rigorous validation, and operational governance serve systems in aerospace and defense better in recognizing vulnerabilities, quick incident response, and establishing trust across software supply chains. This closes critical gaps while trying to keep mission-critical systems safe from the ever-evolving cyber threats.

(This article has been adapted and modified from content on Keysight Technologies.)

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Electrochemical impedance spectroscopy (EIS) is a powerful technique for studying electrochemical systems such as electrochemical cells, batteries, fuel cells, corrosion protection setups, and sensors. By differentiating processes such as charge transfer across the electrode interface, diffusion, double-layer behavior, etc., by applying small sinusoidal signals generated in random magnitudes over a wide frequency range, we invoke responses from such mechanisms. Equivalent circuits in the traditional sense can conveniently give impedance data representations; however, they do not suffice when overlapping or nonideal processes come into play. Modern physics-based modeling approaches enable the researcher to consider adsorption, mass transport, and electrode surface effects far beyond simple resistor–capacitor analogies.

EIS Real-Life Applications

Sensitivity renders EIS paramount for:

Batteries: Detects ion and electron transport at early stages of degradation and capacity fading.

Corrosion: Detects subtle interface changes between metal and electrolyte in pipelines, concrete, and marine structures.

Fuel Cells: Performance and durability improvements by separating contributions of catalyst layers, membranes, and reactant flows.

Sensors: Evaluates electrode interactions with target molecules, enabling applications like glucose monitoring.

The Limitations of Equivalent Circuits

For the simpler reactions, the impedance data frequently fit an elementary equivalent circuit: a resistor in series with a parallel resistor-capacitor pair. In a Nyquist plot, this will look like a neat semicircle corresponding to charge transfer resistance. However, rarely do real systems behave so nicely. Adsorption, diffusion, and electrode morphology will add time constants and overlapping processes with which the equivalent circuit cannot always keep up. Physics-based models are, therefore, chosen to solve the underlying electrochemical equations, thus providing a more accurate picture of how these processes may interrelate.

Consider the Nonidealities of EIS:

Important Factors

1. Adsorption–Desorption Dynamics

Intermediates may adsorb on electrodes during electrochemical reactions. The changing surface coverage may, over time, change the impedance response. For instance, with copper deposition, a progressive increase in coverage of additives changes the spectra from two capacitive loops into one dominated by an inductive loop at low frequency. Such effects demonstrate the crucial nature of adsorption in the design of such systems.

2. Mass Transport Limitations

In fuel cells, the diffusion and convection of gases such as hydrogen and oxygen significantly affect performance. Through impedance plots, one can observe the changes in charge-transfer and diffusion contributions as functions of the operating potential:

• Distinct high- and low-frequency loops at intermediate voltages
• At low voltages, loops combine with overlapping time constants
• On the strongly cathodic side, diffusion is dominant, and a single huge loop appears

This sequence clearly demonstrates the ability of EIS to differentiate between reaction kinetics and transport limitations.

3. Electrode Surface Effects

Surface roughness and uneven geometries alter the effective electrochemical area, thus shifting the impedance response. Accounting for electrode structures helps render better predictions in situations where morphology is important.

Handling Residual Behaviors

Sometimes, the impedance response cannot be explained by referring to adsorption, diffusion, or surface structure. A constant phase element (CPE) is then introduced to incorporate frequency-dependent effects that deviate from an ideal capacitive behavior. From a mechanistic standpoint, (CPE)behave as systems in which the mathematical expression describing a single mechanism can be modified with a continuous parameter that accounts for system complexity.

Conclusion:

Electrochemical impedance spectroscopy has remained one of the most versatile electrochemical experimental probes, and by moving beyond the simple circuit analogy to include adsorption, diffusion limitation, and surface-effects, researchers gained a more realistic view of the system behavior. Modeling platforms such as COMSOL Multiphysics support these newer approaches, albeit all electrochemical disciplines offer a general foundation.

From extending battery lifetimes to detecting early corrosion, EIS when paired with detailed physical insights continues to unlock new possibilities for innovation and reliability in electrochemical technologies.

(This article has been adapted and modified from content on COMSOL.)

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“The Semicon India program has brought new energy to the ecosystem, signaling the government’s commitment to building a resilient and self-sufficient semiconductor value chain,” says Jose Lok, Product Category Director, Semiconductors, element14, in an exclusive interaction with the ELE Times under its exclusive series ‘Powering the Chip Chain.’ As India wrapped up its largest electronics and semiconductors carnival this month, we grabbed the hot seat to discuss some very pertinent issues with Jose, representing element14, a consistent feature of Global 500 Fortune companies, with its resounding presence across 140 countries, with over 125 company locations.

Reflecting on India’s journey in electronics and semiconductors, he says, “India’s semiconductor landscape is going through a remarkable transformation.” Underlining the impact of schemes like Semicon India, PLI, and DLI, he highlights the momentum contributed by these schemes to the wholesome electronics and semiconductor ecosystem of India. This is further coupled by India’s growing influence over the global supply chain as demand peaks back home across sectors like automotive, IoT, and industrial automation.

Making Access Easier and Efficient

In the interaction, Jose touched upon the critical challenges faced by the design engineers in developing new products. He says, “Engineers often face long lead times, difficulty sourcing small quantities for prototypes, and a lack of visibility into real-time inventory,” as he underlines the pain points.

He further adds that the company has made its business in India largely by addressing these pain points and making it easier for engineers in prototyping and R&D, including its intuitive e-commerce platform and an inventory of over 950,000 products from 2,000 leading suppliers.

Emerging Opportunities

Further adding to the impact of the government schemes, he says, “The increased momentum has translated into increased demand from OEMs and design houses. It’s also creating new opportunities for companies like ours to support emerging players with the right components, kits, and engineering resources.” Further, adding to the same, he emphasizes the visibility and structure offered by these to enable distributors like element14 to work more closely with the Indian engineers and also align their plans accordingly.

element14’s India Plans

Talking about the company’s India plans, he says, “For element14, India is a strategic growth market. It represents not just an opportunity to expand but to partner with a new generation of engineers and innovators.” He also sounds quite optimistic when it comes to India’s role in the global supply chain of semiconductors, as he underlines the growing demand for components across the globe in segments like automotive, IoT, and industrial automation.

Challenges in the Indian Landscape

Every company faces one or the other challenge when it comes to scaling in a given nation under certain circumstances. For element14, these remain to be infrastructure variability, diverse needs, and timely last-mile delivery, specifically in the remote areas. He says, “Strategically, the pace of policy execution and the need for talent development in chip design and testing are areas that will require continued focus.”

Find the Part-01 at “Exclusive Feature: “We’re Using AI to Help Us Make Better, Faster, and More Accurate Decisions,” says DigiKey’s Ken Paxton”

Changing Roles

Reflecting on how the nation’s stride in electronics manufacturing impacts the distributors, he says, “The expectation from distributors has shifted beyond just availability.” The distributors are today expected to provide better technical support, along with alternative prototyping options, and also better credit terms, enabling an end-to-end partnership in the product development cycle.

As Jose puts it, “As India moves toward becoming a global electronics hub, distributors must grow into enablers of speed, reliability, and innovation.”

As India’s semiconductor ambitions gather pace, element14 is positioning itself as more than a distributor. “Our focus in India and across Asia is clear. We want to support innovation in a truly end-to-end way, from the early stages of design all the way to mass production and beyond,” says Jose. At its core, he adds, the company’s goal is “to be a reliable partner for innovation, one that grows with our customers and helps them build what’s next.”

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The semiconductor industry is entering a new phase where artificial intelligence is taking on some of the most complex aspects of chip development. With design cycles growing more challenging due to advanced system-on-chip (SoC) requirements, AI-driven design automation tools are proving to be a game-changer bringing higher productivity, improved performance, and faster time to market.

Rising in Complexity in SoC Development

Modern (SoC) has multiple functions integrated, making them huge optimization targets for power, performance, and area (PPA). Mock manual iterative style often cannot efficiently address design rule checks (DRCs), timing closure, and multi-block optimizations. That has created an ever-increasing demand for intelligent design solutions that can handle scaling design.

Productivity Gains Through AI-Optimized Workflows

According to industry evaluation reports, AI-enabled chip design platforms have shown transformative improvements. These reports demonstrate productivity improvements, speeding up design completion from more than five to thirty times over and reducing design rule checks (DRCs) by as much as 70%. Performances outcomes have also improved significantly, highlighting how AI can streamline bottlenecks that previously slowed down development.

Accelerating Time to Market

Products must be delivered on time in very demanding markets like display drivers, imaging solutions, and advanced electronics. This makes automated design optimization allow the engineering teams to focus on innovation rather than repetitive fine-tuning, ensuring that smarter, quicker, and more cost-efficient solutions reach the market.

AI for Competitive Edge

By implementing intelligent design automation, not only do companies improve their operations-oriented efficiency, but they also boost their actual competitive thrust. The concurrent multiple-block optimization of large (SoC) is turning into the strategic differentiator in markets where performance and speed to market define success.

Looking Ahead

AI-driven chip design automation has already gone beyond being a laboratory experiment it is fast becoming an orthodoxy in modern semiconductor engineering. The early adopters, foremost of them being Himax with Cadence’s Cerebrus Intelligent Chip Explorer, demonstrated astonishing gain in productivity and design quality. As more semiconductor companies embrace similar AI-driven platforms, the industry is poised to unlock new levels of creativity, reduce development costs, and accelerate the path to next-generation chips.

(This article has been adapted and modified from content on Cadence.)

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Largest-ever edition in Bengaluru underscores India’s journey to becoming a global electronics manufacturing hub

• Featured 50,194 visitors, unprecedented international participation of 6000+ brands from 50+ countries
• Targeted international pavilions and 2,000+ structured business matchmaking sessions transformed potential into partnerships with measurable commercial outcomes.
• Conferences bridged policy, manufacturing, and innovation divides, creating actionable pathways to India’s technological leadership rather than theoretical aspirations.

Electronica India and Productronica India 2025, held at the Bangalore International Exhibition Centre (BIEC), concluded three days of significant business engagement, industry discourse, and technological exploration. The trade fairs, featuring over 6000+ global brands from more than 50 countries and attracting 50,194 trade professionals, reinforced India’s expanding role within the global electronics manufacturing landscape.

Organised by Messe Muenchen India, these co-located trade fairs continue to serve as a strategic meeting point for the entire electronics manufacturing value chain, encompassing design, components, assembly, automation, embedded systems, and quality assurance. While established global entities leveraged the platform to consolidate their regional footprint, Indian manufacturers, Electronics Manufacturing Services (EMS) providers, and material suppliers actively showcased advanced capabilities, often with a view toward securing international export partnerships.

Government representation, including senior leadership from Karnataka – Shri. Rahul Sharanappa Sankanur, IAS, Managing Director, Managing Director Karnataka Innovation and Technology Society (KITS), Smt. Gunjan Krishna, IAS, Commissioner, Industries and Commerce Department, Government of Karnataka and Dr. Darez Ahamed, IAS- Managing Director, Guidance Tamil Nadu affirmed ongoing state-level commitments to cultivating electronics manufacturing hubs. Concurrently, dedicated international pavilions from Japan, Taiwan, and Germany were prominent, solidifying the show’s reputation as a key gateway for international enterprises seeking to engage with India’s dynamic ecosystem.

The facilitated Buyer-Seller Forum proved highly effective, recording over 2,000 structured meetings. Sourcing teams from key sectors such as automotive, industrial automation, and consumer electronics–including leading companies such as Samsung, Spark Minda, and Jio platforms–engaged directly with component manufacturers and solutions providers. Discussions primarily revolved around optimizing lead times, establishing local inventory, implementing cost engineering strategies, and fostering supplier development – all critical aspects for global supply chain resilience.

With Rohit Sharma as the face for electronica India and productronica India 2025, the platform also expanded its reach beyond the immediate industry community. His association helped connect the event’s core message to a wider and increasingly tech-aware audience, highlighting the growing societal relevance of electronics manufacturing in India.

Exhibitor Testimonials

Exhibitors consistently reported high-quality interactions. Sanjay Kumar, Managing Director from Kyocera Asia Pacific India Pvt. Ltd an electronica India exhibitor, said, “The scale and focus here in Bengaluru this year was truly impressive. The international pavilions provided direct access to component suppliers we would typically need to visit multiple regional shows to engage with.”

For process-focused technology providers, the utility was clear Gaurav Mehta, President – Business Development from Kaynes Technology India Ltd, an exhibitor at productronica India, stated, “For a process-driven technology company like ours, productronica India gave us access to the right mix of automation buyers and R&D teams. What impressed us was not just the quantity of inquiries but their technical specificity—Indian manufacturers are now discussing Industry 4.0 integration parameters and machine learning capabilities, not merely basic automation. We received interests from across verticals like defence & aerospace, IT/IOT, Healthcare, Automotive. Semiconductor, bare PCBs, Industrial and Consumer segments.

Buyer Testimonials

Mr. Gurdeep Singh, General Manager – Strategic Sourcing Group, Samsung India Electronics Pvt Ltd – “This exhibition brilliantly showcased the immense potential for localized electronics component sourcing in India. We were particularly impressed with the focus on nurturing growing Indian manufacturing capabilities and the opportunity to identify several promising new sourcing partners. A truly invaluable experience for anyone in the industry!”

Mr. Sushil Kumar, General Manager – Procurement and Sourcing, Jio Platform Limited. – “What stood out was the access to both established names and emerging startups under one roof. This juxtaposition is invaluable—we were able to benchmark mature solutions against emerging supply chain scenarios and witness India emerging as a key global manufacturing destination.”

Mr. Prakash Palanisamy, DGM – Group Corporate Electronics Sourcing, Spark Minda Group – “We attend shows globally, but the scale and focus here in Bengaluru this year were truly impressive. The international pavilions provided direct access to component suppliers we would typically need to visit multiple regional shows to engage with.”

Beyond the exhibition floor, the 2025 edition integrated a robust schedule of supporting programs designed to foster deeper technical and strategic discussions. These included the India Semiconductor Conclave, focusing on policy and design ecosystems, and the CEO Forum, addressing procurement and MSME component strategies. A strong highlight this year was the eFuture Conference, which brought together experts to discuss emerging technologies and future roadmaps for the electronics industry. Additional sessions like the eMobility Conference, the Innovation Forum, and a Live Podcast Zone further enhanced the event’s value proposition by providing diverse perspectives and real-time insights from technologists and decision-makers.

Industry leaders underscored the event’s significance. Rajoo Goel, Secretary General of ELCINA, remarked, “This edition reflects the growing depth of the Indian electronics industry. India’s electronics sector is no longer merely an assembly hub but a burgeoning ecosystem demonstrating sophisticated capabilities across the value chain. The “substantive and targeted” nature of the discussions indicates a higher level of technical readiness and business acumen among domestic participants, making them increasingly attractive partners for international collaborations that seek specialized expertise beyond basic manufacturing.”

Dr. Reinhard Pfeiffer, CEO of Messe München GmbH, offered a global perspective: “India is no longer an emerging destination—it is becoming a critical node in the global electronics supply chain. India now plays an indispensable role not just in production volumes but also in strategic design, supply chain resilience, and technological innovation. Both of these trade fairs provide a tangible showcase, allowing international stakeholders to directly gauge India’s advancements, fostering confidence and catalysing direct foreign investment and partnerships”

Bhupinder Singh, President IMEA, Messe München and CEO, Messe Muenchen India, concluded, “The 2025 edition of electronica India and productronica India has cemented the industry’s trust in these platforms and their intent to catalyse the next phase of electronics manufacturing in India. The “trust” placed in the platform reflects its proven ability to consistently deliver valuable cross-border interactions, solidifying its role as a premier facilitator for the next, more advanced phase of electronics manufacturing in India, characterized by deeper international integration and technological collaboration.”

Starting 2026, electronica India and productronica India will transition to a bi-annual format taking place both in Greater Noida (April) and Bengaluru (September). This strategic shift aims to provide more frequent market access points and better align with evolving regional business cycles, reflecting the accelerated pace of India’s electronics sector.

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Author: Mr. Saleem Ahmed, Officiating Head, ESSCI

When you hold your smartphone, drive your car, or even switch on your smart TV, there’s an invisible heartbeat inside, semiconductors. These tiny chips power satellites in orbit, fighter jets in the skies, and the AI algorithms reshaping our lives. For years, India has depended on importing these critical components, an Achilles’ heel for a country that aspires to be a global tech leader. But the tide is turning. With billion-dollar investments, government incentives, and, most importantly, a young pool of engineers, India is poised to script a new chapter: becoming a semiconductor innovation powerhouse.

Yet, there’s a catch. Money can build fabs and policy can set direction, but without the right skills, the vision will remain half-written. The future of India’s semiconductor journey will not just be about silicon, it will be about skills.

The Opportunity Before India

The global semiconductor industry is racing towards a trillion-dollar valuation by 2030. India’s own market is expected to touch $64 billion by 2026, nearly three times its 2019 size of $22.7 billion, according to Counterpoint Research and the India Electronics & Semiconductor Association (IESA). At the same time, the Electronics Sector Skills Council of India (ESSCI) projects the industry will employ 1.70 lakh professionals by 2025 and create another 1.03 lakh jobs by 2030. These are not routine jobs, they’re high-paying, future-facing roles that will place young Indians at the cutting edge of global innovation.

India already has an edge: it is home to nearly 20% of the world’s chip design engineers. Leading companies have set up design and R&D centers in Bengaluru, Hyderabad, and Noida. The recent unveiling of a 3nm semiconductor chip designed in India showcased the sheer technical capability of our engineers and the strategic importance of Indian design centers to the global industry.

By August 2025, the Union Cabinet of India had approved a total of ten semiconductor projects under the India Semiconductor Mission (ISM), amounting to cumulative investments of approximately ₹1.6 lakh crore (around $18.2 billion) across six states. These projects cover a range of technologies and partners, including advanced fabs, packaging, and silicon carbide-based compound semiconductors.

Why Skilling is the Decisive Factor

Despite this progress, the semiconductor value chain is highly talent-intensive. The design and IP creation phase, where the most economic value resides, requires deep expertise in VLSI (Very-Large-Scale Integration), electronic design automation (EDA) tools, and system-on-chip (SoC) architecture.

Currently, India produces tens of thousands of electronics graduates every year, but only a fraction are industry-ready. The gap lies in practical exposure, specialized training, and familiarity with real-world tools. For India to move beyond being a service center and emerge as a global innovation leader, a sharper focus on semiconductor design and VLSI roles is essential.

Equally critical is the manufacturing side of semiconductors, which demands not just technical know-how but also safety and operational excellence. Specialized programs such as Industrial Safety for Semiconductor Manufacturing – Hazchem and Electrical Safety in Semiconductor Facilities are vital to prepare a workforce capable of managing the highly sensitive and hazardous environments of fabrication plants. By strengthening both design expertise and manufacturing readiness, India can build a holistic talent pipeline for the semiconductor ecosystem.

Role of ESSCI: Building the Skills Bridge

This is where ESSCI plays a transformative role. Recognizing the talent gap, ESSCI has developed 32 NSQF-aligned qualifications spanning the entire semiconductor ecosystem, from chip design to  advanced packaging, cleanroom operations to safety protocols.

The courses are designed to cater to:

• Engineering graduates looking to specialize,
• Diploma and ITI students preparing to enter the workforce, and
• Professionals seeking to upskill or switch domains.

Some of the most critical roles where demand is already soaring include:

• VLSI Design Engineers – Designing advanced digital and analog circuits at nanoscale.
• Physical Design Engineers – Specializing in floor-planning, power optimization, and timing.
• Verification Engineers – Ensuring chips are error-free before fabrication.
• Analog & Mixed-Signal Designers – Vital for sensors, RF communication, and power management.
• Wafer Processing and Packaging Engineers – Especially relevant as fabs emerge in India.

Each of these roles commands global relevance and premium salaries, but only if the workforce is trained at world-class standards. The full range of programs is available on ESSCI’s website, offering aspirants a structured path to join the semiconductor workforce. Beyond curriculum design, ESSCI collaborates with industry leaders ensuring that Indian talent is benchmarked against international standards.

Why This Matters for Young Engineers

For India’s youth, the semiconductor wave represents more than jobs, it represents a chance to lead global technological change. Whether in AI, electric vehicles, 5G, space technology, or IoT, semiconductors are at the heart of every emerging sector.

A career in this industry offers:

• High-paying roles with global exposure,
• Opportunities to work on frontier technologies, and
• The satisfaction of contributing to national self-reliance and global leadership.

Conclusion:

India’s semiconductor journey has moved from dream to execution. Fabs are being built, policies are in place, and global players are betting big on India. But without a deeply skilled workforce, the dream of becoming a global semiconductor hub risks falling short.

The responsibility now lies with all stakeholders, universities, industry, government, and skill councils like ESSCI, to align efforts and ensure our engineers are not just employable, but world-class innovators.

For young Indians, the message is simple: this is your moment. Equip yourself with the right skills, embrace the semiconductor revolution, and help India design not just chips, but its future.

Because if we skill right, India won’t just participate in semiconductor innovation, it will lead it

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