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Decision Tree Learning’s architecture is a tree-like, hierarchical structure employed in both classification and regression in supervised machine learning. It starts with a root node, which is the complete dataset and the starting point of the first split according to a chosen feature. From there, the tree splits into internal decision nodes, where each of them is a test on an attribute, and branches, which represent the results of those tests. The algorithm repeats recursively, splitting the data into subsets until reaching leaf nodes, where the terminal output is represented as either a class label or a numeric value.

Such an architecture is constructed based on algorithms such as CART (Classification and Regression Trees), which select the optimal splits based on evaluation of criteria such as Gini impurity or entropy. The aim is to produce a model imitating human decision-making by posing a series of questions that progressively give more particular conclusions. The ease of interpretability and simplicity of this organization make decision trees widely used in predictive analytics and data mining.

Types of Decision Tree Learning:

1. Classification Tree

A Classification Tree is created to solve problems where the output variable is a category, i.e., it is a member of a particular class or category. The tree divides the data based on feature values that can best distinguish the categories. For each node, the algorithm selects the feature that gives the maximum information gain or decreases Gini impurity most. This goes on until the data has been separated into pure subsets, or leaf nodes, which are the final class prediction. For instance, it can distinguish between emails and non-spams.

2. Regression Tree

A Regression Tree is employed when the target variable is continuous, i.e., it has numerical values. Rather than dividing data into categories, it estimates a numeric value by averaging the values in each leaf node. The tree splits data according to features that reduce the variance or mean squared error in the target variable. Each split is designed to produce subsets as homogeneous as possible based on the numerical output. For example: Predicting house prices, forecasting sales.

Decision Tree Learning Diagram:

The figure shows the decision tree learning architecture, a supervised learning machine model that applies to both classification and regression learning. At the apex is the root node, which symbolizes the entire data set and makes the first decision based on a chosen feature. It divides into internal nodes, each symbolizing a point of decision which further divides the data along specific feature values. These internal nodes subsequently branch out to leaf nodes that give the terminal output either a class label for a classification tree or a numerical value for a regression tree. The left half of the diagram illustrates a classification tree where the decisions end up in discrete categories, and the right half illustrates a regression tree where the outputs are continuous values. The framework is binary and symmetrical, highlighting the way data recursively splits in order to make a predictive judgment. The graphical framework serves to demystify how decision trees work through the gradual elimination of possibilities based on feature divisions.

Conclusion:

Decision trees are not only model they’re reasoning frameworks. Their readability, interpretableness, and flexibility make them a starting point for data science, particularly when understanding and actionable results are paramount. From classifying emails to forecasting real estate values, decision trees provide a step-by-step, logical process to comprehend the data.

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Designed for Automotive, Energy, and Industrial Applications, AEC-Q200 Qualified Device Withstands Grade III THB Testing

Vishay Intertechnology, Inc. introduced a new AEC-Q200 qualified DC-Link metallized polypropylene film capacitor designed for the harsh conditions of automotive, energy, and industrial applications. Offering high temperature operation up to +125 °C, the Vishay Roederstein MKP1848e delivers ripple current up to 44.5 A and withstands temperature humidity bias (THB) in accordance with Grade III of IEC60384-16 ed.3 – 60 °C / 93 % R.H for 1344 hours at rated voltage.

With its high temperature operation and resistance to high humidity, the Automotive Grade capacitor released, is ideal for automotive power conversion applications such as on-board chargers (OBC), power trains, HVAC systems, e-compressors, and DC/DC converters. This next-generation DC-Link capacitor also addresses the stringent needs for energy and industrial power conversion applications such as fast chargers, solar inverters, rectifiers for hydrogen electrolyzers, battery storage systems, motor drives, and UPS.

The MKP1848e offers rated capacitance from 1 µF to 140 µF and low ESR down to 1.0 mΩ, in rated voltages from 500 VDC to 1300 VDC. The devices provide 25 % higher ripple current density than previous-generation solutions with the same volume, while its compact footprint and pitch options down to 22.5 mm enable volume reductions up to 40 % and 15 %, respectively, at 500 VDC and 900 VDC.

To meet the standard high voltage levels of electric (EV) and plug-in hybrid electric vehicles (PHEV), the MKP1848e withstands operating voltages from 250 VDC to 800 VDC at +125 °C for a limited time. It also features high thermal shock capabilities — withstanding 1000 temperature cycles from -40 °C to +125 °C, with a 30-minute dwell time for each temperature extreme.

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In the backdrop of Semicon India 2025, Kaynes Semicon announces a strategic partnership with Emeron’s NI Semiconductor Test Systems (STS). Under the strategic partnership, Kaynes will deploy Emerson’s NI STS as the preferred platform across its expanding semiconductor test facilities. 

“We have partnered in the sense that we have invested in those testers, and those would be a part of our ecosystem that we build,” says Mr Raghu Panicker, CEO of Kaynes Semicon Private Limited, in an exclusive conversation with ELE Times. “They have already given us their best possible prices for the testers, and we will deploy them in the products that we will assemble and test in Sanand, Gujarat,” he adds. 

Scope of Work

The collaboration will unify test infrastructure across Kaynes’ analog, mixed-signal, RF, power, and MEMS devices—enhancing production speed, ensuring test flexibility, and shortening time-to-market. This move reinforces Emerson’s vision of establishing itself as a trusted Test-as-a-Service partner for the semiconductor industry.

Emergence of Partnerships 

Underlining the need for partnerships as India strives to achieve its semiconductor ambitions, Shitendra Bhattacharya, Country Head and Director, India, Emerson Test and Measurement Buseiness Group says, “ The great value add that we were able to offer and where we see a synergy is the fact that our hardware and software capabilities have come together in modular, flexible, and scalable system” in an exclusive conversation with ELE Times at Semicon India 2025. 

Adding to the business aspect of securing investments, he says, “NI Testers are the most preferred because of the modularity, flexibility, and scalability. These platforms can evolve into different kinds of chips that they will be testing in the future.” 

About the systems 

The NI STS is a PXI-based test solution offering compact form factor, reconfigurable architecture, and software integration through LabVIEW and TestStand, enabling reuse of instruments and multi-site execution. This helps manufacturers like Kaynes to reduce equipment redundancy, streamline workflow, and respond quickly to changing test requirements.

The partnership is supported by Emerson’s strong India presence, including field engineers, application support, and training resources, ensuring seamless implementation and long-term success for Kaynes’ test operations.

As India ramps up semiconductor manufacturing, Emerson’s NI test platforms are well-positioned to support emerging OSATs and fabs with high-speed, mixed-signal testing. With up to 10x faster test speeds, these systems help reduce capital costs and enable scalable, efficient production—making them ideal for the country’s growing semiconductor ecosystem.

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One of the most intriguing areas of machine learning is reinforcement learning (RL), in which agents interact with their surroundings and acquire the best behaviors through trial and error. RL is perfect for resolving complicated, real-world issues because, in contrast to classical supervised learning, it flourishes in dynamic, uncertain environments. Reinforcement learning is reshaping how machines make decisions, driving innovation in areas such as autonomous vehicles and tailored healthcare solutions. The top 10 notable applications that highlight the strength and adaptability of reinforcement learning will be explored in this article.

1. Autonomous Vehicles

RL empowers autonomous vehicles to make intelligent decisions in real time, enabling them to navigate complex and ever-changing environments—such as congested traffic or unpredictable road conditions with greater precision and adaptability.

2. Predictive Maintenance

With reinforcement learning, predictive maintenance could figure out when a machine is most likely to break down, to get it fixed bait time. With that, the RL agents comprehend when equipment failure might occur by learning from past reports and further optimizes maintenance scheduling to reduce downtime and save repair costs.

3. Personalized Recommendations

Reinforcement learning is employed by streaming platforms such as Netflix, and e-commerce giants such as Amazon, to customize recommendations, adapting to the evolving preferences of a user, and learning which content or products an individual is most likely to engage with.

4. Healthcare Treatment Planning

RL is revolutionizing personalized medicine to assist clinicians in determining the best therapeutic strategy. It can also be used for radiation therapy, drug dose optimization, and robotic-assisted surgeries to achieve better outcomes at lower risks.

5. Energy Management in Grids

Reinforcement learning(RL) helps optimize energy consumption in smart buildings and grids. By learning patterns of usage and environmental conditions, the systems adjust heating, cooling, and lighting to avoid wastage. Such measures reduce costs.

6. Supply Chain and Inventory Optimization

RL-based systems help retailers and logistics companies maintain inventory levels, forecast demand, and optimize delivery routes, lowering operational costs while increasing levels of customer satisfaction.

7. Robotics and Automation

In robotics, RL allows machines to acquire the skills required to perform complex tasks such as walking, grasping, and assembling objects. Manufacturing, space, and domestic robots rely on these types of skills.

8. Financial Trading and Portfolio Management

RL systems allow creation of trading and portfolio management strategies adapted to the fluctuations of markets. They may improve risk management, increase returns, and support decision-making in volatile environments.

9. Drone and Aerospace Navigation

With reinforcement learning, it is possible for drones and space vehicles to autonomously plan routing, collision avoidance, and adaptiveness to environmental changes. This feature is highly potential in scenarios where human intervention is limited or impossible.

10. Natural Language Processing (NLP)

In NLP, the chatbot and virtual assistant are fine-tuned by reinforcement learning methods to produce a more coherent and context-aware response. It is also applied in such areas as training translation, summarization, and sentiment analysis models.

Conclusion:

Reinforcement Learning is more than just a theoretical concept it’s a transformative force across industries. Its ability to learn from interaction and adapt to change makes it uniquely suited for solving problems that traditional algorithms struggle with. As reinforcement learning (RL) continues to advance, it is expected to unlock increasingly ground-breaking applications that redefine the capabilities of machines. Whether one is a researcher, developer, or simply an intrigued observer, RL remains a dynamic and promising field that merits close attention and exploration.

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In the fast-paced world of digital transformation, Automatic Identification and Data Capture (AIDC) has moved beyond just scanning barcodes it is now driving intelligent business outcomes powered by AI, IoT, 5G, and cloud. At the forefront of this transformation is Mr. Chakravarthy Balaji, Chief Business Officer and Vice President Products & Solutions Group (PSG Business) at TVS Electronics (TVSE).

With nearly two decades of leadership at TVSE, Mr. Balaji has played a pivotal role in reshaping the company’s growth trajectory from finance operations to leading large-scale product innovations.

In this exclusive interview with ELE Times, Mr. Balaji shares insights on how AIDC is evolving with next-gen technologies, the role of cloud-native analytics, and how TVS Electronics is positioning itself to lead the next wave of Industry 4.0 adoption in India. Excerpts:

ELE Times: How is Advanced AIDC evolving with AI, IoT, and Industry 4.0?

C. Balaji: Advanced AIDC is shifting from simple data capture to intelligent data interpretation. With AI, IoT, and Industry 4.0, it now enables predictive insights, real-time visibility, and autonomous decision-making across industries.

ELE Times: What role do cloud-native integration and real-time analytics play in driving digital transformation through AIDC?

C. Balaji: Cloud-native AIDC ensures scalability and agility, while real-time analytics converts raw data into actionable insights. Together, they drive faster decisions, process transparency, and end-to-end digital transformation.

ELE Times: What makes TVS Electronics’ ‘Make in India’ AIDC solutions stand out technologically?

C. Balaji: Our AIDC solutions are rugged, reliable, and designed for Indian conditions while meeting global standards. With launches like industrial-grade label printers, scanners, fixed scanners, and enterprise mobile computers such as HS65 and T1 Pro, we combine strong R&D, local innovation, and pan-India service support to deliver true “Make in India” excellence.

ELE Times: What role is TVS Electronics playing in leveraging AIDC to drive digital transformation across industries?

C. Balaji: TVS Electronics is enabling enterprises across retail, logistics, manufacturing, and healthcare with end-to-end AIDC solutions. We act as a solutions partner, aligning technology with business outcomes and industry digital roadmaps.

ELE Times: Which emerging technologies (AI, IoT, 5G, cloud) are most critical for the future of AIDC-led transformation?

C. Balaji: AI, IoT, 5G, and cloud are converging to redefine AIDC. Together, they transform AIDC from a data enabler into a decision enabler, powering the next wave of digital enterprises.

ELE Times: How is TVS Electronics preparing its products and services to address the next wave of digital transformation needs?

C. Balaji: We are expanding our portfolio with industrial-grade label printers, advanced scanners, fixed-position devices, and mobility solutions like HS65 and T1 Pro. Alongside, we are building partnerships in AI, IoT, and cloud to deliver future-ready, scalable, and customer-centric solutions for Industry 4.0.

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Distribution Partnership to Expand Presence Across APAC

Lotus Microsystems ApS, a power management solutions company, and EDOM Technology, one of the Top 10 Global Distributors, jointly announced the signing of a strategic distribution agreement for the Asia-Pacific region.

This collaboration combines Lotus Microsystems’ innovative power management solutions with EDOM Technology’s extensive distribution network, strong field application engineering (FAE) force, and deep market expertise. The partnership is designed to accelerate customer adoption, deliver superior technical support, and strengthen the presence of both companies across the fast-growing APAC markets.

Power and thermal management are crucial aspects of electronic design, especially in the rapidly developing computing, networking, and IoT markets. Effective thermal management ensures that devices operate within a safe temperature range, optimizing performance and extending their operational life. Lotus Microsystems’ work on high-efficiency power modules supports more sustainable computing by reducing energy losses and improving overall power usage effectiveness.

“This partnership with Lotus Microsystems allows us to bring differentiated and forward-looking solutions to our customers in the APAC region. We see great potential in Lotus Microsystems’ technology and are confident it will contribute to the success of our ecosystem.”
— Jeffrey Yu [CEO of EDOM Technology]

“We are delighted to partner with EDOM Technology, a recognized leader in distribution across Asia. This agreement marks an important step in our global expansion, enabling Lotus Microsystems to better serve customers in key APAC markets with the strong support and capabilities that EDOM provides.”
— Hans Hasselby-Andersen [CEO of Lotus Microsystems]

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Tata Electronics Private Limited has signed a strategic Memorandum of Understanding (MoU) with Merck, a global leader in science and technology, to accelerate the development of India’s semiconductor ecosystem. The agreement, finalized, underscores a joint commitment to building robust capabilities in materials, fabrication, and supply chain infrastructure.

Under the partnership, Merck will prepare a full suite of advanced solutions for Tata Electronics, including high-purity electronic materials, advanced gas and chemical delivery systems, and turnkey fabrication infrastructure services. Merck’s AI-enhanced Material Intelligence solutions will also aid operations at Tata’s Semiconductor Fabrication Plant in Dholera, Gujarat.

The partnership encompasses more than just the transfer of technology. Merck will provide guidance on safety and production excellence practices and grant access to Athinia, a secure data analytics platform that enables collaboration at scale. The contract also foresees the establishment of local warehouses, the development of raw material supply chain, and talent development programs, all aimed at bolstering India’s position in the semiconductor sector in the world.

Tata Electronics has promised to invest ₹91,000 crore ($11 billion) in creating the Dholera semiconductor fabrication plant, the first of its kind in India. Once operational, the fab will manufacture chips for applications ranging from automotive and mobile devices to artificial intelligence and advanced computing, catering to both domestic and international markets.

This partnership is viewed as a major step in furthering the goals of the India Semiconductor Mission, establishing Merck and Tata Electronics as important figures in determining the future of high-tech production in the nation.

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The Uttar Pradesh government has introduced a draft policy aimed at strengthening electronics and smartphone manufacturing in the state, with a particular focus on the Noida region. The initiative is part of the state’s broader goal of becoming a $1 trillion economy by 2030.

The draft policy titled “UP Electronics Component Manufacturing Policy 2025” has a goal of providing an ecosystem to nurture domestic and international investors. A variety of incentives, such as capital investment subsidies, stamp and electricity duty waivers, and participation interest grants are proposed to gain more participants.

The state’s IT and electronics department confirmed that the policy was approved by the cabinet in September 2025 and has been made effective retrospectively from April 1, 2025.

The policy aims to achieve $50 billion worth of electronics production within the next five years. Electronics production from U.P. is expected to grow, attracting serious investment, creating massive employment, and cementing the state’s position as a major player in India’s U.P. electronics manufacturing is expected to grow multi-fold within that period.

With Noida as a confirmed centre for electronics and smartphone production, the policy is expected to enhance the state’s role in global supply chains supporting the greater vision of India as a hub for electronics manufacturing.

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Prime Minister Narendra Modi inaugurated Semicon India 2025, positioning India as a rising powerhouse in the global semiconductor industry. Addressing the summit, he said the world now looks to India not only as a trusted partner but as a future leader in chip innovation.

“Oil has been referred to as black gold in the semiconductor industry, but chips are the digital diamonds,” Modi said, highlighting India’s determination to become a full-stack semiconductor nation. Even though we started our trip later than others, we are now unstoppable. The world’s largest revolution will soon be made possible by India’s smallest chip.

Under the Atmanirbhar Bharat vision, the Prime Minister underlined that India’s efforts go beyond chip production and instead concentrate on creating a comprehensive semiconductor ecosystem that boosts competitiveness and self-reliance.

He further elaborated on the Indian semiconductor plan by connecting the dots with India’s stronger economic output. “GDP figures released for the first quarter indicate that India’s GDP is growing at a remarkable 7.8 percent. The growth is seen in every sector of the economy,” he said, putting semiconductor development into the picture of the national economy.

The summit came after Modi’s trip to Japan, where he visited Tokyo Electron Miyagi Ltd., a notable company in semiconductor technology. He explained the complementary relationship between Japan’s advanced technology and India’s nascent semiconductor manufacturing ecosystem and implied that there is more collaboration from other countries to come.

India’s semiconductor market, estimated to be worth between $45 and $50 billion in FY2024–2025, is expected to more than double to $100–110 billion by 2030, according to industry projections presented at the event. Together with international collaborations and regulatory backing, this quick growth is anticipated to solidify India’s position as one of the world’s most important chip-making destinations.

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In the heart of India’s rapidly transforming digital economy, a silent revolution is underway women are stepping into the circuits and chips of the electronics industry, carving out spaces in labs, production floors, design centers, and boardrooms. Once considered a male-dominated field, the Indian electronics sector is now increasingly recognizing the power of diversity, and women are playing a key role in this evolution.

From the factory lines in Noida to innovation hubs in Bengaluru, women are taking up the soldering iron, the oscilloscope, and the executive chair. And at the heart of this transformation is the Electronics Sector Skills Council of India (ESSCI)—a catalyst for empowering women through targeted skilling and industry-aligned training.

The Expanding Electronics Landscape

India’s electronics industry is expected to surpass USD 300 billion by 2026, fuelled by global shifts in supply chains, robust government incentives like the Production Linked Incentive (PLI) scheme, and rising domestic consumption of electronic goods. As India moves towards becoming a global hub for electronics manufacturing and design, the demand for a skilled, innovative, and diverse workforce is growing exponentially.

This surge brings with it immense career opportunities for women, especially in:

• Electronics Manufacturing Services (EMS)
• Semiconductor design and embedded systems
• Mobile and consumer electronics repair
• PCB assembly and quality control
• IoT, Robotics, and Automation
• Solar electronics and green energy solutions

The industry’s demand for precision, discipline, and focus makes women particularly well-suited for many of these roles. However, to fully harness this potential, skilling and upskilling are non-negotiable—and that’s where ESSCI plays a pivotal role.

ESSCI: The Enabler Behind the Change

Established under the Ministry of Skill Development and Entrepreneurship (MSDE), ESSCI is the nodal body dedicated to creating a skilled ecosystem for the electronics sector. With over 75 job roles developed and aligned to National Skill Qualification Framework (NSQF), ESSCI has been instrumental in mainstreaming women into electronics-related job roles.

Key Initiatives Include:

• Women-Centric Skilling Programs for roles like LED assembly, mobile repair, solar installations, and PCB soldering.
• Industry-Academia Partnerships to ensure real-world exposure and better placement outcomes.
• National Apprenticeship Promotion Scheme (NAPS) facilitation to integrate women into mainstream apprenticeships.
• Train-the-Trainer Models to build a strong base of female instructors, creating ripple effects in communities.

How to Get Started

1. Education: Pursue a B.Tech/B.E. in Electronics and Communication Engineering, Electrical Engineering, or related fields from private institutions. Specialized courses in VLSI, IoT, or embedded systems enhance employability.
2. Certifications: Enroll in ESSCI courses for industry-recognized certifications in semiconductor design, IoT, and AI.

Career Paths Open to Women

Whether a woman is a school dropout, an ITI student, or an engineering graduate, the electronics sector has space for everyone:

1. Skilled Technicians and Operators

Women are increasingly hired in electronics factories for their dexterity, precision, and focus, particularly in roles like soldering, assembling, testing, and quality control for products like smartphones, consumer durables, and electric vehicles (EVs). For example, Tata Motors employs 1,500 women in its SUV production line, and MG Motor India has 37% women on its shop floor.

Women with short-term skill training can begin careers in:

• Electronic assembly
• PCB soldering
• Component testing
• Quality inspection

These roles are in high demand in electronics manufacturing clusters like Sriperumbudur, Noida, and Pune.

2. Mid-Level Technical Jobs

Diploma holders and trained candidates can explore:

• Service and repair of smartphones, TVs, and consumer electronics
• Solar system installation and maintenance
• EV charging station technicians
• Automation and IoT device installation

3. Engineering and R&D Careers

Women are excelling in chip design, verification, and testing. The semiconductor industry is projected to grow significantly, with women’s participation expected to rise from 24–28% in 2020 to over 30% by 2027. Roles include VLSI design engineer and semiconductor manufacturing engineer. For B.Tech or M.Tech graduates in ECE or related fields, opportunities lie in:

• VLSI and embedded systems
• Hardware design and validation
• Product testing and compliance
• Robotics and sensor integration

With remote work and flexible hours becoming more acceptable, women engineers can balance family responsibilities and professional growth effectively.

4. Entrepreneurship

Skilled women are also turning into job creators by starting:

• LED bulb manufacturing units
• Repair centers for electronics and white goods
• Retail of components and accessories
• Local e-waste collection and recycling businesses

ESSCI supports such ventures by linking women to funding agencies, mentoring, and digital platforms.

Industry Trends Supporting Women

• Growth of the Electronics Sector: India’s electronics industry is projected to grow significantly, with the semiconductor market alone expected to reach $100–110 billion by 2030, driven by technologies like AI, IoT, 5G, and EVs. This creates a high demand for skilled professionals, including women.
• Gender Diversity Initiatives: Companies like Micron (28% women workforce) and NXP (24% women workforce) are fostering inclusive environments with flexible work policies, maternity benefits, and return-ship programs for women re-entering the workforce.
• Government Support:
  • Science and Technology for Women Program promotes women’s participation in STEM through research and skill development.
  • Skill India Initiatives provide training in VLSI, AI, and IoT, targeting women to bridge the skill gap.
  • The 2017 Maternity Bill and policies addressing workplace safety support women’s retention in the workforce.

High-Demand Roles and Salaries

• VLSI Design Engineer: ₹5–10 LPA (entry-level), ₹15–20 LPA (senior).
• Embedded Systems Engineer: ₹5–8 LPA (entry-level), ₹10–15 LPA (mid-level).
• PCB Design Engineer: ₹4–7 LPA (fresher), up to ₹12 LPA (experienced).
• Semiconductor Manufacturing Engineer: ₹6–10 LPA (entry-level), ₹15 LPA+ (senior).

Conclusion: 

The journey for women in electronics has just begun, and the signal is strong: India’s electronics industry needs women—not just as workers, but as leaders, innovators, and entrepreneurs. With the right mix of policy support, industry collaboration, and targeted skilling initiatives like those from ESSCI, the future circuit boards of India will not only carry current—they’ll carry the hopes of empowered women everywhere.

The post Career Opportunities for Women in India’s Electronics Industry appeared first on ELE Times.

Kaynes Semicon Private Limited, a pioneering Indian semiconductor manufacturer and Infineon, a global leader in semiconductor solutions, has signed a Memorandum of Understanding (MoU) to explore strategic collaboration opportunities in India’s fast- growing semiconductor market.

Strengthening India’s Semiconductor Supply Chain

This collaboration will add a significant milestone with the launch of the first Kaynes Semicon MEMs Microphone, featuring Infineon’s reliable and market proven bare die, a breakthrough in domestic semiconductor module manufacturing. This “Made in India” MEMs Microphone will target for especially TWS earbuds, positioning Kaynes Semicon at the forefront of next generation wearable tech.

Additionally, Infineon will supply high-performance power solution bare die wafers to Kaynes Semicon, which will package them into discrete and module semiconductor products tailored for Indian customers.

By combining Infineon’s leadership with Kaynes Semicon’s advanced semiconductor packaging expertise, the two companies aim to strengthen India’s domestic reach and its global supply chain position. This collaboration will ensure a cost-optimized, locally integrated supply chain that delivers high-performance, reliable, and energy-efficient solutions with significantly reduced lead times for customers.

Driving Innovation Across Key Industries

By working together, Infineon and Kaynes Semicon will address critical semiconductor needs across various sectors, including:

• Energy Semiconductors & Renewable Solutions – Delivering high-efficiency technologies for solar, wind, and energy management applications.
• Industrial & Consumer Applications – Enhancing energy efficiency and performance in smart appliances and manufacturing processes.

With the Indian government prioritizing semiconductor self- reliance, this collaboration supports India’s goal of strengthening local production and reducing import dependency. It also lays the foundation for future innovation and deeper engagement in advanced semiconductor technologies, catering to India’s evolving needs in next-generation electronics.

“Infineon’s industry-leading solutions are known for its high performance, efficiency, and reliability across various applications, including automotive, consumer, industrial, renewable energy and data centers. By bringing together our know-how in semiconductors, with the semiconductor packaging and supply chain expertise of Kaynes Semicon, we are confident this partnership will drive India’s high-tech manufacturing push to greater heights. Congratulations to Kaynes Semicon on the opening of their new Gujarat plant, and we look forward to closer collaboration in the future,” said CS Chua, President and Managing Director, Infineon Technologies Asia Pacific.

“The launch of our first ‘Made in India’ MEMs Microphone, powered by Infineon’s technology, is a milestone moment for the Indian semiconductor industry. We are proud to be enabling next-gen innovations across wearable tech, renewables, and industrial sectors with a trusted global leader.” said Mr. Raghu Panicker, CEO, Kaynes Semicon.

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Delta, a global leader in power management and smart green solutions, unveiled a comprehensive portfolio of next-generation innovations at SEMICON India 2025, inaugurated by the Hon’ble Prime Minister of India, Shri Narendra Modi. The showcase features Delta’s Collaborative Robot, the DIATwin Virtual Machine Development Platform, advanced Smart Screwdriving System and Semiconductor Assembly Solutions, and an integrated Smart Manufacturing Architecture. Delta also demonstrated its Smart Green Facility Monitoring & Control Systems and Energy Management Solutions, along with SEMI E187 cybersecurity certification, reinforcing its commitment to advancing India’s semiconductor ecosystem with precision, resilience, and sustainability.

Speaking on India’s semiconductor journey, the Hon’ble Prime Minister said,“Semiconductor factories are coming up in India, and the country will see its first domestically made chip in the market by the end of 2025. Work is also progressing rapidly on developing a ‘Made in India’ 6G network.”

Aligning with this vision, Benjamin Lin, President, Delta Electronics India, said, “India is at the cusp of a semiconductor and electronics revolution, and Delta is proud to contribute to this transformation with future-ready technologies. By combining our deep global expertise with localized innovation, we aim to empower manufacturers with reliable, secure, and intelligent solutions that strengthen competitiveness and create long-term value for India’s high-tech ecosystem. Our efforts are deeply aligned with the Government’s Semiconductor Mission and Make in India initiative.”

Delta’s Collaborative Robot boasts payloads from 6 to30 kg, reach ranges from 800–1,800 mm, and IP66-rated protection. Equipped with Reflex Safety for instant stoppage on contact and the AI Cognitive Module kit for intuitive interaction via speech, gesture, and 3D object recognition.  In addition, the DIATwin Virtual Machine Development Platform shortens new product development by 20%, linking virtual production lines with real data to enable high-fidelity simulation and improved first-pass yield.

Niranjan Nayak, Managing Director, Delta Electronics India, added, “At Delta, we believe India’s journey to becoming a global semiconductor powerhouse will be driven by a strong digital and sustainable backbone. Through investments in collaborative robotics, digital twins, and green technologies, we are ensuring that India’s manufacturing ecosystem is not only competitive but also resilient and sustainable. Delta’s vision is to stand alongside India as it accelerates toward this milestone.”

Highlights of Delta’s booth at SEMICON India 2025 include:

• The showcase includes a Silicon Die Handling Solution for heterogeneous integration, a high-speed wafer feeder, and the High-Speed Die Pick-and-Place Solution powered by CODESYS controllers, enabling high-precision semiconductor assembly.
• Smart Screwdriving System – Torque up to 7.5 N·m, dual-tool capability (one controller managing two screwdrivers), and storage of 200,000 tightening results, ensuring unmatched assembly accuracy across automotive, aerospace, electronics, and medical sectors.
• Smart Manufacturing Architecture – Integrates OT and IT through DIASECS Semiconductor Equipment Standard Communication and Control Application Software), DIAEAP+ Equipment Automation Program, DIASPC Statistical Process Control, and DIAWMS Warehouse Management System, enabling predictive maintenance, process optimization, and seamless factory digitalization.
• Smart Green Facility Monitoring & Control Systems and Energy Management Solutions – Enable enterprises to optimize operations, reduce energy costs, and embed sustainability into production systems.

Dr Sanjeev Srivastava, Business Head- Industrial Automation SBP, Delta Electronics India, said, “India’s Semiconductor Mission and Make in India program are bold and visionary initiatives, and achieving them requires robust digital and automation backbones. With Digital Twin, Smart Manufacturing, and precision robotics, Delta is helping manufacturers move from concept to execution faster, safer, and more efficiently—positioning India as a global hub for high-tech manufacturing.”

Alongside its hardware innovations, Delta also showcased its software portfolio, including DIASECS Semiconductor Equipment Standard Communication and Control Application Software for standardized equipment communication, DIAWMS Warehouse Management System, DIAEAP+ Equipment Automation Program for efficient data collection, and DIASPC Statistical Process Control. Together, these platforms enable seamless integration, higher operational efficiency, and quality assurance while adhering to global semiconductor industry standards.

Anil Chaudhry, Head of Robotics & IA Solutions, Delta Electronics India, added, “Our technologies are not just about automation they are about resilience, agility, and long-term growth. By bridging IT and OT, we help companies break down silos, predict challenges, and adapt seamlessly to market volatility. This is the future of intelligent manufacturing, and we are proud to bring it to India under the vision of the Semiconductor Mission and Make in India.”

Delta is also setting a new benchmark in semiconductor equipment cybersecurity by adopting the SEMI E187 certification, ensuring greater reliability, resilience, and trust for customers operating critical manufacturing platforms.

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Decision tree algorithms continue to be one of the most reliable methods for converting unprocessed data into useful insights as artificial intelligence transforms various industries. With its quickly expanding tech sector, India is home to a number of businesses that are highly skilled at developing and implementing decision tree-based solutions in a variety of sectors, including banking, healthcare, retail, telecommunications, and agriculture. In order to provide highly accurate, scalable AI solutions, these companies use decision trees not only for classification and regression tasks but also incorporate them into sophisticated ensemble techniques like Random Forests and Gradient Boosted Trees. This article will examine the top 10 companies that are at the forefront of machine learning innovation powered by decision trees.

1. TCS

TCS uses decision tree models in Ignio in IT automation, including anomaly detection and predictive analytics. Its solutions span banking, manufacturing, and retail, assisting organizations in making reliable scalable advanced data-backed decisions.

2. Infosys

With its proprietary Nia platform, Infosys is able to use decision tree algorithms for customer analytics, supply chain optimization, and fraud detection. This company is also known for combining decision trees with deep learning to improve both the interpretability and accuracy of the system.

3. Entropik Tech

Entropik uses decision tree algorithms in emotion AI to classify user responses and predict behaviour. Their platforms combine decision trees with computer vision and EEG data to help brands decode consumer sentiment and improve engagement strategies.

4. Wipro

With the help of Wipro’s HOLMES AI and Automation platform, decision tree models can be used for cognitive automation, IT service management, and predictive maintenance. Wipro also combines decision trees with reinforcement learning and NLP to provide smart solutions in the healthcare, energy, and telecommunications industries.

5. Artivatic.ai

Artivatic.ai uses decision trees for its underwriting, fraud detection, and claims automation in insurance technology. Using them along with neural networks, Artivatic.ai’s platform provides explainable AI in health and life insurance, where decision trees are commonly used.

6. Fractal Analytics

Fractal uses algorithms based on decision trees in its Qure.ai and Cuddle.ai platforms, which specialize in healthcare diagnostics and business intelligence. By integrating decision trees with deep learning, they strive to elevate the interpretability and accuracy of their solutions in critical settings.

7. HCLTech

HCLTech’s DRYiCE suite uses decision tree algorithms to improve business functions, pinpoint anomalies, and improve workflows. Their models are applied and further developed with other methods in financial services, the automotive industry, and life sciences to improve functionality and scalability.

8. Zensar Technologies

Zensar uses decision tree algorithms in the reshaping of customer experiences, predictive analytics, and in the digital supply chain. Their AI-powered platforms deliver retail and logistics business intelligence and leverage decision trees to provide real-time analytics for better business decision-making.

9. Mu Sigma

Mu Sigma exploits decision tree techniques in their decision sciences, facilitating risk, churn, and operational optimization analytics for Fortune 500 firms. The company’s unique frameworks integrate decision trees with Bayesian methods, yielding more reliable analyses.

10. Tredence

Tredence creates AI-driven models for retailers by integrating decision trees with demand prediction, inventory management, and customer segmentation. The models function on analytics platforms and can scale on the cloud.

Conclusion:

The use of machine learning models based on decision trees has become pivotal in India’s evolving AI landscape. Numerous organizations, ranging from major IT corporations like TCS, Infosys, and Wipro to niche analytical businesses like Fractal Analytics, Mu Sigma are showcasing the capabilities of decision trees particularly in conjunction with ensemble methods like Random Forests and Gradient Boosted Trees in offering actionable, explainable, and scalable industry solutions.

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Union Electronics and IT Minister Ashwini Vaishnaw has said that India is making rapid strides in the semiconductor sector and is on track to be among the world’s top five chip‑making nations by 2032.

In a recent interaction, Vaishnaw mentioned that SEMICON India 2025 would be an important event to gain global partnerships, attract investments, and showcase India’s growing semiconductor ecosystem. He added, “With policy support and industry collaboration, our aim is to turn India into the semiconductor hub of the world.”

Recalling the chip making vision of the government, Vaishnaw talked about achievements in chip design, advanced packaging, and talent development. Regarding this, he mentioned that the first commercially available semiconductor chip made in India would be released soon.

The India Semiconductor Mission has allocated $10 billion for its first phase. This funding incorporates a plethora of initiatives such as manufacturing incentives, display fabrication units, compound semiconductors, design linked schemes, and research driven collaborations.

An end to end semiconductor ecosystem approach is being adopted encompassing chip design, equipment, materials and manufacturing so that India is fully plugged into the global semiconductor value chain. This approach is expected to lay a strong foundation for sustained industry growth.

Regarding the talent, 270 universities and 70 startups have been provided with advanced semiconductor design tools. Students have already designed 20 chipsets, several of which have been sent for fabrication, showcasing the country’s growing design capabilities.

With six semiconductor production facilities currently authorized or in development nationwide, manufacturing momentum is increasing in the meantime. In order to increase domestic output and lessen dependency on imports, these facilities are expected to be essential.

He emphasised India’s competitive advantage as policy support, engineering talent, and industry collaboration. The country’s electronics exports have already crossed $40 billion, which is an eightfold increase over the last 11 years.

Vaishnaw stressed the Indian Electronics System Design and Manufacturing (ESDM) industry’s strengths because of the semiconductor companies’ policy support and the robust engineering talent base. The ecosystem is getting more robust with several global semiconductor companies starting large R&D and design centres in India.

As India gears up to host SEMICON India 2025, it is expected that the semiconductor industry officials and the policy makers will come up with a roadmap that will expedite the journey of India to become semiconductors self-reliant and also strengthen the role in global supply chain.

By 2032, if present trends continue, India may rank among the world’s top five semiconductor powers, revolutionizing the country’s electronics manufacturing sector and making a substantial contribution to economic growth.

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• The upcoming facility in Gwalior, Madhya Pradesh, will have an annual capacity of producing 105MW of electrolysers, with a roadmap to scale up to 500 MW by 2030, contributing direction to the National Green Hydrogen Mission.
• Supported by ₹157.5 crore Production Linked Incentive (PLI) subsidy, the project stems from a landmark MoU between GH2 Solar and AHES Ltd. It will be backed by GH2 Solar’s UK based partner Rhizome Energy.
• ₹400 crore of total investment, with ₹100 crore allocated in the first phase to set up up a 3 GWh BESS assembly line, and the remaining ₹300 crore to be invested in phases by 2030 to expand the facility.
• The facility is expected to create 300+ direct jobs in the clean energy sector.
• Supported by Invest India and Skill council for Green Jobs to build renewable energy capabilities and train future workforce in line with the Government of India’s Atmanirbhar Bharat Mission.

GH2 Solar Limited, a next generation renewable energy company and one of only five companies in India Government’s PLI scheme for both green hydrogen production and electrolyser manufacturing, announced a major milestone under India’s Green Hydrogen Mission its upcoming state-of-the-art Green Hydrogen Electrolyzer Manufacturing Facility in Gwalior, Madhya Pradesh, in joint venture with South Korea-based Advanced Hydrogen Energy Solutions (AHES) Ltd.

The facility located in Pipersewa, Morena district (Madhya Pradesh), will begin with an annual manufacturing capacity of 105 MW awarded under SECI’s SIGHT program, supported by ₹157.5 crore Production Linked Incentive (PLI) subsidy. The total investment in the project is approximately ₹400 crore, with ₹100 crore allocated in the first phase to set up a 3 GWh BESS assembly line, and the remaining ₹300 crore to be invested in phases by 2030 to expand the facility. GH2 Solar has also outlined plans to expand the electrolyser capacity to 500 MW by 2030, directly contributing to the National Green Hydrogen Mission’s target of producing 5 million tonnes of green hydrogen annually by 2030. The announcement was marked by a Bhoomi Pujan ceremony in Gwalior, graced by Shri Dr. Mohan Yadav Ji, Hon’ble Chief Minister of Madhya Pradesh. The project was formally announced by Mr. Anuraj Jain, CEO and Founder of GH2 solar, alongside Prof. Joong-Hee Lee, CEO of AHES Ltd and Mr. Raj Sharma, Director of Rhizome Energy, UK, both key international partners of GH2 Solar’s green hydrogen journey.

Through the JV with AHES Ltd, GH2 Solar will bring advanced alkaline electrolyzer technology to India, with future expansion into PEM and other generation systems. In addition, GH2 Solar’s partnership with Rhizome Energy (UK) will embed sustainable design principles and advanced engineering practices,  to ensure the facility is competitive, efficient and manufactures tailored solutions as per Indian conditions, strengthening the vision of making India a global hub for green hydrogen.

Speaking on the occasion, Mr. Anurag Jain, Founder and CEO, GH2 Solar, “As India advances towards energy independence and transitions from fossil fuels to green hydrogen, our Electrolyser Manufacturing Facility will play a critical role in this journey. Through  global partnerships, we are bringing cutting-edge decarbonization technologies, while government support enables us to effectively leverage local resources. We are also committed to collaborating with academic institutions and skill development centers to train engineers and technicians, ensuring India has a robust workforce to drive green hydrogen technologies forward. Ultimately, our goal is to build a complete clean energy ecosystem that positions India as a leading producer and exporter of green hydrogen, with the workforce and technology to truly realize the vision of Atmanirbhar Bharat”

Adding to his perspective, Prof. Joong-Hee Lee, CEO of AHES, said, “The future is green, and no nation can achieve it alone. The world must unite in its commitment to sustainable energy. Our joint venture with GH2 Solar, brings this vision closer by producing electrolysers in India for the world. India already has skilled manpower, strong public institutions, and crucial government policy and funding support. We are happy to contribute to this ecosystem and believe our Gwalior facility will be an important step in shaping the world’s green future.”

On the public institution side, the project is supported by Invest India and Skill Council for Green Jobs. The facility’s operations are expected to create over 300 direct jobs in manufacturing, operations and research, along with hundreds of secondary jobs across supply chain, logistics, and renewable energy services. By building renewable energy capabilities and training future workforce, the facility also makes a significant contribution to the Government of India’s Atmanirbhar Bharat Mission.

The project supports the Government of India’s National Green Hydrogen Mission, which targets 5 million metric tonnes of annual green hydrogen production by 2030 and underpins India’s ambition to achieve net zero by 2070. The Gwalior facility is expected to play a crucial role in decarbonizing high-emission sectors such as steel, fertilizers, and refineries, while also creating opportunities for export to Europe and East Asia.

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Decision Tree learning is a widely used method in machine learning and data analysis for making decisions and predictions. It employs a tree-like model of decisions, where each internal node represents a test on a feature, each branch corresponds to an outcome of the test, and each leaf node signifies a final decision or classification. The process begins at the root node, which encompasses the entire dataset, and progressively splits into branches based on feature values, ultimately leading to distinct outcomes. This hierarchical structure allows for intuitive visualization and interpretation of decision-making processes. Decision Trees are incredibly versatile and find applications across a wide range of fields. Highlighted below are the top 10 decision tree learning real-world applications and use cases.

1. Fraud Detection

Identifying and preventing fraudulent transactions is one of the primary use cases of Decision Trees, and they are especially beneficial in banking as well as e-commerce centers. For instance, Decision Trees can flag suspicious transactions such as sudden exorbitant spending or transactions from new locations, which helps enterprises to minimize financial risks and combat security threats.

2. Customer Segmentation

Decision Trees are particularly useful in marketing, where customers can be classified into groups based on age, income, and even purchase and browsing history. This form of segmentation is especially useful for marketing as it helps personalize communication and enhances engagement by ensuring the right message is delivered to the appropriate audience.

3. Medical Diagnosis

Decision trees in the healthcare sector are essential for assisting clinicians in making predictions about the likelihood of a disease for a patient. This is derived from the patient’s symptoms, tests, and previous medical records. The trees’ logic is clear, which gives the doctors a chance to follow each step of reasoning, and this makes the tools invaluable in clinical decision support systems.

4. Recommendation systems

Decision trees are used in recommendation systems, such as on Netflix and Amazon, to suggest items, movies, or services by analyzing user preferences, browsing history, and ratings. These models help personalize the user experience and increase engagement by suggesting items that align with individual tastes.

5. Predictive Maintenance

In the sectors of manufacturing and transportation, decision trees based on sensor data, usage patterns, and equipment operating conditions are used to forecast equipment failure. This provides timely maintenance and improves the chance to provide uninterrupted service.

6. Autonomous Driving Decision Systems

Decision trees are important to the development of autonomous vehicles because they incorporate decision making models in driving systems. With their complex environments, these vehicles have to make safe and efficient decisions while learning the rules of the road, functionality of other vehicles, and traffic control. The vehicles accelerate, brake, and even change lanes based on the output of decision trees.

7. Cybersecurity Threat Detection

The use of decision trees in threat detection provides a more in-depth look into network traffic, different login schemes and their failures, as well as different system behaviors. Their use aids in the prevention of attacks and protection of crucial information.

8. Filtering of Email Spam

In order to classify messages, email providers analyze the words used, the sender’s reputation, and the structure of the message. They classify the messages using decision trees as either spam or legitimate email. Making email spam free and increasing security for the users.

9. Space Agencies and Aerospace Companies

Space and aerospace companies use decision trees in monitoring spacecraft systems and in predicting component failure and assist in mission planning. They help ensure safety and reliability in high-stakes environments.

10. Navigation and GPS Functionality

Decision trees are used by mapping and navigation software to provide the best possible route possibilities while accounting for user preferences, roadwork, and traffic conditions. Decision trees also consider the user’s objectives, whether to minimize travel time, fuel consumption, or increase safety. 

Conclusion:

Decision trees learning have a wide array of uses in data driven decision making, and thus can be considered a very strong and useful methodology. Their unique and flexible structure, ease of understanding and use, and transparency make decision trees very useful from the healthcare sector and the finance sector all the way to public administration and environmental care sectors. Decision trees can be used and are very crucial in the healthcare sector to help make very important and life saving decisions, and businesses also stand to benefit through the use of decision trees in optimizing their strategies. The impact of decision trees is very important and will grow even further as technology advances.

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Prime Minister Narendra Modi and his Japanese counterpart Shigeru Ishiba visited the Tokyo Electron Factory (TEL Miyagi) in Sendai. This visit was significant because it marked a focus of India and Japan’s cooperation in advanced technologies, especially semiconductors. The two leaders also emphasised the importance of this industry by taking the bullet train from Tokyo to Sendai, which is more than 300 km.

During the visit, Modi engaged with TEL executives regarding their position in the global semiconductor ecosystem and future partnerships with India. He emphasized how India’s growing manufacturing ecosystem and Japan’s cutting-edge semiconductor machinery and technology work in tandem.

In his remarks at the India–Japan Economic Forum, Modi highlighted semiconductors, batteries, and robotics as focus areas for Make in India collaborations. Prime Minister Ishiba laid out three goals: building stronger people-to-people ties, fusing technology with green initiatives, and boosting cooperation in high-tech fields, especially semiconductors.

The visit to Sendai came as a follow-up of the bilateral agreements made under the India-Japan Industrial Competitiveness Partnership and the Economic Security Dialogue. Both these agreements cover fields like critical minerals, ICT, pharmaceuticals, and more. An understanding was made to speed up the projects in these fields alongside semiconductors.

Involvement from the private sector is increasing steadily. Japanese firms have entered into around 150 MOUs over the last two years in sectors such as aerospace, automotive, semiconductors, energy, and human resources, as per the Ministry of External Affairs of India. Modi also remarked that the Digital Partnership 2.0, AI collaboration, and work on rare earth minerals will continue to be the focus of partnership.

Modi and Ishiba reiterated their vision of developing strong and trusted supply chains and India and Japan’s roles as critical partners in the framework of global technology security by keeping semiconductors as the focus of this visit.

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Union Minister Ashwini Vaishnaw inaugurated India’s first tempered glass manufacturing facility in Noida, marking a major milestone in the country’s electronics manufacturing ecosystem.

Noida now owns the distinction of having inaugurated India’s first tempered glass manufacturing unit, a step ahead in the electronics manufacturing journey.

The plant built in collaboration US technology giant Corning is owned and operated by Optiemus infracom. The factory will manufacture tempered glass for smartphones and other electronic devices, which is used as a protective layer and is used extensively.

Optiemus has emerged as a key player in India’s electronics manufacturing ecosystem, known for its strategic partnerships and innovation, Minister Vaishnaw described Optiemus, “a new gem in India’s fast-growing electronics manufacturing ecosystem,” and further stated that production of covered glass with Corning’s collaboration is slated to begin before the end of this year.

Investment and Production Capacity:

The Noida facility has been built with an initial investment of ₹70 crore and is, and it is furnished with an annual capacity of 2.5 crore units. In addition to supporting domestic manufacturing, the plant is projected to generate more than 600 direct jobs in the area.

Optiemus has set forth expansion plans of a larger scale. In the second phase of growth, the company aims to significantly increase its capacity to 20 crore units per year for the domestic market as well as for exports.

Phase 2 Expansion: 

For the next phase, the company wishes to open another plant in Noida with an annual capacity of 10 crore units. In addition, a new plant in southern India with a capacity of 15 crore tempered glass units is planned. An additional ₹800 crore is earmarked for this expansion, with the southern plant receiving more than ₹450 crore.

In addition, the company plans to launch its own brand of tempered glass, RhinoTech, in September 2025. Emphasizing domestic manufacturing, a ‘Made in India’ tag will be attached to the product. RhinoTech will have consumer-friendly features. For instance, it will be covered by a one-year warranty with unlimited replacement, which is bound to add value to the product in the market.

While speaking at the event, Minister Vaishnaw focused on the achievements of India’s electronics sector. In the past 11 years, this sector’s production value has increased six times, reaching ₹11.5 lakh crore. Exports have also grown to more than ₹3 lakh crore, and the industry supports 25 million jobs both directly and indirectly across the country.

The inauguration of this factory marks India’s entry into the tempered glass manufacturing industry, which was previously reliant on imports. The impact of this development is the expected improvement of the supply chain for smartphones and other electronic devices, which is in line with the government initiative to make India a global hub for electronics production.

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Reinforcement learning (RL), a subfield of machine learning in which agents learn by interacting with their surroundings, is gaining significant popularity in India’s quickly developing AI ecosystem. RL is being used in a variety of areas, including financial modeling, smart energy grids, and autonomous systems. Indian businesses are using RL to innovate and create scalable solutions that are on par with international standards, rather than merely adopting it. The top 10 reinforcement learning companies in India will be explored in this article:

1. Tata Consultancy Services (TCS)

As the global IT leader, TCS focuses on integrating RL into supply chain optimization, autonomous systems, and intelligent automation. It is AI laboratories work on adaptive algorithms that learn from changing environments in logistics, manufacturing, and operations for better decision making. The company also uses its platform TCS iON to apply RL to the fields of education and skill development, employing gamified and tailored learning to increase motivation and achieve better educational results.

2. Infosys

As led by the Infosys Topaz platform, the AI-first initiative of the company shows faster advances in Reinforcement Learning (RL). The platform’s robotics, enterprise automation, and conversational AI are improved by RL and RLHF (Reinforcement Learning with Human Feedback). The completion and integration of these technologies enable the creation of adaptive, scalable, and self-learning enterprise solutions, such as automated fraud detection systems, predictive analytics, and enhanced customer care.

3. Wipro

Wipro is currently engaging with Reinforcement Learning (RL) to upgrade automation, simulation, and intelligent systems across multiple sectors. The company utilizes RL in industrial automation and flight simulation, employing adaptive learning models to improve control mechanisms and decision-making procedures. Wipro’s investigations also extend to scalable RL methodologies for manufacturing and financial services, which facilitate more intelligent resource allocation and operational forecasting.

4. HCL Technologies

HCL Technologies is continuously refining the applications of Reinforcement Learning (RL) across various focus areas, including cybersecurity, workforce analytics, and education. In workforce analytics, HCLTech uses RL for the customization of learning pathways and the prediction of talent development, enabling companies to match employee evolution with their strategic objectives. Their partnership with Pearson brings even greater value in the education sector, where RL-driven adaptive learning systems customize services to the learners and enhance the mastery of skills.

5. ValueCoders

ValueCoders is an Indian software company specializing in adaptive smart system software development for healthcare, finance, and education sectors. They use computer vision, reinforcement learning, and MLOps to ease decision automation, enhance personalization, and boost system performance over time for their clients.

6. Locus

Locus is a top-class supply chain and logistics company that focuses on streamlining and automating supply chain operations with the use of reinforcement learning (RL). With Locus, businesses can now enhance the planning of delivery routes, scheduling of deliveries, and even the allocation of resources. This allows companies to better control and reduce costs, increase the efficiency of their operations, and better respond to fluctuating demand and traffic conditions.

7. Mad Street Den

Mad Street Den is the only company to blend reinforcement learning and computer vision through its Vue.ai platform to enhance personalized retail experiences. Their adaptive systems are designed to optimize merchandising, styling, and customer engagement on behalf of global fashion and e-commerce brands.

8. Arya.ai

With a deep focus on reinforcement learning and deep neural networks, Arya.ai addresses autonomous decision systems. Their SaaS products with real-time adaptation enabled for finance, insurance, and robotics industries address fraud detection, claims automation, and smart underwriting.

9. Infilect

Infilect uses visual intelligence platforms to implement RL in retail. Their technologies optimize pricing, merchandising, and shelf availability using RL-driven analytics, which helps brands lower stockouts and increase in-store compliance.

10. Flutura Decision Sciences

The major industries of oil and gas, chemicals, and heavy machinery benefit from Flutura Decision Sciences’ artificial intelligence and reinforcement learning approaches to machine learning, which are used to develop their industrial internet of things platform, Cerebra. With Flutura, these industries can improve asset performance, anticipate failures, and minimize downtime. To offer complex system digital twins, Cerebra delivers diagnostics and prognostics, which are supported by physics models, heuristics, and machine learning.

Conclusion:

With smart healthcare, smart agriculture, and smart city systems, autonomous systems powered by reinforcement learning are ready to take off, marking the beginning of the AI revolution. With the development of edge AI and quantum computing, real-time decision-making will be dominated by RL. Due to the culture of innovation, availability of skilled resources, and the country’s bold vision, India has the potential to lead the world in adaptive intelligent systems in the upcoming years.

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High Security Integration, Low Power, and Small Package, Providing Cost-Effective RoT

Nuvoton Technology released the upgraded NuMicro M2354, tailored for applications such as server RoT, smart city, IoT, and smart metering.

NuMicro M2354 is an Arm TrustZone microcontroller based on the Armv8-M architecture and powered by the Arm Cortex-M23 CPU, designed to enhance IoT security. It is suitable for long-term confidentiality requirements and highly sensitive data protection scenarios.

The M2354 operates at frequencies up to 96 MHz, offers a wide operating voltage range of 1.7V to 3.6V, and a broad operating temperature range of -40°C to +105°C. The power consumption is 89.3 μA/MHz in LDO mode and 39.6 μA/MHz in DC-DC mode. The Standby Power-down mode consumes less than 2 µA, and the Deep Power-down mode without VBAT consumes less than 0.1 µA, effectively extending the device’s battery life and meeting the needs of long-term IoT operation.

For Secure FOTA, the M2354 has built-in dual-bank Flash Memory of up to 1024 KB and 256 KB of SRAM. In addition to supporting eXecute-Only-Memory (XOM) to prevent code theft, it also integrates a cryptographic hardware accelerator that supports FIPS PUB 197/180/180-2/180-4 and NIST SP 800-38A, as well as a hardware key store to protect against side-channel and fault injection attacks. In terms of secure boot mechanism, the upgraded M2354 supports the Root of Trust architecture based on DICE, implemented in Mask ROM, and supports ECDSA P-521. This feature automatically generates a unique device identity and establishes a chain of trust during boot, effectively verifying firmware version and preventing firmware rollback and tampering attacks. Furthermore, M2354 is compliant with PSA Level 3 and SESIP Level 3 security certifications, which meet the demands of the EU’s Cyber Resilience Act (CRA).

M2354 supports a wide range of peripherals, including CAN, USB 2.0 full-speed OTG, PWM, UART, SPI/I2S, Quad-SPI, I²C, and RTC.

M2354 also integrates several analog components, including analog comparators, ADC, and DAC.

The package options include LQFP-48, LQFP-64, and LQFP-128. The upgraded M2354 also offers a compact WLCSP49 package. With support of the SPDM (Security Protocol and Data Model) secure communication protocol, the upgraded M2354 is well-suited for Root of Trust applications in server motherboards and daughterboards.

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