AI

“Networked AI: Theory and Applications”

INSAI 2026 will be held on December 5–6, 2026, in Macao, China. In Networked AI, heterogeneous AI agents continuously generate high-quality data through mutual interaction, autonomously optimize and evolve their behaviors in real time, adapt to changing environmental conditions, and maintain system-level stability, safety, and trustworthiness. As the application-layer realisation of Networking Systems of AI (NSAI), Networked AI can significantly reduce AI systems’ dependence on massive centralised datasets and ever-growing computational resources, while continuously improving application-specific intelligence in open and dynamic real-world scenarios. INSAI 2026 aims to bring together researchers and practitioners from artificial intelligence, communication networks, distributed systems, signal processing, control, and related application fields to examine the theoretical foundations, enabling technologies, system architectures, and practical applications of Networked AI. Topics of interest include, but are not limited to: Fundamental Theory of Networked AI Networked AI Systems and Communication Infrastructure Networked AI and Signal Processing Networked AI and Distributed Control Networked AI Applications and Practice Publication All manuscripts will undergo a rigorous peer-review process. Accepted papers will be submitted for indexing in EI Compendex, Scopus, and other databases, and selected outstanding papers will be recommended for publication in SCI-indexed international journals. Important dates: Paper submission deadline: September 10, 2026, 23:59 AoE Notification of acceptance: November 1, 2026 Registration deadline: November 15, 2026 Conference dates: December 5–6, 2026 Submission system: https://cmt3.research.microsoft.com/INSAI2026 Conference website: https://insai2026.ainsai.org Contact: insai@ainsai.org

Applied Materials Tampines Campus in Singapore

Applied Materials expands Singapore manufacturing to support AI chip demand

Applied Materials has expanded its manufacturing and R&D operations in Singapore to support the global build-out of AI infrastructure. The new US$500 million (S$600 million) Tampines Campus more than doubles Applied’s advanced cleanroom capacity in Singapore and strengthens the company’s global manufacturing footprint, which also includes facilities in the United States, Europe, Israel and Taiwan. The new facility, already operating at volume production, is focused on serving chipmakers that are expanding production to meet increasing AI-driven demand. “AI is transforming every industry, creating unprecedented demand for advanced semiconductors,” said Gary Dickerson, President and CEO of Applied Materials. “Our expanded manufacturing operations in Singapore strengthen Applied’s ability to deliver semiconductor manufacturing equipment that chipmakers need to bring next-generation chips to market faster.” The Tampines Campus marks a major milestone in Applied’s Singapore 2030 plan to strengthen the company’s global manufacturing and R&D capabilities, broaden technology ecosystem partnerships and promote local workforce development. The campus features an expansive manufacturing cleanroom and production capacity along with R&D facilities to support global and regional customers. With the expansion, Applied anticipates adding approximately 1,000 new local jobs over the next few years to support industry growth and technology commercialization. “Singapore has been a strategic hub of Applied Materials’ global operations for 35 years, and our expansion here is a testament to the world-class semiconductor ecosystem, infrastructure and talent this country has built,” said KC Ong, Group Vice President of Worldwide Manufacturing at Applied Materials. “Our new AI-enabled, automation-ready facility represents the next era of advanced manufacturing optimized for speed, precision and quality.” Intelligent manufacturing and sustainable operations The Tampines Campus sets a new global benchmark for sustainable, intelligent semiconductor equipment production. The facility deploys Autonomous Mobile Robots, autonomous assembly and testing systems, and AI-assisted quality inspection—deepening integration between manufacturing, R&D and ecosystem partners to accelerate time-to-market for […]

Every click has a cost: Singapore’s push to make digital use more sustainable

As AI and cloud use surge, the city-state explores new ways to cut the rising energy footprint of digital services. By Taejun Kang Your smartphone feels clean – no exhaust pipe, no smokestack. Yet streaming an hour of video uses about 0.037 kWh of electricity, equivalent to running a ceiling fan for about three to four hours. When scaled across billions of global searches, streams and artificial intelligence (AI) interactions each day, the energy demand behind routine digital activity is substantial. “The environmental impact of our digital consumption is far more significant than most people realise,” said Dr Lawrence Wee, director of business and ecosystems at Singapore’s Infocomm Media Development Authority (IMDA). As part of IMDA’s BizTech Group, his team focuses on advancing the country’s digital innovation and sustainability across the tech ecosystem. “We are seeing a digital paradox: the very technologies that offer solutions for climate change are simultaneously driving up energy consumption.” Studies over the past several years have placed the Information and Communications Technology (ICT)’s share of global greenhouse gas emissions between 1.8 and 2.8 per cent, with a more recent analysis estimating it at around 3.4 per cent. Data centres – facilities that house servers and keep the internet, cloud services and digital applications running – are among the most energy-intensive components of this ecosystem because they require continuous power and cooling. Singapore is no exception to this trend. The city-state hosts one of the region’s densest clusters of data centres, with about 1.4 gigawatts (GW) of computing capacity from 70 data centres, which power everything from e-payments to food-delivery apps. By regional standards, this capacity is unusually concentrated. Unlike neighbouring countries such as Indonesia, Malaysia or Thailand, where data centres are spread across vast land areas and multiple power grids, Singapore compresses a similar scale of digital infrastructure into just 734 square kilometres, intensifying pressure on electricity supply, land use and […]

How CTEM, AI, and access control redefine OT security in 2026

By Carlos Buenano, Field CTO for OT, Armis As we step into 2026, AI-driven adversaries, supply chain fragility, and relentless digitisation are forcing Operational Technology (OT) security to mature into a force to be reckoned with. Here’s what 2026 looks like: AI-Powered adversaries demand autonomous defence AI is no longer an abstract threat vector; it’s an operational force multiplier that attackers are leveraging with frightening results. We’re witnessing adversaries use autonomous agents to probe networks, map exposed devices, and launch dynamic exploitation campaigns that run continuously. In 2026, those systems will act autonomously: isolating compromised segments, or enforcing multifactor re-authentication for operators under suspicious conditions. In OT, where minutes can mean millions, automation will be the only meaningful defence. CTEM becomes the operational centre of gravity A few years ago, “CTEM” was just another Gartner acronym. In 2026, it’s the organising principle for any serious OT security program. CTEM represents a shift from periodic vulnerability management to continuous, risk-based exposure assessment and management across hardware, firmware, network paths, and even supply-chain dependencies. But the key difference this year is context. We’re aligning exposures with what actually matters; the physical process, the human safety implications, and the potential operational impact. The cybersecurity landscape in 2026 is clearly set for a strong and necessary integration where vendors leverage the strengths of CTEM to directly inform actionable firewall enforcements, workflows, and reporting. This narrative is driven by the final “Mobilisation” step of the CTEM cycle, which demands that validated, confirmed high-priority exposures leads to an immediate, automated remediation. Specifically for firewalls, this means a CTEM platform will no longer just issue a general alert but will use its deep, risk-based context to trigger a Security Orchestration, Automation, and Response (SOAR) playbook that instantly pushes a micro-segmentation policy or a temporary block rule to […]

AI hype is fueling a bubble in humanoid robotics

Humanoid robot (Source: Canva) Humanoid robotics companies backed by investors face fundamental challenges with cost and reliability that will not be solved any time soon, a report by CB Insights shows. According to investors, VCs especially now should embrace a revenue-first philosophy. Recent venture capital (VC) reports from KPMG and PitchBook confirm that AI remains in the lead, accounting for more than half of all investments this year. Data from CB Insights shows that investors’ attention inside the AI market is shifting toward industrial humanoid robotics. As a result, investors argue the flood of AI capital is pushing robotics toward a speculative zone, with too many startups promising breakthroughs without commercial evidence. Last quarter, industrial humanoid robotics captured 17 deals – the most of any category. AI was still the primary destination for investors, split into several categories, such as coding AI agents and copilots (14 deals), end-to-end software development AI agents (12), and others. Rapid growth of the sector has already sparked fears of a bubble from the Chinese leading economic planning industry, which said that the humanoid robotics industry needs to “balance the speed against the risks of bubbles,” Bloomberg reported. Investors’ appetite for humanoid robots is largely driven by AI, because AI gives humanoids a commercial potential that was previously not possible. According to Daiva Rakauskaitė, partner and manager of Aneli Capital, a company that manages a €35 million fund for early-stage Central and Eastern European startups, there are strong similarities between today’s AI-driven investment boom and the dotcom bubble in the early 2000s, leaving many startups exposed. She expects an AI bubble burst in 2-3 years. “Many AI startups that can’t yet generate revenue will fail, but we’re reaching a consensus on that in the market. While the same risks persist in humanoid robotics, many investors tend to […]

Asia Industrial Online Exhibition 2025

The Asian Industrial Online Exhibition 2025 (AIOE 2025) is from March 31 to July 31, 2025, offering international buyers an exclusive opportunity to explore Asia’s top industrial manufacturers—all in one place, without the constraints of geography or time. This four-month hybrid exhibition, co-organised by AsianNet and TradeAsia (www.e-tradeasia.com), is designed specifically to meet the growing needs of global buyers seeking reliable suppliers, advanced technologies, and efficient sourcing solutions from across Asia. Since its successful debut in 2022, AIOE has continued to deliver outstanding results for both buyers and exhibitors. For 2025, the exhibition will expand its reach with a four-month duration, strategically aligned with major global industrial events such as Hannover Messe, Global Industrie, Automate 2025, and Manufacturing World Tokyo. This synchronised timing allows buyers to explore and compare solutions from multiple regions in one procurement cycle—maximizing efficiency and market visibility. AIOE 2025 features a robust lineup of respected Taiwanese manufacturers, including industry leaders such as ASCCO INTERNATIONAL, ZITAI PRECISION MACHINERY, TW GRANDEUR MACHINERY, SAN SHING MACHINERY, U-CAN DYNATEX, KINGDOM ABRASIVE, JESPER PET, OAV EQUIPMENT & TOOLS, UNITRONIC AUTOMATION, CHU-SHIANG INDUSTRIAL, SHANG-YUH MACHINE, KINGDOM MACHINERY, CHUEN CHARNG, YNG YUH ELECTRONIC, and many more. These companies will present thousands of the latest industrial products and technologies, covering a wide array of sectors crucial to modern manufacturing and production. Buyers can explore everything from bearings, castings, and mold-making components to general industrial equipment and mechanical parts. The exhibition also includes cutting-edge solutions in machine tools, metalworking systems, and mining and metallurgy machinery. In addition, it showcases advanced testing instruments, precision measurement devices, automation technologies, and essential industrial electronics such as power supply units, electromechanical components, and industrial computers. Packaging machinery and supporting equipment are also well represented, ensuring buyers have access to complete sourcing solutions across the entire industrial supply chain. […]

AVEVA partners with ServiceNow to drive Industrial Transformation

AVEVA, a global leader in industrial software, driving digital transformation and sustainability, has announced a partnership with ServiceNow, the AI platform for business transformation, that will further accelerate industrial transformation. By leveraging AVEVA’s four decades of industrial software expertise and its groundbreaking industrial intelligence platform, CONNECT, and ServiceNow’s acclaimed AI-driven Operational Technology Management product line, this partnership will unite teams, digital estates, locations, applications, and data to foster seamless collaboration and boost productivity. The new collaboration will bring together both companies’ capabilities within the CONNECT platform, enabling customers to unify information on industrial processes, utilise AI and automation for more efficient workflows, and apply integrated analytics for greater productivity. As a result, companies can empower their workforce and streamline operations, reduce unplanned downtime and optimise production.

Operationalising AI for Manufacturing in ASEAN

Karen Kim, CEO Human Managed While the hype around Gen-AI will shift to the buzz around agentic-AI in 2025, traditional sectors such as manufacturing will still be coming to terms on deploying AI strategies to become participants of Industry 4.0 or the Fourth Industrial Revolution. This is the next phase where disruptive trends including data, connectivity, analytics, robotics and human-machine interaction is said to transform manufacturing significantly. According to a Kearney study[1], while over 70% of ASEAN manufacturers polled claimed to be “non-leaders/followers” of AI adoption, 47% believe investment in AI is “very critical” for their business. Gartner’s[2] Prism use case of GenAI in Manufacturing encourages leaders to evaluate AI use cases on a strategy that addresses both value generation and feasibility . Value parameters include increased revenue, increased efficiency, managed risk and non-financial gain. Feasibility parameters include technical feasibility, internal readiness, external readiness. So how can leaders operationalize AI, keeping value and feasibility in mind? At Human Managed, we believe it begins with an understanding of data. A framework to understand the highest impact for manufacturing businesses in the age of AI, would be to understand “3 Ops”-DataOps (Feeding AI), MLOps (Tuning AI), IntelOps (Applying AI). Data Ops (Feeding AI) In the manufacturing sector, data can be provided through assets in an interconnected ecosystem. From a range of sensors, machine data on temperature, vibrations, pressure, power consumption, operating hours etc are collected. Industrial machines, robotic arms and assembly lines can provide process data includes information on production rates, cycle times, error rates, material usage. Image and video data from cameras capture data for product dimensions and defect detection. ERP systems provide information on inventory levels, order information, transportation data. Given the vast array of data, manufacturing enterprises have to first solve for the issues around understanding the data itself. […]

VCI Global secures distributorship for military-grade AI-Powered cybersecurity solutions

VCI Global Limited has exclusive distributorship of Secure Encryption Storage Limited (“SES”) for Data Security Solutions (“SES Solutions”) in Malaysia. Powered by AI, SES Solutions provide advanced features such as real-time threat detection, virus defense, data encryption, and multi-channel backup. Trusted by over 300 clients, including Fortune 500 companies and government agencies, SES is a leading choice for safeguarding enterprise data and combating cyber threats. According to Check Point Research, the urgency of addressing cybersecurity risks is highlighted by a 30% year-over-year increase in global cyberattacks, with organisations facing an average of 1,636 cyberattacks per week. In response to the rising threat landscape, leading technology players have taken significant steps to enhance data protection. Inetum has partnered with Rubrik, Inc. to improve data protection and recovery, while IBM Corporation launched the Guardium Data Security Center, offering AI and quantum-safe features for unified data protection. At the same time, Salesforce, Inc. has completed its US$1.9 billion acquisition of Own Company, leveraging the latter’s data protection and management solutions to enhance the security and compliance of customer data across the Salesforce platform. These strategic initiatives reflect the increasing demand for robust cybersecurity solutions. According to Statista, the global cybersecurity market is projected to reach around US$280 billion by 2029, fueled by advancements in AI and the growing need for enhanced security. In Malaysia, the cybersecurity market is expected to grow from around US$500 million in 2025 to approximately US$800 million by 2029. In response to this growth, VCI Global is positioning itself to capture 3% of the Malaysian market, with expected revenues surpassing US$15 million within the first two years of its partnership.

Operationalising AI for manufacturing in ASEAN

Karen Kim, CEO Human Managed While the hype around Gen-AI will shift to the buzz around agentic-AI in 2025, traditional sectors such as manufacturing will still be coming to terms on deploying AI strategies to become participants of Industry 4.0 or the Fourth Industrial Revolution. This is the next phase where disruptive trends including data, connectivity, analytics, robotics and human-machine interaction is said to transform manufacturing significantly. According to a Kearney study[1], while over 70% of ASEAN manufacturers polled claimed to be “non-leaders/followers” of AI adoption, 47% believe investment in AI is “very critical” for their business. Gartner’s[2] Prism use case of GenAI in Manufacturing encourages leaders to evaluate AI use cases on a strategy that addresses both value generation and feasibility . Value parameters include increased revenue, increased efficiency, managed risk and non-financial gain. Feasibility parameters include technical feasibility, internal readiness, external readiness. So how can leaders operationalise AI, keeping value and feasibility in mind? At Human Managed, we believe it begins with an understanding of data. A framework to understand the highest impact for manufacturing businesses in the age of AI, would be to understand “3 Ops”-DataOps (Feeding AI), MLOps (Tuning AI), IntelOps (Applying AI). Data Ops (Feeding AI) In the manufacturing sector, data can be provided through assets in an interconnected ecosystem. From a range of sensors, machine data on temperature, vibrations, pressure, power consumption, operating hours etc are collected. Industrial machines, robotic arms and assembly lines can provide process data includes information on production rates, cycle times, error rates, material usage. Image and video data from cameras capture data for product dimensions and defect detection. ERP systems provide information on inventory levels, order information, transportation data. Given the vast array of data, manufacturing enterprises have to first solve for the issues around understanding the data itself. […]

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