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Manufacturing Industrials
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ProcurePro Raises $11M to Deliver AI-Powered Procurement Control for Construction’s $13 Trillion Supply Chain
Backed by QIC Ventures, Airtree, and ISAI, the Brisbane-founded company will expand its AI product suite, scale internationally, and grow its team across key global markets. LONDON, BRISBANE, Australia and DUBAI, UAE, May 11, 2026 /PRNewswire/ — ProcurePro, the first end-to-end construction procurement platform, has secured US$11 million in a funding round led by QIC Ventures […]
Why Caterpillar Could Be the AI Stock of the Year | The Motley Fool
Data center construction is driving the demand for Caterpillar's products.
Power chip shortages deepen as AI server demand and GaN battles escalate
Global power semiconductor suppliers are entering a new upcycle marked by tightening supply, rising prices, and intensifying technology competition, fueled by accelerating investment in AI infrastructure and electric vehicles.
Global Manufacturers Look to AI in Supply Chain | Supply Chain Magazine
In today's operations, manufacturers ... adopt AI technology in order to develop supply chain resilience and risk mitigation · Manufacturing supply chains have undergone significant transformation in recent years, driven by the need to adapt to geopolitical instability and increasing global ...
ROX Expands AI Manufacturing in Abu Dhabi to Boost UAE's Operation 300Bn Initiative
ROX is expanding its operations in Abu Dhabi, focusing on AI-driven manufacturing and regional growth, aiming to produce 300,000 vehicles annually by 2030.
LANTERN: LLM-Augmented Neurosymbolic Transfer with Experience-Gated Reasoning Networks
arXiv:2605.05478v1 Announce Type: new Abstract: Transfer learning in reinforcement learning (RL) seeks to accelerate learning in new tasks by leveraging knowledge from related sources. Existing neurosymbolic transfer methods, however, typically rely on manually specified task automata, assume a single source task, and use fixed knowledge-integration mechanisms that cannot adapt to varying source relevance. We propose LANTERN, a unified framework for multi-source neurosymbolic transfer that addresses these limitations through three components: (i) deterministic finite automata generated from natural language task descriptions using large language models, (ii) semantic embedding-based aggregation of multiple source policies weighted by cross-task similarity, and (iii) adaptive teacher-student gating based on temporal-difference error and semantic uncertainty. Across domains spanning resource management, navigation, and control, LANTERN achieves 40-60% improvements in sample efficiency over existing baselines while remaining robust to poorly aligned sources. These results demonstrate that multi-source, adaptively weighted neurosymbolic transfer can improve scalability and robustness in symbolic RL settings.
Cognex Launches In-Sight 3900: High-Speed AI Vision System
Cognex has launched the In-Sight 3900, an AI-driven vision system designed to enhance factory floor operations without the need for an external PC.
Nvidia and Corning Team Up to Boost AI Manufacturing in US
Nvidia and Corning are partnering to boost U.S. manufacturing for AI infrastructure, specifically focusing on fiber and optical components for data centers.
Automated Large-scale CVRP Solver Design via LLM-assisted Flexible MCTS
arXiv:2605.03339v1 Announce Type: new Abstract: Solving large-scale CVRP (LSCVRP) with hundreds to thousands of nodes remains difficult for even state-of-the-art solvers. Divide-and-conquer can scale by decomposing the instance into size-reduced subproblems, but designing decomposition logic and configuring sub-solvers is highly expertise- and labor-intensive. Large Language Models (LLMs) have emerged as promising tools for automated algorithm design. However, existing LLM-driven approaches struggle with LSCVRP primarily due to the difficulty in generating sophisticated search strategies within a limited context window. To bridge this gap, we propose the LLM-assisted Flexible Monte Carlo Tree Search (LaF-MCTS), a novel framework that automates the design of high-performance LSCVRP solvers. We develop a three-tier decision hierarchy to enable incremental design of decomposition policies and sub-solvers for LSCVRP. To enable efficient search within the algorithmic hypothesis space, we introduce semantic pruning to eliminate semantically and structurally redundant codes, and branch regrowth to regenerate codes and preserve diversity. Extensive experiments on CVRPLib demonstrate that LaF-MCTS autonomously composes and optimizes decomposition-enhanced solvers that surpasses various state-of-the-art CVRP solvers.
MolmoAct 2: An Open Foundation for Robots that Work in the Real World
MolmoAct 2 is an open robotics foundation model featuring a vision-language-action pipeline designed for real-world robot manipulation tasks.
GlobalFoundries turns three-continent footprint into geopolitical hedge
In a recent assessment of the semiconductor landscape, GlobalFoundries emphasized the critical need for supply chain resilience amid a "fragmented geopolitical environment." The company is positioning its three-continent manufacturing presence—spanning the US, Germany, and Singapore—as ...
2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing
arXiv:2605.00839v1 Announce Type: new Abstract: The evolution of artificial intelligence (AI) and machine learning (ML) is reshaping smart manufacturing by providing new capabilities for efficiency, adaptability, and autonomy across industrial value chains. However, the deployment of AI and ML in industrial settings still faces critical challenges, including the complexity of industrial big data, effective data management, integration with heterogeneous sensing and control systems, and the demand for trustworthy, explainable, and reliable operation in high-stakes industrial environments. In this roadmap, we present a comprehensive perspective on the foundations, applications, and emerging directions of AI and ML in smart manufacturing. It is structured in three parts. The first highlights the foundations and trends that frame the evolution of AI in smart manufacturing. The second focuses on key topics where AI is already enabling advances, including industrial big data analytics, advanced sensing and perception, autonomous systems, additive and laser-based manufacturing, digital twins, robotics, supply chain and logistics optimization, and sustainable manufacturing. The third section explores non-traditional ML approaches that are opening new frontiers, such as physics-informed AI, generative AI, semantic AI, advanced digital twins, explainable AI, RAMS, data-centric metrology, LLMs, and foundation models for highly connected and complex manufacturing systems. By identifying both opportunities and remaining barriers across these areas, this roadmap outlines the advances needed in methods, integration strategies, and industrial adoption. We hope this roadmap will serve as a guide for researchers, engineers, and practitioners to accelerate innovation, align academic and industrial priorities, and ensure that AI-driven smart manufacturing delivers reliable, sustainable, and scalable impact for the future of manufacturing ecosystems.
A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion
arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainable defect diagnosis and mitigation guidance in manufacturing, using LPBF as a representative, safety-critical case study. The proposed ontology-integrated LLM-based decision support system for LPBF defect analysis and mitigation guidance is built on a knowledge base containing 27 known LPBF defect types organized into hierarchical categories and causal relationships. The developed system supports fuzzy natural language queries for systematic knowledge retrieval, literature-supported explanation of defects, and guidance on defect causes and mitigation strategies derived from encoded process knowledge. Furthermore, a multimodal image-assessment module based on foundation models enables descriptor-guided interpretation of representative microscopic defect images through semantic alignment scoring. The proposed framework was evaluated through qualitative comparisons with general-purpose vision-language models, an ablation study, and an inter-rater reliability analysis. Evaluation on the literature-derived dataset showed that the fully integrated configuration outperformed the other three evaluated system configurations, achieving a macro-average F1 score of 0.808. Additionally, inter-rater reliability analysis using Cohen's kappa indicated substantial agreement between the model outputs and the literature-derived reference labels. These findings suggest that ontology-guided knowledge representation can improve the consistency, interpretability, and practical usefulness of LLM-assisted LPBF defect analysis.
Veeco Instruments Surges 19% on Massive $250M AI Laser Orders Despite Q1 Miss
The move reflects broader enthusiasm ... to AI infrastructure buildout, even if quarterly results are not perfect. ... Despite the positive momentum, Veeco faces ongoing challenges. Reduced shipments to China due to export controls impacted Q1 results, and the company continues navigating a complex geopolitical environment. Competition in the ...
Gartner: The Cost of Reducing Entry-Level Hiring for AI | Supply Chain Magazine
As more businesses look to save money and fill workforce gaps with AI, Gartner warns that pausing entry-level hiring could result in higher business costs
AI era forces Korea's labor, capital to negotiate new ‘survival pact' - The Korea Times
As artificial intelligence (AI) spreads from coding assistants to factory robots and hiring tools, experts say Korea’s familiar labor disputes over...
French startup unveils AI model for robots and human-like hand | Reuters
May 6 (Reuters) - Genesis AI , a French robotics startup backed by former Google CEO Eric Schmidt and telecoms tycoon Xavier Niel, on Wednesday unveiled an AI model designed to make robots more adaptable, along with a human-like robotic hand.
Thinking in Text and Images: Interleaved Vision--Language Reasoning Traces for Long-Horizon Robot Manipulation
arXiv:2605.00438v1 Announce Type: new Abstract: Long-horizon robotic manipulation requires plans that are both logically coherent and geometrically grounded. Existing Vision-Language-Action policies usually hide planning in latent states or expose only one modality: text-only chain-of-thought encodes causal order but misses spatial constraints, while visual prediction provides geometric cues but often remains local and semantically underconstrained. We introduce Interleaved Vision--Language Reasoning (IVLR), a policy framework built around \trace{}, an explicit intermediate representation that alternates textual subgoals with visual keyframes over the full task horizon. At test time, a single native multimodal transformer self-generates this global semantic-geometric trace from the initial observation and instruction, caches it, and conditions a closed-loop action decoder on the trace, original instruction, and current observation. Because standard robot datasets lack such traces, we construct pseudo-supervision by temporally segmenting demonstrations and captioning each stage with a vision-language model. Across simulated benchmarks for long-horizon manipulation and visual distribution shift, \method{} reaches 95.5\% average success on LIBERO, including 92.4\% on LIBERO-Long, and 59.4\% overall success on SimplerEnv-WidowX. Ablations show that both modalities are necessary: without traces, LIBERO-Long success drops to 37.7\%; text-only and vision-only traces reach 62.0\% and 68.4\%, while the full interleaved trace reaches 92.4\%. Stress tests with execution perturbations and masked trace content show moderate degradation, suggesting that the trace can tolerate local corruption and moderate execution drift, but remains limited under stale or incorrect global plans.
Paris-based Lithosquare raises €21.4 million to accelerate transition-critical mineral discovery with Geology AI
Lithosquare, a Paris-based startup that deploys Geology AI and geologist-led intelligence to amplify and accelerate the discovery of transition-critical minerals, has raised €21.3 million ($25 million) in fresh funding. The round was co-led by World Fund and Kindred Capital, with participation from Daphni, Omnes Capital and Ovni Capital. The company plans to use this funding […]
Integrated Digital Management System for Railway Workshops: A Modular Multi-Workflow Architecture for Machine, Permit, Contract, and Incident Management
arXiv:2605.00840v1 Announce Type: new Abstract: Indian Railway workshops form a critical component of rolling stock maintenance infrastructure, employing more than 2.5 lakh personnel across 44 major workshops nationwide. However, safety management in many workshops still relies on fragmented manual processes, resulting in delayed approvals, incomplete documentation, and increased exposure to operational hazards. Field safety observations indicate that lacerations (28.7%) and abrasions (21%) remain among the most frequent workplace injuries, highlighting the need for structured digital safety workflows. This paper presents the Integrated Digital Management System for Railway Workshops, a modular multi-workflow digital platform developed to improve safety governance and workflow transparency. The proposed system integrates four primary modules: Machine and Plant Management, Permit-to-Work (PTW) Management, Contract Management, and Incident Management. The Permit-to-Work module digitizes hazardous work authorization in accordance with IS 17893:2022, while the Contract Management module supports workforce validation and regulatory oversight. The Incident Management module enables rapid reporting, investigation tracking, and corrective action workflows. Functional evaluation in a railway workshop-oriented deployment scenario demonstrated measurable operational improvements, including a reduction in permit processing time by approximately 35%, improved incident reporting response time by nearly 40%, and enhanced workflow traceability across multiple safety modules. The proposed system establishes a scalable foundation for digital safety governance in large-scale railway workshop environments.
Rheinmetall’s first-quarter revenues fail to meet expectations
German company’s shares under pressure over profitability concerns and questions about the future of warfare
Asia Manufacturing Sector Feeling Strain From Middle East Conflict
Gauges of factory activity showed more evidence of supply-chain disruptions from the war, with stockpiling buoying production as cost pressures intensify.
An Aluminum Crisis Is Roiling the Auto Industry
America’s top-selling vehicle, the Ford F-150, bears the brunt of metal-supply-chain woes.
National Safety Council and Wolters Kluwer Enablon Report Finds Adoption of AI Growing Rapidly Among EHS Pros | ISHN
Enthusiasm for AI accompanied by caution, as 90% of safety professionals agree guardrails are needed.
How AI Tools Generate Technical Debt in IoT Systems — and What to Do About It
AI tools speed up IoT development, but the same code that looks correct can silently break thousands of devices at once.
Physical AI Startup Statistics
Physical AI startup statistics for 2026: robotics funding, robot foundation models, industrial robots, warehouses, drones, autonomous systems, and founder opportunity.
CISA and partners release agentic AI security guidance to protect critical infrastructure, outline mitigation action - Industrial Cyber
CISA and partners release agentic AI security guidance to protect critical infrastructure, outline mitigation action
Always Be Curious #305: EUV's engineering story, earnings bonanza, and prediagnostic AI
Japanese researchers built an AI tool that designs thermoelectric generators 10,000 times faster than conventional approaches, with prototypes performing on par with today’s best devices — potentially
India roundup: India accelerates AI, semiconductor, and manufacturing push with major investments and startup bets
India's technology ecosystem is seeing rapid expansion across AI infrastructure, semiconductors, and electronics manufacturing. From startup bets on AI inference to multi-billion-dollar data center plans and OSAT capacity buildouts, global and domestic players are deepening commitments.
AI data center demand boosts IDM growth in industrial market
Recovery in the industrial chip market, driven by AI data center demand, is poised to reshape manufacturers and supply chains worldwide, as Texas Instruments and NXP Semiconductors report stronger performance in their industrial segments. Improved demand visibility and projected growth through ...
Fortune
Unionized workers form alliance with rich tech giants on AI data centers, pushing back on local opposition and redrawing political lines
The U.S. will raise tariffs on automobiles from the European Union to 25% from 15%, President Trump said Friday
The president said tariffs will go from 15% to 25% and accused the bloc of failing to comply with a trade agreement signed last year.
‘Temu Range Rover’: what the bestselling Jaecoo 7 says about China’s electric car ascendancy
Loaded with extras and produced at a cut price, the crossover SUV has overtaken rival cars from US, Japanese and Korean firms The UK is no stranger to foreign cars. The bestseller lists in recent years have been dominated by the US’s Ford Puma, Japan’s Nissan Qashqai, Korea’s Kia Sportage and occasionally even Tesla’s Model Y. But in March the top 10 provided a shock: a Chinese car leapt into the lead.
Meta buys robotics startup to bolster its humanoid AI ambitions
Meta has acquired a robotics company to accelerate its development of humanoid AI technologies.
Inside A Fabricator’s Digital Reinvention
CEO Lance Thrailkill is pushing a 70-year-old family business beyond traditional fabrication—investing in Industry 4.0, vertical integration and critical infrastructure to drive speed, precision and long-term growth.
Dyad 3.0: Revolutionizing Industrial Design with AI and Digital Twins at Live Launch Event
JuliaHub's Dyad 3.0 platform uses AI-enabled digital twins to automate engineering processes and reduce development time for industrial design.
AI chip boom sends Korea exports to record highs, supply crunch deepens
South Korea's export surge is entering a new phase, with artificial intelligence-driven semiconductor demand powering record shipments even as geopolitical risks and cost pressures mount.
Samsung chip profit jumps almost 50-fold
Samsung chip profit jumps almost 50-fold; supply shortage to worsen in 2027
Dyad 3.0 Revolutionizes Industrial Design
JuliaHub's Dyad 3.0 platform, an AI-enabled digital twin system, is set to revolutionize industrial design by automating engineering processes and reducing development time.
AI chip boom sends Korea exports to record highs, supply crunch deepens
South Korea's export surge is entering a new phase, with artificial intelligence-driven semiconductor demand powering record shipments even as geopolitical risks and cost pressures mount.
Shares in Japanese toilet maker Toto soar on AI-related pivot
Investors cheer after company unveils plans to boost output of semiconductor components
AI’s Bottleneck Is Steel, Silicon and Ships
Boris Kriuk is right: AI does not fail when a model misbehaves; it falters when the supply chains beneath it do. The real constraint on AI is no longer clever code, but the physical and institutional systems that make large‑scale computation possible.
EU Chips Act Overhaul Aims to Boost Investment - Bloomberg
EU Chips Act Overhaul Aims to Boost Investment - Bloomberg Chip Wars: US AI Export Control BackForward Semiconductor wafer fabrication in Germany. Photographer: Krisztian Bocsi/Bloomberg Gift this article Contact us:Provide news feedback or report an error Confidential tip?Send a tip to our reporters Site feedback:Take our Survey By Gian Volpicelli and Alberto Nardelli April 30, 2026 at 12:34 PM U
Humanoid Maker 1X Opens New US Factory, Plans to Build 10,000 Home Robots in First Year
1X Technologies AS, the Norway-founded robotics startup backed by OpenAI, has opened a new 58,000-square-foot factory in Hayward, California, where it aims to be one of the first players to build humanoids for consumers at scale.
No question the AI megatrend continues, Taiwan's MediaTek says
No question the AI megatrend continues, Taiwan's MediaTek says | Reuters Exclusive news, data and analytics for financial market professionalsLearn more aboutRefinitiv A Mediatek logo appears in this illustration taken August 25, 2025. REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights, opens new tab - Summary - Companies - MediaTek upbeat on AI demand - MediaTek is Taiwan's top chip design company - MediaTek shares have leapt more than 80% this year - Taiwanese tech firms key suppliers for AI darling Nvidia TAIPEI, April 30 (Reuters) - The CEO of MediaTek(2454.TW), opens new tab, Taiwan's top chip design company, on Thursday said he has no doubts about the strength of the artificial intelligence wave, adding that demand for data centres is accelerating. Taiwanese tech companies like MediaTek and TSMC(2330.TW), opens new tab, the world's largest contract chipmak
EU legislators fail to clinch deal to delay AI law – POLITICO
Talks derailed over request backed by Germany to weaken rules for manufacturing and medical devices.
Supermicro opens largest US campus in Silicon Valley, producing AI infrastructure
Supermicro's new 32.8-acre Silicon Valley campus will add hundreds of US positions and expand domestic production of AI infrastructure, signaling increased US capacity for enterprises and cloud providers worldwide. The expansion may affect global AI deployment timelines and supply-chain choices ...
The Race to Merge AI With Humanoid Robots
Humanoid robots that use AI are going mainstream, but they’re far from proven. With billions of dollars invested, can they deliver real-world value or will they fall short of the hype? (Source: Bloomberg)
SoftBank plans to list new AI and robotics company in the US
Masayoshi Son plots IPO for business named Roze as soon as this year
As Europe pushes for AI sovereignty, Germany’s SPREAD raises €25 million to scale industrial AI
SPREAD AI, a Berlin-based Engineering Intelligence Platform innovating how complex products are developed and operated, today announced it has raised €25 million ($30 million) in Series B funding to expand across Europe and the U.S., scale within the Salesforce ecosystem, and strengthen its presence in aerospace, defense, and heavy machinery sectors. The round was backed […]
NSK and Accenture Forge Strategic Collaboration to Drive Business Reinvention Through AI and Digital Technology | MarketScreener
NSK Limited and Accenture today announced a strategic collaboration to drive the reinvention of NSK's business through AI and digital technology, with the goal of achieving sustainable growth and...
AI-related spending propels US core capital goods orders in March | Reuters
New orders for key U.S.-manufactured capital goods increased by the most in nearly six years in March while their shipments rose solidly, suggesting that business spending on equipment helped drive economic growth in the first quarter.
Exclusive: How one venture firm is investing in an increasingly fragmented world | TechCrunch
Geopolitical turmoil has made venture investing challenging, leading Kompas VC to carve out a niche in startups focused on the physical world.
Applied Materials Faces New China Export Halt And Revenue Exposure Questions - Simply Wall St News
The U.S. Department of Commerce has halted shipments of certain semiconductor manufacturing tools to China’s Hua Hong, directly affecting Applied Materials’ cross border business. The action targets sales of advanced equipment that Hua Hong uses for chip production, adding a fresh layer ...
Steelmaker Cliffs Taps Palantir Technologies for AI Overhaul
Cleveland-Cliffs Inc. struck a three-year agreement with Palantir Technologies Inc. to deploy artificial intelligence tools across its operations, as the US steelmaker steps up efforts to modernize its manufacturing footprint.
Foxconn Industrial Falls Short of Lofty AI Expectations
Foxconn Industrial Internet Co. benefited less than expected from China’s artificial intelligence boom as sales and earnings growth fell short of lofty expectations.
Nvidia-Supplier Victory Giant’s Sales Surge on Solid AI Demand
Victory Giant Technology Huizhou Co. reported a 28% increase in quarterly sales on stronger demand for printed circuit boards critical for development of AI servers.
The Real ROI of AI Coworkers in Manufacturing ( With Cost Models) - Programming Insider
AI coworkers in manufacturing are no longer pilot-stage experiments. In 2025, they will live on production floors at mid-market and enterprise manufacturers alike, reducing downtime, compressing onboarding cycles, and delivering measurable cost savings within 12–18
Open source Xiaomi MiMo-V2.5 and V2.5-Pro are among the most efficient (and affordable) at agentic 'claw' tasks
Xiaomi's new open-source MiMo-V2.5 models are setting new benchmarks for efficiency and affordability in agentic robotic tasks.
Unlocking AI: IBM’s ‘Client Zero’ Strategy and Key Insights for Indian Manufacturers, ETEnterpriseai
Discover how IBM's 'client zero' approach enhances AI deployment for manufacturers in India. Learn valuable lessons on data management, AI ownership, talent constraints, and the future of agentic AI in industry.
The Impact of Dodd-Frank and the Huawei Shock on DRC Tin Exports
arXiv:2512.21645v2 Announce Type: replace Abstract: This paper investigates the structural transformation of the Democratic Republic of the Congo (DRC) tin market induced by the U.S. Dodd-Frank Act. Focusing on the breakdown of the pricing mechanism, we estimate the price elasticity of export demand from 2010 to October 2022 using a structural identification strategy that overcomes the lack of reliable unit value data. Our analysis reveals that the regulation effectively destroyed the price mechanism, with demand elasticity dropping to zero. This indicates the formation of a ``captive market'' driven by certification requirements rather than price competitiveness. Also, we find strong hysteresis; deregulation alone failed to restore market flexibility. The structural rigidity was finally broken not by policy suspension, but by the 2019 ``Huawei shock,'' an external demand surge that forced supply chain diversification.
Amazon Web Services unveils agentic AI supply chain tool | Supply Chain Dive
Amazon Web Services today launched ... that aims to help businesses improve planning, data analysis and decision making. The product combines more than 25 specialized supply chain tools into a set of artificial intelligence agents, called “teammates,” to make calculations on behalf of the user, VP of AWS Supply Chain Ozgur Dogan told Supply Chain Dive. “Every variance, invisible patterns — the system learns and ...
Inside China’s robotics revolution – podcast
How close are we to the sci-fi vision of autonomous humanoid robots? I visited 11 companies in five Chinese cities to find out By Chang Che. Read by Vincent Lai Continue reading...
AI Startup Sereact Raises $110 Million for Robots That Predict Consequences
Sereact, a German robotics software company, has raised $110 million in fresh funding to develop its artificial intelligence model that makes robots smarter and more adaptable to different tasks.
Iran War Disrupts Circuit Board Supply Chain
The conflict in the Middle East has disrupted supplies of crucial raw materials and pushed up prices of the printed circuit boards.
Semiconductors core to Tyndall’s five-year strategy
The institute said its strategy is aligned with government policies such as Silicon Island and Impact 2030 while helping towards Ireland’s obligations under the European Chips Act. Read more: Semiconductors core to Tyndall’s five-year strategy
STMicroelectronics Q1 FY 2026 Earnings Show Early AI and Satellite Upside
Brendan Burke, Research Director, analyzes STMicroelectronics’ Q1 FY 2026 earnings, focusing on AI data center and LEO satellite momentum, photonics ramp timing.
The sovereign shift as Asia accelerates industrial realignment amid global tensions | Domain-b.com
Asia is accelerating investments in defense, sovereign AI, and energy transition as geopolitical risks reshape global supply chains and industrial strategy.
‘World models’ are AI’s latest sensation: what are they and what can they do?
Training AI world models on data about physical environments could improve their real-world capabilities in technologies such as robotics. Training AI world models on data about physical environments could improve their real-world capabilities in technologies such as robotics.
Roadmap to Autonomous Manufacturing: An AI driven Approach Based on Engineering Foundations - Edge AI and Vision Alliance
This article was originally published at HCLTech’s website. It is reprinted here with the permission of HCL Tech. Autonomous manufacturing can be achieved through a structured journey built on foundational engineering, converged data and human-led AI Key takeaways Autonomous manufacturing ...
Activist Palliser takes stake in Japan's SMC, proposes $3.8 billion buyback
Activist Palliser takes stake in Japan's SMC, proposes $3.8 billion buyback.
BMW and PepsiCo robotics partner Sereact raises €93 million Series B to scale across the US
Stuttgart-based Sereact, an innovator in physical AI for warehouses and manufacturing, has raised a €93 million ($110 million) Series B round in order to scale their ‘Cortex 2’ offering and to open its first office in the U.S. in Boston at some point during the coming summer – aiming to hire new staff locally. The […]
The Biggest Risk of Embodied AI is Governance Lag
arXiv:2604.21938v1 Announce Type: new Abstract: Embodied AI is widely discussed as a job-displacement problem. The deeper risk, however, is governance lag: the inability of public institutions to keep pace with how fast the technology spreads through the physical economy. As reusable robotic platforms are combined with increasingly general AI models, embodied AI may scale across manufacturing, logistics, care, and infrastructure faster than governance systems can observe, interpret, and respond. We argue that this lag appears in three connected forms: observational, institutional, and distributive. The central policy challenge, therefore, is not automation alone, but whether governance and compliance systems can adapt before disruption becomes entrenched.
On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery
arXiv:2604.22455v1 Announce Type: new Abstract: A core component of any AI-Augmented Business Process Management System (ABPMS) is the process frame, which gives the system process-awareness and defines the boundaries in which the system must operate. Compared to traditional process models, the process frame should, in principle, provide a somewhat more permissive representation of the managed processes, such that the (semi) autonomous behavior of an ABPMS, referred to as framed autonomy, could emerge. At the same time, it is not limited to a single linguistic or symbolic formalism and may incorporate heterogeneous knowledge ranging from predefined procedures to commonsense rules and best practices. In this paper, we conceptualize the notion of an ABPMS process frame as a hybrid business process representation, consisting of semi-concurrently executed procedural and declarative process models. We rely on our earlier works to outline the execution semantics of this type of process frame, arguing in favor of adopting the open-world assumption of the declarative paradigm also for procedural process models. The latter leads to a constraint-like interpretation, where each procedural model is considered to constrain the activities within that model, without imposing explicit execution requirements nor limitations on activities that may be present in other models. This is analogous to existing declarative languages, such as Declare, where each constraint has a direct effect only on the specific activities being constrained. Given this similarity, we propose mapping subsets of discovered declarative constraints into equivalent semi-concurrently executed procedural fragments, thus laying the foundation for a corresponding process (frame) discovery approach.
Chinese Workers Train AI Replacements
Chinese workers are being directed to train their AI replacements, sparking concerns over job displacement.
AI Revolutionizes Bottle Filling
AI is revolutionizing bottle filling with predictive maintenance, real-time data analysis, and adaptive systems, enhancing efficiency and reducing waste.
After call from Beijing, China's auto industry races to embed AI in just about everything | Reuters
Xiaomi has said its AI -empowered HyperOS operating system in its cars would allow drivers to task the system with complicated to-do lists, making restaurant reservations, placing coffee orders and compiling notes from the road.
America's Largest Landowner Is Mapping And Digitizing Forests With AI, Creating A 'Database Detailing Each Tree In The Forest'
Weyerhaeuser, a timber company that owns roughly 10,400,000 acres of American forest land and 14,000,000 acres of timberland in Canada, is mapping every inch of their land with AI , creating a detailed database containing every tree the company has mapped out.
India-Japan Alliance to Transform Urban Development
India's DataKaveri Systems and Japan's ONESTRUCTION Inc. have teamed up to leverage underutilized construction data for AI-driven urban development.
China's Auto Industry Revolutionizes with AI-Driven Cars
China's AI Plus initiative is driving rapid integration of artificial intelligence into vehicles, with brands like Xpeng and Xiaomi showcasing advanced AI features.
‘Startup Cowboys’ Are Making This Texas Town the New Tech Hotspot
The site near Austin known as Proto-Town is attracting robotics and energy firms whose members work and live in trailer parks on the more than thousand-acre campus.
Jtibot Showcases Autonomous Outdoor Sweeping Innovation at Interclean Amsterdam 2026, Accelerating European Market Expansion
AMSTERDAM, April 24, 2026 /PRNewswire/ — Jtibot, a developer of autonomous outdoor cleaning solutions, concluded a successful showcase at Interclean Amsterdam 2026, highlighting its focus on large-scale, AI-driven sweeping for industrial, municipal, and campus environments. At Hall 8, Booth 538, Jtibot presented its autonomous outdoor sweeper designed for environments exceeding 10,000 sqm. Positioned between traditional […]
Infor launches AI orchestration tools as research shows enterprises struggle to scale AI
Infor has introduced new capabilities across its AI portfolio, alongside research suggesting many businesses are still struggling to scale artificial intelligence beyond pilot stages. The company’s…
The Hidden Cost of AI in Warehouses Is Training Workers - Supply Chain 24/7
The Hidden Cost of AI in Warehouses Is Training Workers - Supply Chain 24/7 - Free newsletters - Become a member - Why join? - Log in # The Hidden Cost of AI in Warehouses Is Training Workers ## New analysis from Resume Now show logistics facing one of the largest AI readiness gaps as adoption grows Source: Getty Images AI is becoming part of daily logistics operations, but workers are not keeping up. Artificial intelligence is becoming part of daily operations in logistics and warehousing, but getting workers up to speed may come with additional costs. What’s Related A new analysis from Resume Now, based on data from Lightcast, finds that logistics and warehousing ranks fourth among industries with the largest gaps between AI adoption and workforce readiness heading into 2026. The report focuses on preparedness, examining where AI-related skill demands are rising faster than th
Renault Revenue Rises on Brand Momentum
Revenue rose 8.8% at constant exchange rates, while the carmaker said it was taking additional steps to mitigate the potential impact of the Middle East conflict.
Ping-pong robot Ace makes history by beating top-level human players | Reuters
Ace, created by the Japanese company Sony's (6758.T), opens new tab AI research division, is the first robot to attain expert-level performance in a competitive physical sport, one that requires rapid decisions and precision execution, the project's leader said.
From Data to Theory: Autonomous Large Language Model Agents for Materials Science
arXiv:2604.19789v1 Announce Type: new Abstract: We present an autonomous large language model (LLM) agent for end-to-end, data-driven materials theory development. The model can choose an equation form, generate and run its own code, and test how well the theory matches the data without human intervention. The framework combines step-by-step reasoning with expert-supplied tools, allowing the agent to adjust its approach as needed while keeping a clear record of its decisions. For well-established materials relationships such as the Hall-Petch equation and Paris law, the agent correctly identifies the governing equation and makes reliable predictions on new datasets. For more specialized relationships, such as Kuhn's equation for the HOMO-LUMO gap of conjugated molecules as a function of length, performance depends more strongly on the underlying model, with GPT-5 showing better recovery of the correct equation. Beyond known theories, the agent can also suggest new predictive relationships, illustrated here by a strain-dependent law for changes in the HOMO-LUMO gap. At the same time, the results show that careful validation remains essential, because the agent can still return incorrect, incomplete, or inconsistent equations even when the numerical fit appears strong. Overall, these results highlight both the promise and the current limitations of autonomous LLM agents for AI-assisted scientific modeling and discovery.
A Multi-Plant Machine Learning Framework for Emission Prediction, Forecasting, and Control in Cement Manufacturing
arXiv:2604.19903v1 Announce Type: cross Abstract: Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, selective non-catalytic reduction (SNCR), exhibits low NH3 utilization efficiency, resulting in operational inefficiencies and increased reagent costs. Here, we develop a data-driven framework for emi
TSMC Says ASML’s Latest Chipmaking Gear Is Too Pricey
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Infor releases global study on AI adoption barriers and introduces key platform features. -
Infor has published the results of its Infor Enterprise AI Adoption Impact Index, new proprietary research.
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ILO sets first global framework for AI use in manufacturing sector | Digital Watch Observatory
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Union City Hosts First U.S. Advanced AI Chip Assembly Center – ICO Optics
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Volkswagen to equip Chinese cars with AI agents
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Industrial AI for the Physical World: Siemens’s Peter Koerte
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Sight Machine Launches AI Agent Crews to Revolutionize Manufacturing
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Extended Reality (XR) Market Trends Gain Momentum with Industrial Use Cases
XR combined with AI and IoT is enabling fully connected, intelligent industrial ecosystems. ... Industrial organizations are increasingly adopting XR for remote assistance and field service operations. Technicians equipped with AR-enabled devices or smart glasses can receive real-time instructions from experts located anywhere in the world. ... It also improves first-time fix rates and operational efficiency, especially in sectors like utilities, manufacturing...
Manufacturers face rising costs as AI adoption struggles
The survey of 1,453 senior executives ... to deploy industrial AI and its current operational readiness, raising concerns about worsening cost pressures and competitiveness through 2030. Schneider Electric said manufacturers are increasingly turning to industrial intelligence combining AI, data systems and automation to address structural inefficiencies in production environments. However, it warned that foundational constraints are limiting the pace and impact of adoption...
Merz, Siemens call for easing of EU regulations on industrial AI
At the huge Hannover Messe trade fair over the weekend, attendees heard calls for a lightening of EU Act regulations for industrial AI. Read more: Merz, Siemens call for easing of EU regulations on industrial AI
Merz, Siemens call for easing of EU regulations on industrial AI
At the huge Hannover Messe trade fair over the weekend, attendees heard calls for a lightening of EU Act regulations for industrial AI. Read more: Merz, Siemens call for easing of EU regulations on industrial AI
SAP at Hannover Messe 2026: Supply Chain AI Agents - AI
Manufacturing is entering a decisive moment. Rising costs, intensifying global competition, expanding regulatory requirements, and the rapid acceleration of
Siemens Warns EU’s AI Rules Will Deter Investment in Europe - Bloomberg
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Roland Busch: Siemens to prioritise AI investments in US and China instead of Europe; as CEO Roland Busch says: I cannot explain to my shareholders why I am … | - The Times of India
Tech News News: Siemens is not happy with European Union (EU) regulations related to artificial intelligence (AI). Europe’s biggest engineering company has reportedly.
Making AI Work: Germany's Friedrich Merz Advocates for Looser EU Regulations on Industrial AI, ETEnterpriseai
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Siemens AG warns that current European regulations regarding artificial intelligence could put a brake on investments in the region.
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Stellantis, Microsoft sign five-year partnership for AI push | Reuters
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Intel eases reliance on TSMC with 'Merica-made Core Series 3 processors
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Deepbullwhip: An Open-Source Simulation and Benchmarking for Multi-Echelon Bullwhip Analyses
arXiv:2604.13478v1 Announce Type: cross Abstract: The bullwhip effect remains operationally persistent despite decades of analytical research. Two computational deficiencies hinder progress: the absence of modular open-source simulation tools for multi-echelon inventory dynamics with asymmetric costs, and the lack of a standardized benchmarking protocol for comparing mitigation strategies across shared metrics and datasets. This paper introduces deepbullwhip, an open-source Python package that integrates a simulation engine for serial supply chains (with pluggable demand generators, ordering policies, and cost functions via abstract base classes, and a vectorized Monte Carlo engine achieving 50 to 90 times speedup) with a registry-based benchmarking framework shipping a curated catalog of ordering policies, forecasting methods, six bullwhip metrics, and demand datasets including WSTS semiconductor billings. Five sets of experiments on a four-echelon semiconductor chain demonstrate cumulative amplification of 427x (Monte Carlo mean across 1,000 paths), a stochastic filtering phenomenon at upstream tiers (CV = 0.01), super-exponential lead time sensitivity, and scalability to 20.8 million simulation cells in under 7 seconds. Benchmark experiments reveal a 155x disparity between synthetic AR(1) and real WSTS bullwhip severity under the Order-Up-To policy, and quantify the BWR-NSAmp tradeoff across ordering policies, demonstrating that no single metric captures policy quality.
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Traza raises $2.1 million led by Base10 to automate procurement workflows with AI
For decades, procurement has been the back office that enterprise software forgot. Billions of dollars flow through vendor negotiations, purchase orders, and supplier communications every year at the largest manufacturers and construction companies in the country — and the vast majority of that work still runs on email threads, spreadsheets, and phone calls. Traza, a newly launched startup headquartered in New York, believes the moment has arrived to change that. The company announced today the close of a $2.1 million pre-seed round led by Base10 Partners, with participation from Kfund, a16z scouts, Clara Ventures, Masia Ventures, and a roster of angel investors including Pepe Agell, who scaled Chartboost to 700 million monthly users before its acquisition by Zynga. The funding is modest by Silicon Valley standards. But Traza's pitch is anything but incremental: the company deploys AI agents that don't just recommend procurement actions — they execute them autonomously, handling vendor outreach, request-for-quote generation, order tracking, supplier communications, and invoice processing without continuous human supervision. "AI is redesigning the procurement category from the ground up," said Silvestre Jara Montes, Traza's CEO and co-founder, in an exclusive interview with VentureBeat. "This wave of AI won't just build procurement software — it will rebuild how procurement works." Why procurement contracts silently lose millions after the ink dries The market Traza is targeting is enormous and, by the company's framing, spectacularly underserved. The procurement software market alone exceeds $8 billion and grows at roughly 10% annually. But the real cost sits in the labor — the armies of people, agencies, and ad hoc workarounds required to actually run procurement operations at scale. Most enterprises meaningfully engage with only their top 20% of suppliers. The remaining 80% — the vendor outreach, order tracking, invoice reconciliation, and compliance monitoring — goes largely unmanaged. Research from World Commerce & Contracting and Ironclad finds that organizations lose an average of 11% of total contract value after agreements are signed, a phenomenon described as "post-signature value leakage." As Tim Cummins, President of WorldCC, put it: "The research shows that the 11% value gap is not caused by poor negotiation, but by how contracts are managed after signature." For a large enterprise with $500 million in annual contracted spend, that represents $55 million vanishing each year — not from bad deals, but from the operational void between what gets agreed at the negotiating table and what actually gets executed on the ground. Missed savings, unauthorized changes, and poor renewal planning are responsible for the biggest losses. Jara Montes argues that Traza sits precisely in this gap. "The 11% spans commercial, operational, and compliance leakage. We own the operational layer — and that's where the most recoverable value sits," he said. "Supplier tail management that never happens, RFQ processes skipped because someone ran out of bandwidth, invoice discrepancies that slip through unnoticed. That's where contracts bleed value after signing, and that's exactly what we automate." The numbers from Traza's early deployments, while nascent, are striking: the company claims a 70% reduction in human hours spent on procurement tasks and procurement cycles running three times faster than manual baselines. How AI agents crossed the line from procurement copilot to autonomous worker To understand what makes Traza's approach different, it helps to understand what "AI for procurement" has meant until now. For the past several years, the term largely described dashboards, analytics layers, and recommendation engines that surfaced insights but left every decision and action in a human's hands. Products from incumbents like SAP Ariba and Coupa — as well as newer entrants like Zip, Fairmarkit, and Tonkean — have layered AI capabilities on top of existing systems of record. But the gap between piloting AI and achieving production-scale impact remains stark, with 49 percent of procurement teams running pilots but only 4 percent reaching meaningful deployment. Traza's bet is that 2026 represents an inflection point. AI agents now possess the multi-step reasoning, tool use, and contextual memory required to execute full procurement workflows autonomously — from vendor discovery through invoice processing. The company frames this not as an upgrade to existing procurement software, but as an entirely new product category. "The incumbents built systems of record. They organize procurement data and they've never executed procurement work — and their AI additions don't fundamentally change that," Jara Montes said. "What they're shipping is a recommendation layer on the same underlying architecture. A human still has to act on every suggestion. We replace the operational layer entirely." Industry data supports the thesis that enterprises are hungry for this shift. According to the 2025 Global CPO Survey from EY, 80 percent of global chief procurement officers plan to deploy generative AI in some capacity over the next three years, and 66 percent consider it a high priority over the next 12 months. A 2025 ABI Research survey found that 76% of supply chain professionals already see autonomous AI agents as ready to handle core tasks like reordering, supplier outreach, and shipment rerouting without human intervention — and early deployments are demonstrably reducing supply chain operational costs by 20 to 35%. Inside the workflow: what Traza's AI does and where humans still make the call In a typical deployment, Traza's AI agent takes over the operational labor that currently lives in inboxes, spreadsheets, and manual follow-up chains. In a standard RFQ workflow, the agent identifies suitable suppliers, drafts and sends the request for quotes, monitors supplier responses, follows up automatically when responses lag, parses incoming quotes regardless of their format, and builds a structured comparison table ready for a human decision-maker. The key design principle is deliberate: humans remain in the loop at critical junctures. "At critical steps — approving a purchase order, flagging a compliance issue, committing spend above a threshold — a human is always in the loop," Jara Montes explained. "That's not a limitation, it's the design. It's how you maintain the auditability enterprises require while moving faster than any manual process could. You earn expanded autonomy over time, as trust is built and results compound." When asked about the risk of AI errors — a wrong purchase order or a missed compliance check that could prove costly — Jara Montes was direct: "Anything with meaningful financial or compliance exposure requires human approval before it executes — that's non-negotiable and baked into the architecture. Below those thresholds, the agent acts autonomously and logs everything." He added a point that reveals a subtler product insight: "Most procurement operations today are a black box — nobody has a clear picture of what's happening across the supplier tail. We make it legible." In other words, the transparency the AI agent provides may itself be a product — giving procurement leaders visibility they have never had into the long tail of supplier relationships that most enterprises simply ignore. How Traza plugs into legacy enterprise systems without ripping them out One of the recurring challenges for any enterprise AI startup is the integration question: How do you plug into the deeply entrenched, often decades-old technology stacks that large manufacturers and construction companies rely on? Traza's answer is to sit on top of existing systems rather than replace them. "We connect via API or direct integration into whatever the customer already runs — ERPs, email, supplier portals. We have reach across more than 200 enterprise tools," Jara Montes said. "We don't rip out their system, we sit on top of them." The go-to-market motion mirrors this pragmatism. Instead of attempting a big-bang deployment, Traza runs a two-to-three-month proof of value focused on a single, specific workflow. Integrations are built at the key steps that matter for that particular use case, then expanded as the scope of the engagement grows. "We don't try to connect everything upfront — we compound integrations as we expand scope within each account," Jara Montes said. "And every integration we build compounds across customers too. Each new deployment makes the next one faster." Throughout the process, the company works side by side with the customer's team, managing complexity and helping them transition into a new way of operating. It is a notably high-touch approach for a company selling automation. The company is already working with large manufacturers and construction companies and says they are paying, though it declines to name them publicly. "We want to earn the right to grow inside each account, not land a pilot that goes nowhere," Jara Montes said. "That's how you build something that actually sticks in enterprise." Traza bets that vertical depth in physical industry will beat horizontal AI platforms Traza enters a market that is rapidly heating up. The leading AI procurement solutions include platforms from Coupa, Ivalua, SAP Ariba, Zip, Zycus, and Fairmarkit. Keelvar provides autonomous sourcing bots capable of launching RFQs, collecting bids, and recommending optimal awards, while Tonkean offers a no-code orchestration platform using NLP and generative AI to streamline procurement intake and tail-spend management. Against this crowded field, Jara Montes draws a sharp distinction between horizontal automation tools and Traza's focus on physical industry. "We're built specifically for the physical industry, where supplier relationships, compliance requirements, and workflow complexity are categorically different from software procurement," he said. "A generic agent doesn't survive contact with how procurement actually works in manufacturing or construction. Specificity is the moat." The competitive dynamics with major incumbents are perhaps even more consequential. SAP Ariba, Coupa, and their peers have massive installed bases and deep enterprise relationships. Jara Montes frames their AI initiatives as surface-level additions to legacy architectures — but whether Traza can convert that framing into market share at scale, especially given the gravitational pull of existing vendor relationships, remains the central strategic question. Beneath Traza's product pitch sits a deeper strategic thesis about compounding data advantages. The company describes a two-layered learning architecture: at the agent level, Traza gets smarter across every deployment by absorbing supplier behavior patterns, RFQ response dynamics, pricing anomalies, and workflow edge cases. At the data level, each customer's information stays fully isolated. "What we're building is deep operational knowledge of how procurement actually runs in the physical industry — not how it's supposed to run according to an RFP, but how it really runs, with all the exceptions and workarounds," Jara Montes said. "That's extraordinarily hard to replicate if you're starting from scratch, and it gets harder to catch up with the more deployments we have." Three Spanish founders, one fellowship, and a plan to rewire industrial procurement Traza was co-founded by three Spanish entrepreneurs — Silvestre Jara Montes, Santiago Martínez Bragado, and Sergio Ayala Miñano — who came to the United States through the Exponential Fellowship, a program that brings Europe's top technical talent to the U.S. to build companies at the frontier of AI. Their backgrounds span both sides of the problem Traza is trying to solve. Jara Montes worked at Amazon and CMA CGM — one of the world's largest shipping groups — at the intersection of operations strategy and supply chain optimization. Martínez Bragado built and deployed agentic AI at Clarity AI before joining Concourse (backed by a16z, Y Combinator, and CRV) as Founding AI Engineer. Ayala Miñano comes from StackAI, one of the fastest-growing enterprise AI platforms in San Francisco, where he was a Founding Engineer. None of the founders carry the title of Chief Procurement Officer, a gap that the company acknowledges has occasionally surfaced in buyer conversations. Jara Montes's response is characteristically direct: "Our work is the answer. The results we're generating move that conversation quickly." He noted that the company has senior procurement leaders serving as advisors who have run procurement at the scale of its target customers. Base10 Partners, the lead investor, is a San Francisco-based venture capital firm that invests in companies automating sectors of what it calls "the Real Economy." Its portfolio includes Notion, Figma, Nubank, Stripe, and Aurora Solar. Rexhi Dollaku, General Partner at Base10, framed the investment in emphatic terms: "Supply chain and procurement is one of the largest, most underautomated markets in the Real Economy. AI agents are finally capable of doing the work, not just assisting with it." The supporting cast of investors reinforces the immigrant-founder narrative. Clara Ventures — founded by the executives behind Olapic's $130 million exit — specifically invests in driven foreign founders building in the United States, and Agell adds operational credibility from building Chartboost into a $100 million revenue business in under three years as a Spanish founder in Silicon Valley. Why $2.1 million may stretch further than it looks for an enterprise AI startup At $2.1 million, this is a deliberately small round for a company selling to large enterprises with notoriously long procurement cycles. Jara Montes argues it goes further than it appears for structural reasons. "We leverage Europe as a tech talent hub, where we have a deep network of exceptional engineers — people who want to work at the frontier of AI but have far fewer opportunities to do so than their US counterparts," he said. "We're not just lean — we're built to outcompete on capital efficiency while others are burning through runway trying to hire in San Francisco." The go-to-market motion is designed for speed to revenue. Proofs of value are scoped, time-bounded, and converted to paying partnerships. The company says it is not running 18-month enterprise sales cycles before seeing a dollar. The milestone for the next raise is explicit: more paying customers, meaningfully stronger annual recurring revenue, and a repeatable sales motion that makes the seed round, as Jara Montes put it, "an obvious conversation." Looking ahead, he outlined an ambitious three-year target: 20 to 30 large industrial enterprises in the U.S. and Europe running Traza across their procurement operations, with over a billion dollars in procurement spend flowing through the platform. Whether that vision is achievable depends on several interlocking variables — the pace at which AI agent capabilities continue to improve, the speed of enterprise adoption in a traditionally conservative buyer segment, and Traza's ability to navigate the competitive gauntlet of incumbents adding AI features and well-funded startups attacking adjacent workflows. But the underlying math may be on Traza's side. In procurement, the money that disappears does not look like waste. It vanishes into inefficiency, missed obligations, unmanaged risks, and forgotten commitments — the kind of silent losses that no one tracks because no one has the bandwidth to track them. The traditional mandate of procurement, as currently configured, ends where the value gap begins: at signature. Traza is building an AI workforce that picks up where the humans leave off. For an industry that has spent decades losing $55 million at a time to the back office nobody watches, that might be precisely the point.
Korean AI chip startup DEEPX, Hyundai work on robots powered by ...
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Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations
arXiv:2604.09584v1 Announce Type: new Abstract: Flow physics and more broadly physical phenomena governed by partial differential equations (PDEs), are inherently continuous, high-dimensional and often chaotic in nature. Traditionally, researchers have explored these rich spatiotemporal PDE solution spaces using laboratory experiments and/or computationally expensive numerical simulations. This severely limits automated and large-scale exploration, unlike domains such as drug discovery or materials science, where discrete, tokenizable representations naturally interface with large language models. We address this by coupling multi-agent LLMs with latent foundation models (LFMs), a generative model over parametrised simulations, that learns explicit, compact and disentangled latent representations of flow fields, enabling continuous exploration across governing PDE parameters and boundary conditions. The LFM serves as an on-demand surrogate simulator, allowing agents to query arbitrary parameter configurations at negligible cost. A hierarchical agent architecture orchestrates exploration through a closed loop of hypothesis, experimentation, analysis and verification, with a tool-modular interface requiring no user support. Applied to flow past tandem cylinders at Re = 500, the framework autonomously evaluates over 1,600 parameter-location pairs and discovers divergent scaling laws: a regime-dependent two-mode structure for minimum displacement thickness and a robust linear scaling for maximum momentum thickness, with both landscapes exhibiting a dual-extrema structure that emerges at the near-wake to co-shedding regime transition. The coupling of the learned physical representations with agentic reasoning establishes a general paradigm for automated scientific discovery in PDE-governed systems.
China Dominates Global AI Metrics, Stanford Report Finds - Los Angeles Today
A new report from Stanford University's Institute for Human-Centered AI has found that China leads the world across key metrics in artificial intelligence, including publication volume, citation counts, total patent output, and industrial robot installations.
AHC: Meta-Learned Adaptive Compression for Continual Object Detection on Memory-Constrained Microcontrollers
arXiv:2604.09576v1 Announce Type: new Abstract: Deploying continual object detection on microcontrollers (MCUs) with under 100KB memory requires efficient feature compression that can adapt to evolving task distributions. Existing approaches rely on fixed compression strategies (e.g., FiLM conditioning) that cannot adapt to heterogeneous task characteristics, leading to suboptimal memory utilization and catastrophic forgetting. We introduce Adaptive Hierarchical Compression (AHC), a meta-learning framework featuring three key innovations: (1) true MAML-based compression that adapts via gradient descent to each new task in just 5 inner-loop steps, (2) hierarchical multi-scale compression with scale-aware ratios (8:1 for P3, 6.4:1 for P4, 4:1 for P5) matching FPN redundancy patterns, and (3) a dual-memory architecture combining short-term and long-term banks with importance-based consolidation under a hard 100KB budget. We provide formal theoretical guarantees bounding catastrophic forgetting as O({\epsilon}{sq.root(T)} + 1/{sq.root(M)}) where {\epsilon} is compression error, T is task count, and M is memory size. Experiments on CORe50, TiROD, and PASCAL VOC benchmarks with three standard baselines (Fine-tuning,EWC, iCaRL) demonstrate that AHC enables practical continual detection within a 100KB replay budget, achieving competitive accuracy through mean-pooled compressed feature replay combined with EWC regularization and feature distillation.
Google Invests $10M to Train 40,000 Manufacturing Workers in AI Skills (2026)
Google Invests $10M to Train 40,000 Manufacturing Workers in AI Skills (2026) { style = event.detail.style; message = event.detail.message; show = true; }); "> # Google Invests $10M to Train 40,000 Manufacturing Workers in AI Skills (2026) The AI Skills Train for a New American Factory Town Hall Personally, I think Google’s latest move is more than a funding gimmick. It’s a deliberate bet on a future where the factory floor isn’t a relic but a rapidly evolving, AI-augmented workspace. The core idea is simple on the surface: teach 40,000 manufacturing workers AI literacy and connect them to deeper apprenticeship tracks across the country. What makes it interesting is what this implies about who owns the future of production—and who pays for the education required to participate in it. A practical reboot of shop floor intelligence What makes this program notable is not just the scale,
Tesla leader believes Shanghai factory operations will play a role in ...
Tesla leader believes Shanghai factory operations will play a role in robot mass production - The Washington Post Democracy Dies in Darkness By Andy Wong and Kanis Leung | AP SHANGHAI — A Tesla Inc. leader said Tuesday he believes its Shanghai factory operations will help resolve the challenges in achieving mass production of the company’s humanoid robots as the U.S. electric vehicle giant pivots to robotics.
AI Arms Race Triggers $143 Billion Explosion In Chip Gear Spending - Applied Materials (NASDAQ:AMAT) - Benzinga
AI Arms Race Triggers $143 Billion Explosion In Chip Gear Spending - Applied Materials (NASDAQ:AMAT) - Benzinga My Account --- Login LoginRegister Trade Ideas Stock of the Day Best Stocks & ETFs Best S&P 500 ETFs Best Swing Trade Stocks Best Blue Chip Stocks Best High-Volume Penny Stocks Best Small Cap ETFs Best Stocks to Day Trade Trade Ideas Stock of the Day Best Stocks & ETFs [Best S&P 500 ETFs](https://www.benzinga.com/money/best-s
Google Expands AI Education With New Manufacturing Training Program
Google Expands AI Education With New Manufacturing Training Program ## Google Expands AI Education With New Manufacturing Training Program #### By Madelaine Panganiban Google is investing $10 million to expand artificial intelligence education for manufacturing workers, aiming to train about 40,000 people across the United States. The funding will support a new program developed with the Manufacturing Institute, a workforce and education partner of the National Association of Manufacturers. The money comes from Google.org's AI Opportunity Fund and will help create new training courses focused on real-world factory work. According to Maggie Johnson, global head of Google.org, the goal is to bring practical AI skills directly to workers. "Through this ini
Agentic AI in Engineering and Manufacturing: Industry Perspectives on Utility, Adoption, Challenges, and Opportunities
arXiv:2604.09633v1 Announce Type: new Abstract: This work examines how AI, especially agentic systems, is being adopted in engineering and manufacturing workflows, what value it provides today, and what is needed for broader deployment. This is an exploratory and qualitative state-of-practice study grounded in over 30 interviews across four stakeholder groups (large enterprises, small/medium firm
Structural Consequences of Policy-Based Interventions on the Global Supply Chain Network
arXiv:2604.11479v1 Announce Type: cross Abstract: As global political tensions rise and the anticipation of additional tariffs from the United States on international trade increases, the issues of economic independence and supply chain resilience become more prominent. The importance of supply chain resilience has been further underscored by disruptions caused by the COVID-19 pandemic and the ongoing war in Ukraine.In light of these challenges, ranging from geopolitical instability to product supply uncertainties, governments are increasingly focused on adopting new trade policies. This study explores the impact of several of these policies on the global electric vehicle (EV) supply chain network, with a particular focus on their effects on country clusters and the broader structure of international trade. Specifically, we analyse three key policies: Country Plus One, Friendshoring, and Reshoring. Our findings show that Friendshoring, contrary to expectations, leads to greater globalisation by increasing the number of supply links across friendly countries, potentially raising transaction costs. The Country Plus One policy similarly enhances network density through redundant links, while the Reshoring policy creates challenges in the EV sector due to the high number of irreplaceable products. Additionally, the effects of these policies vary across industries; for instance, mining goods being less affected in Country Plus One than the Friendshoring policy.
The AI build-out is powering global goods trade
Data centre boom is helping to mask the impact of Trump tariffs on US and world economy
Steel giants, automakers, and banks plan to build Japan's answer to US and Chinese AI dominance
Steel giants, automakers, and banks plan to build Japan's answer to US and Chinese AI dominance # Steel giants, automakers, and banks plan to build Japan's answer to US and Chinese AI dominance Apr 13, 2026 Softbank is uniting Japan's industrial elite to build the country's own AI foundation, trying to reduce dependence on American and Chinese models. Eight Japanese corporations, including NEC, Honda, Sony, three major banks, Nippon Steel, and Kobe Steel, have invested in a new Softbank unit. The goal is to develop a foundation model with roughly one trillion parameters by the end of the decade. The project focuses on "Physical AI," meaning artificial intelligence that can autonomously control robots and machinery. Even large Japanese companies increasingly rely on foundation models from OpenAI, Anthropic, or Alibaba. But as AI handles more sensitive data like the operational status
LG Energy Solution chief eyes 50% productivity boost with AI - The Korea Herald
LG Energy Solution CEO Kim Dong-myung said Monday that the South Korean battery maker aims to boost overall productivity by 50 percent by 2028 through an aggres
Global chip equipment sales reach record US$135 billion as AI drives investment surge
Worldwide semiconductor manufacturing equipment sales rose 15% to a record US$135.1 billion in 2025 from US$117.1 billion a year earlier, driven by investment in advanced logic, memory, and AI-related capacity expansion, SEMI, the global semiconductor industry association, said.
Transforming industries with physical AI
Transforming industries with physical AI Article Apr 13, 2026 # Transforming industries with physical AI Cisco’s Vikas Butaney on the 2026 State of Industrial AI Report — and what it takes to be an AI ‘pacesetter’. In complex, rugged environments like manufacturing floors, container-ship ports, or power utilities, AI has an essential role to play. But Cisco’s 2026 State of Industrial AI Report reveals that while 61 percent of industrial users are actively deploying physical AI, only 20 percent have successfully scaled the technology. The study, which surveyed 1,000 industrial professionals across 19 countries and 21 sectors, delved into what’s holding many organizations back — and what the mature “pacesetters” are doing right. For further insight, we turned to Vikas But
India’s manufacturing giants are embracing agentic AI to enhance efficiencies | Mint
The manufacturing sector is evolving from automation to an Agentic Enterprise model, where AI acts as a strategic teammate, enhancing decision-making and logistics. This shift requires reskilling workers, integrating AI into daily operations, and addressing data security risks.
How manufacturers are testing physical AI before making big investments | Manufacturing Dive
Growing interest in automation has created a need for testing centers to let manufacturers see if the technology will work for them. Deloitte, Tata Consultancy Services and Microsoft are among them.
3D Machine Vision Market Set for Transformational Growth as Automation and AI Redefine Global Manufacturing Ecosystems - Industry Today
3D Machine Vision Market outlook to 2031 driven by automation, AI vision systems, and smart manufacturing adoption across global industries.
AI boom widens US trade deficit by $200 billion; Mexico, Taiwan dominate AI trade: Study - BusinessToday
AI-related products accounted for 23 percent of total US imports in 2025, up sharply from 15 percent in 2023, reflecting a structural shift in trade composition.
Google commits $10M to Manufacturing Institute for AI worker training
Google commits $10M to Manufacturing Institute for AI worker training | Fox Business ### Recommended Videos #### Former NASA astronaut says human spaceflight ‘fuels’ US economy #### Trump draws hard red line on Iran nukes, demands ‘everything’ in high stakes talks #### Elon Musk's next big bet: Inside the rise of SpaceX #### Magnificent 7 stocks are back in style #### AI investing playbook: Quality companies vs overvalued tech #### Portfolio manager shares energy investment opportunities amid Hormuz uncertainty #### BlackBerry CEO speaks on Anthropic's AI cybersecurity model and QNX systems #### Drone food deliveries take off in the Northeast #### US is ready to land ‘boots on the moon,’ says Texas congressman #### Wonder launches drone program in New Jersey to deliver food #### Food deliveries take flight in New Jersey #### This is where investors can find opportunity ####
Chinese premier urges policy coordination, AI integration at economic meeting
Premier Li Qiang urged better policy coordination and deeper integration of artificial intelligence and manufacturing during a meeting with economists and entrepreneurs.
Industrial Automation: From Control to Intelligence | Bain & Company
AI is reshaping the automation value pyramid into an hourglass.
The $11 Billion Power Play: How Infrastructure and Data Centers are Fueling the 2026 Equipment Surge | Simplified Capital
dream…grow…succeed [NEWS ALERT: FEBRUARY VOLUME HITS RECORD $11 BILLION ... CONSTRUCTION SECTOR GROWTH AT 22.2% YTD ... DATA CENTERS AND ENERGY INFRASTRUCTURE DRIVING HISTORIC DEMAND ... SIMPLIFIED CAPITAL ANALYSIS ...] Breaking: The Equipment Market Just Shattered Expectations If you’ve ...
AI Skills Training | The Manufacturing Institute
AI Skills Training | The Manufacturing Institute Manufacturers know better than anyone how quickly technology is changing. Artificial intelligence is rapidly becoming a larger part of modern manufacturing—from machine learning that improves predictive maintenance, to tools that optimize production and quality in real time. While AI's impact is unfolding, waiting isn't an option. In fact, a key barrier to faster adoption is preparing manufacturing's frontline workforce with the skills needed to succeed in an AI-enabled future. After all, manufacturing in America is human-led. Without these skills, manufacturers risk falling behind, while those who embrace AI will strengthen overall competitiveness. But manufacturers don't have to figure it out alone. The Manufacturing Institute is stepping forward to ensure workforce preparation keeps pace. ## What We're Doing The Manufacturing Insti
india manufacturing growth: India wants manufacturing at 25% of GDP — will AI in factories help? - The Economic Times Video | ET Now
What does it take to move India's manufacturing from 16% to 25% of GDP? Two industry heavyweights, Vinod Kumar, Partner & Leader – Manufacturing,PwC India and Srihari Kaninghat, Group Chief Digital Officer, JSW Group sit down with host Anirban Chowdhury to cut through the hype and get real ...
Taiwan's chip program covers 200+ high-end devices to boost advanced IC design talent
The Chip-based Industrial Innovation Program (Taiwan CBI), a decade-long, NT$300 billion (US$9.4 billion) initiative launched by the Executive Yuan to support academic and research institutions in acquiring costly semiconductor equipment, has begun to achieve initial results.
New York Invests in Next-Gen Chip Manufacturing - NYC Today
New York Invests in Next-Gen Chip Manufacturing - NYC Today By the People, for the People News More # New York Invests in Next-Gen Chip Manufacturing Albany NanoTech Complex to host cutting-edge semiconductor research hub Apr. 9, 2026 at 7:52pm Got story updates? Submit your updates here. › A cutting-edge semiconductor fabrication tool, glowing with the promise of next-generation chip technology, signals New York's push to lead the future of computing.NYC Today New York state is making a major investment in the future of semico
Industrial AI moves into physical operations - IT-Online
AI is now delivering measurable operational benefits in use cases such as process automation, automated quality inspection, predictive maintenance, logistics, and energy forecasting says the latest Cisco State of Industrial AI Report. However, many organisations are increasingly constrained ...
Norwegian Kilter secures €6.5 million to expand autonomous weeding technology globally
– Advertisement – Norwegian agtech company Kilter has raised €6.5 million in new financing in a strategic round that includes a lead investment from Japanese agricultural machinery group Kubota Corporation alongside continued participation from existing shareholders such as Pymwymic, SBG Invest, and Nufarm. The company, which develops autonomous precision weeding and spraying systems for row […]
Automotive Engineering-Centric Agentic AI Workflow Framework
Engineering workflows such as design optimization, simulation-based diagnosis, control tuning, and model-based systems engineering (MBSE) are iterative, constraint-driven, and shaped by prior decisions. Yet many AI methods still treat these activities as isolated tasks rather than as parts of a broader workflow. This paper presents Agentic Engineering Intelligence (AEI), an industrial vision framework that models engineering workflows as constrained, history-aware sequential decision processes i...
Toward Generalizable Graph Learning for 3D Engineering AI: Explainable Workflows for CAE Mode Shape Classification and CFD Field Prediction
Automotive engineering development increasingly relies on heterogeneous 3D data, including finite element (FE) models, body-in-white (BiW) representations, CAD geometry, and CFD meshes. At the same time, engineering teams face growing pressure to shorten development cycles, improve performance and accelerate innovation. Although artificial intelligence (AI) is increasingly explored in this domain, many current methods remain task-specific, difficult to interpret, and hard to reuse across develop...
FANUC, NVIDIA Partner to Advance Physical AI in Industrial Robotics | ASSEMBLY
ROCHESTER HILLS, MI — FANUC America is collaborating with NVIDIA to advance the use of physical AI in industrial robotics, combining automation systems with AI computing and simulation technologies to support more adaptive manufacturing environments.
Peace President's Iran war piles more pain on already battered PC market
Memory costs were already through the roof - now freight's spiking too, and budget systems face extinction America's war with Iran is jacking up the pressure on computing markets already struggling with memory shortages and component cost inflation, meaning buyers should brace themselves for even higher prices this year.…
Kia delays launch of software-focused cars, unveils big hike to investment plans
South Korea's Kia Corp said on Thursday it had delayed plans to build 'software-defined vehicles' by about one year to 2028, and announced a hefty hike in investment plans, underscoring its struggles to catch up with the likes of Tesla.
Asian start-ups evolve to reshape industries with AI
Entrepreneurs focus on improving established sectors including logistics, manufacturing and healthcare
Cyngn Accelerates Autonomous Vehicle Adoption in 2026
Cyngn reported continued commercial expansion as industrial AI adoption shifts from isolated pilots to scaled deployment across enterprise operations.
Semiconductor equipment billings surge to $135B in 2025 – ICO Optics
And for policymakers or industry groups, there’s a lot to do—think supply-chain resilience, investment incentives, and talent pipelines—if innovation in AI hardware, memory, and advanced packaging is going to keep up this pace. Here is the source article for this story: Semiconductor ...
Data Centers, AI Boom Tests Limits on Power, Trade in Texas
Others said AI could boost productivity and create new demand in areas tied to infrastructure and construction. “You’re going to see trades being revitalized,” said state Rep. Keith Bell, a Republican who works as an electrical contractor. For Texas, the stakes are high. The state’s energy resources, business climate, and population growth have made it a magnet for both data centers ...
Trelleborg Sealing Solutions in India Breaks Ground on Expanded New Manufacturing Facility in Bengaluru | RoboticsTomorrow
The facility campus spans 50,000 square meters/540,000 square feet and is scheduled for completion in 2027. It brings together comprehensive manufacturing capabilities, R&D with extensive testing facilities, application engineering support, the Customer Solutions Center, supply chain center ...
Beyond LLMs: Why industrial AI Is India's real AI opportunity?
We will need smart factories that use self-correcting, AI-driven infrastructure. Technology to make this happen exists today. Industrial AI is the real AI opportunity.
KD-MARL: Resource-Aware Knowledge Distillation in Multi-Agent Reinforcement Learning
arXiv:2604.06691v1 Announce Type: new Abstract: Real world deployment of multi agent reinforcement learning MARL systems is fundamentally constrained by limited compute memory and inference time. While expert policies achieve high performance they rely on costly decision cycles and large scale models that are impractical for edge devices or embedded platforms. Knowledge distillation KD offers a promising path toward resource aware execution but existing KD methods in MARL focus narrowly on action imitation often neglecting coordination structure and assuming uniform agent capabilities. We propose resource aware Knowledge Distillation for Multi Agent Reinforcement Learning KD MARL a two stage framework that transfers coordinated behavior from a centralized expert to lightweight decentralized student agents. The student policies are trained without a critic relying instead on distilled advantage signals and structured policy supervision to preserve coordination under heterogeneous and limited observations. Our approach transfers both action level behavior and structural coordination patterns from expert policies while supporting heterogeneous student architectures allowing each agent model capacity to match its observation complexity which is crucial for efficient execution under partial or limited observability and limited onboard resources. Extensive experiments on SMAC and MPE benchmarks demonstrate that KD MARL achieves high performance retention while substantially reducing computational cost. Across standard multi agent benchmarks KD MARL retains over 90 percent of expert performance while reducing computational cost by up to 28.6 times FLOPs. The proposed approach achieves expert level coordination and preserves it through structured distillation enabling practical MARL deployment across resource constrained onboard platforms.
Infrastructure First: Enabling Embodied AI for Science in the Global South
arXiv:2604.06722v1 Announce Type: new Abstract: Embodied AI for Science (EAI4S) brings intelligence into the laboratory by uniting perception, reasoning, and robotic action to autonomously run experiments in the physical world. For the Global South, this shift is not about adopting advanced automation for its own sake, but about overcoming a fundamental capacity constraint: too few hands to run too many experiments. By enabling continuous, reliable experimentation under limits of manpower, power, and connectivity, EAI4S turns automation from a luxury into essential scientific infrastructure. The main obstacle, however, is not algorithmic capability. It is infrastructure. Open-source AI and foundation models have narrowed the knowledge gap, but EAI4S depends on dependable edge compute, energy-efficient hardware, modular robotic systems, localized data pipelines, and open standards. Without these foundations, even the most capable models remain trapped in well-resourced laboratories. This article argues for an infrastructure-first approach to EAI4S and outlines the practical requirements for deploying embodied intelligence at scale, offering a concrete pathway for Global South institutions to translate AI advances into sustained scientific capacity and competitive research output.
NVIDIA Corporation (NASDAQ:NVDA), Amkor Technology, Inc. (NASDAQ:AMKR) - AI's Hidden Choke Point: Why US-Made Chips Still Depend On Taiwan | Benzinga
NVIDIA Corporation (NASDAQ:NVDA), Amkor Technology, Inc. (NASDAQ:AMKR) - AI's Hidden Choke Point: Why US-Made Chips Still Depend On Taiwan | Benzinga Skip to main content ## Market Overview Tickers, Articles and Keywords: ## Tickers ## Articles ## Keywords Search by keyword... googlecse {{following ? "Following" : "Follow"}} 548 Comments Share: As the artificial intelligence boom accelerates, a little-known step in chipmaking is emerging as a critical choke point: advanced packaging. Even the most cutting-edge semiconductors manufactured in the U.S. are still being shipped to Asia—primarily Taiwan—for final assembly, exposing a fragile supply chain just as demand from Nvidia Corp. NVDA), Intel Corp. INTC), and Tesla Inc. [TSLA](https://www.benzinga.
Coherent Advances Silicon Carbide Thick Epitaxy Capabilities for High-Voltage AI Datacenter and ... | Technology | postregister.com
Coherent Advances Silicon Carbide Thick Epitaxy Capabilities for High-Voltage AI Datacenter and ... | Technology | postregister.com You have permission to edit this article. #### Post Register Share This This website uses certain cookies, pixels and similar tracking technologies in order enhance site navigation, analyze site usage, and assist in our marketing efforts. Certain information collected by that technology may be shared with our third party partners. By continuing to use this website, you agree to the use of these technologies. SAXONBURG, Pa., April 09, 2026 (GLOBE NEWSWIRE) -- Coherent Corp. (NYSE: COHR), a global leader in photonics, today announced advancements in its silicon carbide (SiC) epitaxy capabilities, enabling power devices up to 10kV for next-generation AI datacenter and industrial power applications. As industrial electrification accelerates, demand is risi
Treon Secures €6.8 Million Investment Led by ACME Capital to Accelerate Industrial AI Innovation
TAMPERE, Finland, April 8, 2026 /PRNewswire/ — Treon, a leader in AI–native Smart Industry solutions, today announced a strategic investment led by Silicon Valley–based ACME Capital as part of its Series A extension. The investment will further strengthen Treon’s position as the emerging intelligence layer for factories, logistics environments, and OEM equipment, while accelerating its […]
AI Scale Hinges on Infrastructure
Cisco's State of Industrial AI Report reveals that infrastructure readiness, including connectivity and cybersecurity, is crucial for scaling AI in industrial settings.
AI Boom Fuels Growth for Applied Materials
Applied Materials and Lam Research are thriving amid AI-driven semiconductor growth, with significant revenue and margin projections for 2026.
Intel Joins Elon's Megafab Delusions with AI
Intel gets trapped in Elon's reality distortion field as it joins in megafab delusions. Space is just the next stop on the AI hype train, right after AGI.
Lawmakers push to restrict chipmaking equipment exports to China | Manufacturing Dive
The MATCH Act addresses loopholes that allow countries to obtain restricted technology through front companies, subsidiaries and allied countries.
AI Boom Fuels Growth for Applied Materials and Lam Research as Semiconductor Demand Soars
Applied Materials and Lam Research are thriving amid AI-driven semiconductor growth, with significant revenue and margin projections for 2026.
AI Scale Hinges on Infrastructure, Cybersecurity, and IT/OT Collaboration: Cisco Report Reveals Key Insights
Cisco’s State of Industrial AI Report reveals that infrastructure readiness, including connectivity and cybersecurity, is crucial for scaling AI in industrial settings.
AI chip demand tightens ABF substrate supply, three-year upcycle in sight
As AI CPUs, GPUs, and application-specific integrated circuits (ASICs) advance to new generations, they are driving a sharp increase in both substrate size and layer counts. Simultaneously, supply constraints across upstream materials — including glass fiber cloth, copper foil, and drill ...
LG Chairman Kwang Mo Koo Visits Silicon Valley to Accelerate AI Transformation and Physical AI Strategy | RoboticsTomorrow
Chairman Koo met with Alex Karp, founder and CEO of Palantir, and senior executives to discuss Ontology, Palantir's AI- and data-driven decision-making framework, and representative innovation cases enabled by it.
Industrial AI and Security Trends: 2026 Cisco Report
Cisco’s 2026 State of Industrial AI Report shows 61% of organizations have moved AI into live operations, prioritizing automation while facing security hurdles.
AI set to dominate industrial automation revenues by 2030, Bain says | Wealth Professional
The extent to which AI is disrupting ... – manufacturing. A growing share of industrial automation revenue will be powered by AI by the end of the decade, as the sector undergoes a fundamental economic realignment, according to the new research from Bain & Company, underscoring how quickly value is migrating away from traditional hardware-based systems toward software, data, and intelligent ...
Automation progress: Are manufacturing jobs the most vulnerable? - Digital Journal
Automation progress: Are manufacturing jobs the most vulnerable? - Digital Journal Connect with us Hi, what are you looking for? Cranes and building works. Image by Tim Sandle Cranes and building works. Image by Tim Sandle According to an April 2026 report on job automation, patternmakers are threatened the most by automation, with 99% risk. Patternmakers are at the biggest risk of losing jobs due to automation, with employment projected to drop by 24.4% in the next few years. With most job market predictions focusing on AI automation of white-collar occupations, it is the production sector that is in the riskiest position due to manual labour performed more and more by machines. [These data come](https://docs.google.com/spreadsheets/d/e/2PACX-1vS730xNVnu3HhjqApAivsi_M
ReVEL: Multi-Turn Reflective LLM-Guided Heuristic Evolution via Structured Performance Feedback
arXiv:2604.04940v1 Announce Type: new Abstract: Designing effective heuristics for NP-hard combinatorial optimization problems remains a challenging and expertise-intensive task. Existing applications of large language models (LLMs) primarily rely on one-shot code synthesis, yielding brittle heuristics that underutilize the models' capacity for iterative reasoning. We propose ReVEL: Multi-Turn Reflective LLM-Guided Heuristic Evolution via Structured Performance Feedback, a hybrid framework that embeds LLMs as interactive, multi-turn reasoners within an evolutionary algorithm (EA). The core of ReVEL lies in two mechanisms: (i) performance-profile grouping, which clusters candidate heuristics into behaviorally coherent groups to provide compact and informative feedback to the LLM; and (ii) multi-turn, feedback-driven reflection, through which the LLM analyzes group-level behaviors and generates targeted heuristic refinements. These refinements are selectively integrated and validated by an EA-based meta-controller that adaptively balances exploration and exploitation. Experiments on standard combinatorial optimization benchmarks show that ReVEL consistently produces heuristics that are more robust and diverse, achieving statistically significant improvements over strong baselines. Our results highlight multi-turn reasoning with structured grouping as a principled paradigm for automated heuristic design.
Robot Maker Kuka Eyes US, Asia as Europe’s Factories Lag on AI
Many of Europe’s industrial companies are too slow to adopt artificial intelligence, putting faster-moving global rivals in a position to overtake them, according to German-Chinese robotics maker Kuka AG.
10 Federal Appoints Ex-Nvidia Engineer Christopher Taylor as Chief AI Officer
10 Federal Storage has hired former Nvidia engineer Christopher Taylor to lead AI integration efforts across its self-storage operations.
Cerebras Backer Eclipse Raises $1.3 Billion for Robotics, AI Infrastructure
Venture capital firm Eclipse has raised $1.3 billion to invest in startups working in physical industries such as artificial intelligence infrastructure, manufacturing and defense.
NeuBird AI Launches Falcon Agent with $19.3M Boost, Aiming to Revolutionize Production Operations
NeuBird AI has launched Falcon, an autonomous operations agent, alongside $19.3 million in funding to help companies save engineering time.
Supermicro launches internal probe of alleged AI chip diversion scheme
Supermicro confirmed that an independent investigation is underway regarding the March 2026 indictment of three individuals who were associated with the company at that time.
Lowe’s is investing $250 million to train plumbers, carpenters, and electricians as its CEO says skilled trades are ‘critical to the future’
Lowe’s CEO Marvin Ellison says AI can’t replace hands-on work or fix labor shortages. The company is quintupling its investment in the skilled trades.