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The latest AI stories, analysis and developments relevant to Manufacturing Industrials — curated daily by Best Practice AI.
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Victory Giant Founder on $2.6 Billion HK Listing, AI Boom
Victory Giant Technology Huizhou Co. surged in its Hong Kong trading debut on Tuesday, after raising $2. 6 billion.
Sight Machine Launches AI Agent Crews
Sight Machine has launched autonomous AI agent crews at Hannover Messe, designed to optimize manufacturing by analyzing industrial data for improved output and cost efficiency.
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
TSMC Stock Price Responds After Firm Posts Record Quarter, Chip Demand Defies Geopolitical Headwinds
Taiwan Semiconductor Manufacturing Company (TPE: 2230) has reported first-quarter 2026 results that beat analyst expectations across every major financial
Soaring Tungsten Adds Impetus to Vietnam Mine Sale Effort
Some 80 kilometers (50 miles) north of Hanoi, in Thai Nguyen province, a massive open-cut mine tears into the landscape. Ringed by dense, green hills, the vast, stepped crater is raw gray and brown. Along its sides, huge trucks creep along, while a murky pool lies stagnant at the bottom.
Stellantis, Microsoft sign five-year partnership for AI push | Reuters
Stellantis and Microsoft said on Thursday they agreed to a five‑year strategic partnership to co-develop artificial intelligence (AI), cybersecurity and engineering capabilities, as the automaker ra.
Intel eases reliance on TSMC with 'Merica-made Core Series 3 processors
Stripped-down Ultra for laptops and low-power edge boxes Intel brought a few more chips home from Taiwan this week, with a new round of budget-oriented Core Series 3 processors fabbed right in the US-of-A.…
Musk Asks Suppliers to Move at 'Light Speed' on New Chipmaking Plan
Elon Musk's Terafab initiative aims to build a vertically integrated semiconductor complex to support massive AI compute capacity for Tesla, SpaceX, and xAI.
Tongfu Microelectronics profit jumps on AI chip packaging, AMD demand
Tongfu Microelectronics posted strong 2025 results, supported by AI and automotive chip demand, while reinforcing its position in the global semiconductor packaging supply chain alongside key customer AMD.
Winmate and Blaize Partner for Edge AI
Winmate and Blaize are partnering to integrate rugged platforms with AI inference technology for defense and healthcare.
Humanoids turn AI’s grand ambition physical
The race to give AI a body is accelerating as humanoid robotics technology advances.
Hong Kong to host China's chip hub as Beijing seeks tech edge
Hong Kong is set to host a national manufacturing-innovation center focused on power semiconductors to support China's drive for semiconductor self-sufficiency.
Shanghai Unveils World's First Large-Scale Deployment of AI-Driven Humanoid Robots in Electronics Manufacturing
AGIBOT's G2 humanoid robots are now operational on a high-speed electronics line in Shanghai, marking a milestone in AI-driven manufacturing.
Madison Air Soars After Raising $2.23 Billion in IPO
Jill Wyant, president and CEO of Madison Air, talks about the company’s IPO and the growing opportunity in data center infrastructure, including the buildout of Terafabs. The provider of ventilation and filtration systems raised $2.23 billion. Wyant speaks with Ed Ludlow on "Bloomberg Tech." (Source: Bloomberg)
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.
Skild AI Acquires Zebra Technologies’ Robotics Automation Business
Skild AI, a fast-rising startup that makes software to help robots learn to complete tasks, has bought the robotics automation division of Zebra Technologies Corp., marking its latest effort to broaden its reach in a hot segment.
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 ...
Korean AI chip startup DEEPX, Hyundai work on robots powered by generative AI | Reuters Exclusive news, data and analytics for financial market professionalsLearn more aboutRefinitiv The DEEPX booth at the 2025 Korea Tech Festival in Seoul, South Korea, December 4, 2025. REUTERS/Kim Hong-Ji/File Photo Purchase Licensing Rights, opens new tab - Companies Follow Follow Follow Show more companies SEOUL, April 15 (Reuters) - South Korean AI chip startup DEEPX will expand its partnership with Hyundai Motor Group to develop a computing platform for generative AI robots using its second generation of low-power chips, its top executive said, as it gets set for an
Gemini Robotics-ER 1.6: Powering real-world robotics tasks through enhanced embodied reasoning
Google DeepMind has updated its robotics stack to improve embodied AI performance on real-world tasks like instrument reading and environment interpretation.
Monarch Tractors collapse ends in with an acquisition by Caterpillar
Caterpillar has acquired Monarch Tractors following the latter's business collapse.
Nissan to trim global car lineup, boost use of AI driving tech | Reuters
Nissan Motor plans to streamline its global automobile lineup by exiting low-performing ones and deploy its artificial intelligence driving technology across 90% of its array over the long term as it targets a revitalisation after years of turmoil.
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.
Sofia’s nFuse bags €1.7 million to bring AI-powered ordering to fragmented trade, not another app
nFuse, a Sofia-based Intelligent B2B company acting as the ordering and communication layer between brands and their distribution networks, has raised a €1.7 million ($2 million) in investment. The investment was secured from Eleven Ventures and LAUNCHub. The funding will expedite nFuse’s expansion across Europe, with plans to enter broader EMEA and American markets. “Stoyan […] The post Sofia’s nFuse bags €1.7 million to bring AI-powered ordering to fragmented trade, not another app appeared first on EU-Startups.
TE Connectivity CEO: the real promise of AI is long-term transformation, not short-term efficiency gains
Over 80% of industrial engineering firms have adopted AI. But as exec fixate on ROI, they risk missing the infrastructure overhaul required.
AI-RAN is redefining enterprise edge intelligence and autonomy
Presented by Booz Allen AI-RAN, or artificial intelligence radio area networks, is a reimagining of what wireless infrastructure can do. Rather than treating the network as a passive conduit for data, AI-RAN turns it into an active computational layer. It's a sensor, a compute fabric, and a control plane for physical operations, all rolled into one. That shift has huge implications for industries from manufacturing and logistics to healthcare and smart infrastructure. VentureBeat spoke with two leaders at the center of this transformation: Chris Christou, senior vice president at Booz Allen, and Shervin Gerami, managing director at Cerberus Operations Supply Chain Fund. “AI-RAN can bring the promise of extending 5G and eventually 6G networks into the enterprise,” Christou said. “Proving that a platform can host inference at the edge to enable new types of AI — in particular, physical AI and autonomy-type use cases for things like smart manufacturing and smart warehousing — can make operations more efficient and effective.” “AI-RAN lets enterprises move from digitizing processes to autonomously operating them,” Gerami added. "The enterprise investment should not look at AI-RAN as a networking upgrade. It’s an operating system for physical industries." The difference between AI for RAN, AI on RAN, and AI and RAN The difference between AI for RAN, AI on RAN, and AI and RAN is critical. AI on RAN runs enterprise AI workloads on edge compute infrastructure integrated with the RAN, enabling real-time applications like computer vision, robotics, and localized LLM inference. AI and RAN represents the deeper convergence — where networks are designed to be AI-native, with AI workloads and radio infrastructure architected together as a coordinated, distributed system. At this stage, RAN evolves from a transport layer into a foundational layer of the AI economy. "This is the transformational part," Gerami said. "It’s jointly designing applications with networks. Now the application knows the network state, and the network understands the application’s intent. AI for RAN saves money. AI on RAN adds capability. Then AI and RAN together create entirely new business models.” It's this layered framework that makes AI-RAN more than an incremental evolution of existing wireless technology, and instead a platform shift that opens the network to the kind of developer ecosystem and application innovation that has historically been the domain of cloud computing. How ISAC turns the network into a sensor Integrated sensing and communications (ISAC) is the center of the infrastructure. The network becomes the sensor, a converged infrastructure simultaneously communicating and sensing its environment at the same time it hosts algorithms and applications at the edge. It will enable drone detection, pedestrian safety, and automotive sensing, and eventually even more innovative use cases. The enterprise value proposition of ISAC and a network as the sensor is clear, Gerami says. Today, organizations rely on multiple discrete systems to achieve situational awareness: cameras, radar, asset trackers, motion sensors and more. Each comes with its own maintenance burden, integration overhead and vendor relationship. ISAC has the potential to handle many of those capabilities natively within the network. “With ISAC you can do asset tracking at sub-meter precision inside factories and hospitals," he explained. "You can detect movement patterns, perimeter breaches, and anomalies. Smart buildings can have occupancy-aware HVAC and energy optimization." How AI-RAN shaves milliseconds off edge AI and inference With AI-RAN, edge AI and low-latency inference become supercharged in use cases like real-time robotics management, instant quality inspection, and predictive maintenance. There are the applications where the latency gap between cloud and edge is the difference between a system that works and one that doesn’t. “Where edge AI kicks in is driving operations in milliseconds, not seconds, which is what cloud does,” Gerami explained. Split inference can also change the game, Christou says. “You have a lot of different use cases where the processing is done on the device, making that device more expensive and more power-hungry,” he said. “Now there’s the possibility of offloading that to a local AI-RAN stack, even getting into concepts like split inference, so you do some of the inference on the device, some on the edge AI-RAN stack, and some in the cloud, all appropriate to the use cases and the time scale of the processing required.” Why the timing of AI-RAN investment is critical now AI-RAN investment has a narrow and strategically critical window, both Germani and Christou said. “5G infrastructure is already being deployed, almost getting to a point of completion. 6G standards are not yet locked in,” Gerami explained. “This is an architectural moment for AI-RAN to come in. It allows the ability to not make RAN become a telco-centric design only. It allows the enterprise to become the co-creator of the application, the revenue and value generator of that network infrastructure.” Historically, enterprise IT has consumed wireless standards rather than shaped them. AI-RAN’s open architecture, built on software-defined, cloud-native, containerized components, changes that standardization dynamic. “Previously in the wireless industry it was a very long cycle. Now we’re seeing a push to get it implemented, get it out there, get early pilots, and then we’ll see how the technology works," Christou said. Simultaneously, in parallel, you can start defining the standards. You have real-life implementation experience to help influence how those standards take shape.” And the entry point is accessible, Gerami added. “The barrier to entry is very low," he said. "Right now, it’s all code-based, all software. It’s no different than downloading software. You get yourself an Nvidia box and you can deploy it with a radio.” Why AI-RAN is the future of innovative AI use cases “We see AI-RAN as being an open architecture that’s truly driving innovation," Gerami said. "It’s a flywheel for innovation. We want to create everything to be microservices, open native, cloud native, to allow partners to build vertical AI apps. There’s so much focus right now in the industry around how we can adopt AI effectively, how it will enable autonomy and robotics. This is one of those foundational pieces that can help realize some of those use cases. The future is about owning that physical inference.” “There’s so much focus right now in the industry around how we can adopt AI effectively — how it will enable autonomy and robotics," Christou said. "This is one of those foundational pieces that can help realize some of those use cases.” Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.
Apple’s And Its Suppliers Can’t Seem To Agree On The iPhone Fold’s Material Choices And Prices, Putting Its 2026 Launch In Jeopardy
His expertise lies in the intricate hardware supply chain, covering developments in semiconductor manufacturing, chip lithography, and camera sensor technology. Follow Wccftech on Google to get more of our news coverage in your feeds. Read all comments on Apple’s And Its Suppliers Can’t Seem To Agree On The iPhone Fold’s Material Choices And Prices, Putting Its 2026 ...
Helium Crisis Tightens Grip On Global Chip Supply Chain
Helium gas powering the world’s most advanced semiconductor processes is suddenly in short supply, threatening to slow down production of the chips driving the AI boom
Helium Shortage Threatens Semiconductor Supply Chain, Elevates U.S. Supplier Role – ICO Optics
The Oregon Group’s recent research warns that a global helium shortage is disrupting the semiconductor supply chain. This problem is […]
Rare Earth Shortage and Auto Demand Strain Semiconductor Supply - Astute Group
Global electronics and semiconductor supply chains are tightening as rare earth shortages and automotive demand spikes disrupt component availability across multiple sectors. Toyota halted global orders for selected hybrid SUVs in early March 2026 due to component shortages, while semiconductor ...
Cisco Research: Industrial AI Moves into Physical Operations, Readiness Gaps Determine Scale
/PRNewswire/ -- Cisco (NASDAQ: CSCO) today announced the release of its latest annual industrial research report, the State of Industrial AI Report, examining...
Physical AI hits 99% reliability as frontier labs unite
Physical AI hits 99% reliability as frontier labs unite SubscribeSign in Playback speed × Share post Share post at current time Share from 0:00 0:00 / Transcript ## Robots Learn to Improvise - TCR 04/07/26 Physical AI hits 99% reliability as frontier labs unite Apr 07, 2026 Share Transcript A physical AI system reached 99% production reliability while improvising solutions outside its training data, three rival frontier labs began sharing intelligence to defend against Chinese capability extraction, a memristor chip survived 700°C with over a billion switching cycles, Iran explicitly threatened OpenAI’s $30 billion Abu Dhabi data center, and OpenAI published an economic framework proposing robot taxes and a four-day workweek. Generalist’s GEN-1 system crossed a threshold physical AI has been approaching for months: a single model performing diverse manipulation tasks - fo
Samsung forecasts record profit on AI boom
First-quarter earnings surge eightfold despite rising energy costs from Middle East war
Mapping AI into Production: A Field Experiment on Firm Performance
This research studies the mapping problem in AI adoption, finding that firms that identify where AI creates value in production workflows see significant performance gains.
Larry Gies' Madison Air targets $13.2 billion valuation in US IPO
Ventilation and filtration systems provider Madison Air Solutions said it was targeting a valuation of up to $13. 2 billion in its U. S.
Samsung Beats High Estimates After AI Chip Sales Defy War Fears
Samsung Electronics Co. earned a far stronger-than-expected eight-fold leap in quarterly profit, underscoring robust demand for AI memory chips in the face of markets roiled by war in the Middle East.
AI-led demand to drive sharp surge in semiconductor revenues: Goldman Sachs, ETTelecom
Semiconductor Revenues: The surge is being driven by rising demand for AI-linked hardware and infrastructure. Goldman Sachs observed that "AI-related hardware revenues could rise to over $700bn in 2026Q4," underlining the scale of the ongoing investment cycle.
Texas Instruments 2025 Report: AI Drives Data Center Growth & Financial Results - News and Statistics - IndexBox
Texas Instruments' 2025 performance highlights its critical role in AI infrastructure, with data center sales soaring 70%. The report details strong financials, a new US fab, and a 22-year dividend growth streak.
The Ridiculously Nerdy Intel Bet That Could Rake in Billions | WIRED
Advanced chip packaging is suddenly at the center of the AI boom. Intel is going all in.
ASML Lithography Systems: Powering Advanced Chip Production
ASML lithography systems enable the manufacturing of cutting-edge semiconductors used in smartphones, AI, and automotive tech worldwide, holding a dominant position in the global chip supply chain.
Tesla's Bold Move: Building AI Chip Factories in Texas
Tesla and its partners plan to build two AI chip factories near Austin, Texas, to meet semiconductor demand through a fully-integrated approach.
How Rockwell sees industrial AI moving from promise to plant-floor use
Rockwell’s industrial AI strategy centers on uptime, data clarity, machine vision, and OT security. Here’s what that means for real factories.
The price of progress: How manufacturers are weighing AI’s energy demands | Manufacturing Dive
AI and robotics can help save energy by optimizing inefficient systems, but they may also come with larger costs at scale.
AI Is Powering a Blue‑Collar Hiring Boom Few Saw Coming
Demand for electricians, welders, and technicians is surging—putting a hard limit on how fast AI can scale.
Infrastructure Firms Are Winning the AI Transition—But the Productivity Flip Isn’t Here Yet
Infrastructure Firms Are Winning the AI Transition—But the Productivity Flip Isn’t Here Yet
Humanoids are being mispriced as an “AI moment.” They are actually an “industrial governance moment.”
Humanoids are being mispriced as an “AI moment.” They are actually an “industrial governance moment.” # ZenSightful Bytes SubscribeSign in # Humanoids are being mispriced as an “AI moment.” They are actually an “industrial governance moment.” Zen KOH Apr 06, 2026 ∙ Paid Share The humanoid story is being valued as an “AI moment” because that’s the pattern markets know: a new capability appears, distribution expands, unit economics improve with scale. That model fails here. Humanoids are gated by whether a buyer can insure the downside of deploying a moving, learning machine around people—then prove, week after week, that upda… Previous © 2026 Zen KOH · Privacy∙ Terms∙ Collection notice [Start your Substack](https://substack.com/signup?
Driving intelligent automotive manufacturing: How robotics and AI are transforming OEM operations - Capgemini Canada - English
Explore how robotics, agentic AI, and liquid neural networks are revolutionizing automotive production. Discover the future of intelligent manufacturing now.
Arm’s Agentic AI CPU: Engineering the Next Generation of AI Data Centers - Tech Briefs
Arm’s Agentic AI CPU: Engineering the Next Generation of AI Data Centers - Tech Briefs Arm CEO Rene Haas holds the new Arm Agentic AI CPU during his live-streamed keynote for the “Arm is Everywhere” event. (Image: Arm) This episode of the Aerospace & Defense Technology podcast features highlights from Arm CEO Rene Haas’ keynote at the recent live‑streamed Arm is Everywhere event, during which he outlined how agentic AI is reshaping the future of compute. The discussion centers on Arm’s landmark move into silicon with the launch of its Arm agentic AI central processing unit (CPU), purpose‑built for next‑generation AI data centers. We also connect those developments to growing U.S. military interest in AI‑driven decision‑making, resilient compute infrastructure, and energy‑efficient data centers that can operate at scale. It’s a t
Generalist releases highly capable GEN-1 robotic intelligence AI foundation model
Artificial intelligence startup Generalist AI Inc., a startup focused on embodied robotics intelligence, has released GEN-1, a highly capable foundation model for robot learning and mastery of physical tasks. The new model, which debuted Friday, arrives merely five months after the company launched GEN-0, a new class of robotics foundation model that allowed the company to […] The post Generalist releases highly capable GEN-1 robotic intelligence AI foundation model appeared first on SiliconANGLE.
Enhance manufacturing efficiency with AI - Capgemini Canada - English
Agentic AI can help to address many of the automotive industry’s hardest manufacturing challenges. Explore how.
AIVV: Neuro-Symbolic LLM Agent-Integrated Verification and Validation for Trustworthy Autonomous Systems
arXiv:2604.02478v1 Announce Type: new Abstract: Deep learning models excel at detecting anomaly patterns in normal data. However, they do not provide a direct solution for anomaly classification and scalability across diverse control systems, frequently failing to distinguish genuine faults from nuisance faults caused by noise or the control system's large transient response. Consequently, because algorithmic fault validation remains unscalable, full Verification and Validation (V\&V) operations are still managed by Human-in-the-Loop (HITL) analysis, resulting in an unsustainable manual workload. To automate this essential oversight, we propose Agent-Integrated Verification and Validation (AIVV), a hybrid framework that deploys Large Language Models (LLMs) as a deliberative outer loop. Because rigorous system verification strictly depends on accurate validation, AIVV escalates mathematically flagged anomalies to a role-specialized LLM council. The council agents perform collaborative validation by semantically validating nuisance and true failures based on natural-language (NL) requirements to secure a high-fidelity system-verification baseline. Building on this foundation, the council then performs system verification by assessing post-fault responses against NL operational tolerances, ultimately generating actionable V\&V artifacts, such as gain-tuning proposals. Experiments on a time-series simulator for Unmanned Underwater Vehicles (UUVs) demonstrate that AIVV successfully digitizes the HITL V\&V process, overcoming the limitations of rule-based fault classification and offering a scalable blueprint for LLM-mediated oversight in time-series data domains.
Tesla Builds AI Chip Factories
Tesla and partners plan two AI chip factories near Austin, Texas, aiming to meet demand for AI semiconductors with a unique, fully-integrated approach.
Interpretable Deep Reinforcement Learning for Element-level Bridge Life-cycle Optimization
arXiv:2604.02528v1 Announce Type: new Abstract: The new Specifications for the National Bridge Inventory (SNBI), in effect from 2022, emphasize the use of element-level condition states (CS) for risk-based bridge management. Instead of a general component rating, element-level condition data use an array of relative CS quantities (i.e., CS proportions) to represent the condition of a bridge. Although this greatly increases the granularity of bridge condition data, it introduces challenges to set up optimal life-cycle policies due to the expanded state space from one single categorical integer to four-dimensional probability arrays. This study proposes a new interpretable reinforcement learning (RL) approach to seek optimal life-cycle policies based on element-level state representations. Compared to existing RL methods, the proposed algorithm yields life-cycle policies in the form of oblique decision trees with reasonable amounts of nodes and depth, making them directly understandable and auditable by humans and easily implementable into current bridge management systems. To achieve near-optimal policies, the proposed approach introduces three major improvements to existing RL methods: (a) the use of differentiable soft tree models as actor function approximators, (b) a temperature annealing process during training, and (c) regularization paired with pruning rules to limit policy complexity. Collectively, these improvements can yield interpretable life-cycle policies in the form of deterministic oblique decision trees. The benefits and trade-offs from these techniques are demonstrated in both supervised and reinforcement learning settings. The resulting framework is illustrated in a life-cycle optimization problem for steel girder bridges.
Semiconductors Near $1 Trillion as AI Chips Drive Fragile, One-Theme Boom
Semiconductors Near $1 Trillion as AI Chips Drive Fragile, One-Theme Boom Symbols Symbols # Semiconductors Near $1 Trillion as AI Chips Drive Fragile, One-Theme Boom Generated by AI Agent Marcus Lee Reviewed by AInvest News Editorial Team Monday, Apr 6, 2026 3:25 am ET5min read AI Podcast:Your News, Now Playing Loading Aime Summary OverviewThe 5 WsOpposite SidesInfobox - Semiconductor sales hit $1 trillion in 2026, driven by AI chips, with AI-related demand accounting for nearly half of industry revenue. - Market consolidation sees top ten firms capturing most revenue, led by memory suppliers and AI leaders like NVIDIA NVDA--. - Risks include over-reliance on AI, energy c
Japan Deploys Physical AI Robots to Fill Labor Shortage Gaps, Not Replace Workers
Japan Deploys Physical AI Robots to Fill Labor Shortage Gaps, Not Replace Workers Sponsored by Video Watermark Remover - AI Video Watermark Remover – Clean Sora 2 & Any Video Watermarks! Video Watermark Remover - AI Video Watermark Remover – Clean Sora 2 & Any Video Watermarks! AI Tools AI Agents MCP AI News Ranking Submit & Advertise EN ## The New Wave of Embodied AI in Japan The landscape of artificial intelligence is undergoing a profound transformation. While the past few years have been dominated by the rapid evolution of large language models (LLMs) and generative text engines, the frontier of innovation has shifted toward the tangible. In Japan, this movement is no longer theoretical; it is a critical infrastructure strategy. As the country grapples with an acute labor shortage driven by a shrinking and aging population, Japan is rapidly
Foxconn first-quarter revenue jumps, company cautions on ...
Foxconn first-quarter revenue jumps, company cautions on geopolitics | Reuters Exclusive news, data and analytics for financial market professionalsLearn more aboutRefinitiv Foxconn Chairman Young Liu speaks to members of the press at New Taipei City, Taiwan March 6, 2026. REUTERS/Ann Wang/File Photo Purchase Licensing Rights, opens new tab - Summary - Companies - Foxconn's Q1 revenue rose 29.7% y/y - Foxconn benefiting from surge in AI demand - Company to report full Q1 earnings on May 14 TAIPEI, April 5 (Reuters) - Taiwan's Foxconn, the world's largest contract electronics maker, reported a 29.7% on-ye
Goldman Sachs forecasts 49% semiconductor revenue growth driven by AI
Goldman Sachs forecasts 49% semiconductor revenue growth driven by AI {ced(ce('ie-0'))});}"/> LOADING... AI is driving demand for semiconductors # Goldman Sachs forecasts 49% semiconductor revenue growth driven by AI Business Apr 05, 2026 AI is giving the semiconductor industry a serious boost. According to Goldman Sachs, semiconductor revenue is set to grow 49% from current levels by the end of 2026, and revenue from AI-focused hardware could rise to over $700 billion by 2026Q4. The big reason? More businesses are turning to AI, which means a huge need for chips and digital infrastructure to keep things running. ### AI prompts layoffs and job gains While there's been some worry about AI replacing jobs, the impact so far has been pretty balanced. Only around 4,600 employees were affected by corporate layoffs attributed to AI in February 2026. On the flip side, sectors supporting A
Why April 10 Could Be Huge for Taiwan Semiconductor Manufacturing – ICO Optics
With TSMC controlling most advanced ... that AI demand is turning into real production and revenue. The April 10 release is shaping up as a real-time read on whether the AI boom is outpacing chip supply—and how geopolitical or resource pressures could change the chip landscape in 2026. ... TSMC’s dominance in the foundry world—about 72% of global capacity—puts it right at the core of AI hardware ... Topic group: Economics & Markets
Chinese Robot Pioneer UBTech Offers $18 Million for AI Scientist
Chinese humanoid robot maker UBTech Robotics Corp. is seeking a chief scientist, offering an annual pay of as much as 124 million yuan ($18 million) in an aggressive bet on an industry where product applications are still at an early stage.
Irish Government approves ‘next-generation sites’ for industry
The Government said that the strategy is essential to ensuring Ireland remains competitive in attracting the next wave of large-scale, high-value manufacturing investment opportunities in sectors such as semiconductors, life sciences, and renewables. Read more: Irish Government approves ‘next-generation sites’ for industry Topic group: Geopolitics
Intel Reclaims Full Ownership of Irish Fab
Intel will buy back a 49% stake in its Ireland Fab 34 from Apollo Global Management for $14.2 billion, regaining full ownership.
Activist Palliser Targets MSG Maker Ajinomoto in AI Hunt
UK-based activist fund Palliser Capital has expanded its hunt for overlooked AI beneficiaries in Japan with a stake in seasoning maker Ajinomoto Co., according to people familiar with the matter.
Agibot Rolls Out 10,000th Humanoid Robot
Agibot has deployed its 10,000th humanoid robot, marking a significant shift to scalable, real-world applications of embodied AI.
Volkswagen Group AI Marketing
Volkswagen Group showcases how generative AI is transforming marketing through large-scale AI-driven content creation, particularly in generating brand-consistent images across multiple global brands.
MIT Researchers Use AI to Uncover Atomic Defects
A new model measures defects that can be leveraged to improve materials' mechanical strength, heat transfer, and energy-conversion efficiency.
Datamine Unveils AI-Driven MineScape 2026
Datamine launches MineScape 2026, an AI-powered digital twin platform designed to optimize mining operations by integrating geological modeling, planning, and real-time execution.
Scaling industrial AI is more a human than a technical challenge
Industrial artificial intelligence has moved from promise to practice, with 61% of organizations across manufacturing, transportation, and utilities using AI.
How ElevenLabs Voice AI is Replacing Screens in Warehouse and Manufacturing Operations
How ElevenLabs Voice AI is replacing screens in warehouse and manufacturing operations, a warehouse picking operation is the process of collecting items from storage locations to fulfill customer orders.
AI Robotics Lab in Talks to Raise $1 Billion at $11 Billion Valuation
Physical Intelligence, a two-year-old robotics startup founded by AI academics and former Google DeepMind researchers, is discussing a new funding round of about $1 billion that would bring the company’s valuation to more than $11 billion including dollars raised, according to people familiar with the matter.
Musk has a plan to make human labor obsolete. Billionaires are joining in.
Tech elites have seized on humanoid robots to transform manual labor and other fields left out of the AI boom, an area called “physical AI.”
Mandel AI Raises $3.9 Million in Funding
Mandel AI has raised $3.9 million in seed funding to enhance global supply chain coordination. The startup's AI platform automates procurement by managing supplier communications and detecting disruptions.
Krane Raises $9 Million in Funding
Krane Inc., an artificial intelligence-native construction supply chain management startup, has raised $9 million in funding to enhance its operations crew for general contractors, owners, and subcontractors. Founded in 2022 by Eshan Jayamanne.
Doss Raises $55 Million in Funding
Doss, a San Francisco-based developer of an AI-native operations cloud for inventory-based businesses, raised $55 million in Series B funding. The round was co-led by Madrona and Premji Invest, with participation from new investors Greyhound, Commerce Ventures, and Intuit Ventures.
Fullbay Acquires Pitstop for Predictive Maintenance
Fullbay has acquired Pitstop, an AI-powered predictive maintenance platform, to enhance its operational efficiency for heavy-duty repair shops. This acquisition integrates Pitstop's technology with Fullbay's extensive repair data from over 5,000 shops.
AI System Keeps Warehouse Robot Traffic Running Smoothly
A new AI system has been developed to keep warehouse robot traffic running smoothly, according to MIT News.
Krane raises $9M to expand AI-driven construction supply chain platform
Artificial intelligence-native construction supply chain management startup Krane Inc. revealed today that it has raised $9 million in new funding to accelerate the development of its operations crew for general contractors, owners and subcontractors. Founded in 2022 by Chief Executive Eshan Jayamanne, a licensed professional engineer with experience in large-scale construction and infrastructure projects, Krane […] The post Krane raises $9M to expand AI-driven construction supply chain platform appeared first on SiliconANGLE.
YC-backed Mandel AI raises €3.6 million Seed round for its AI supply chain coordination platform
Mandel AI, a Sofia-based startup specialising in AI supply chain coordination that helps manufacturers manage supplier coordination, detect disruptions, and automate procurement, has closed a €3. 6 million Seed round. The round was supported by Y Combinator, Category Ventures, Ritual Capital, e2vc, and other leading Silicon Valley investors and angels.
Jeff Bezos in talks to raise $100 billion fund to bring AI to manufacturing
Jeff Bezos in talks to raise $100bn fund to acquire manufacturing companies and infuse them with AI.
Epoch Biodesign raises €10.3 million to use AI and enzymes to recycle plastic and textile waste at commercial scale
Epoch Biodesign, a London-based BioTech startup specialising in enzymatic recycling technology, has closed a €10. 3 million ($12 million) financing round to accelerate the commercialisation of its recycled nylon 6,6. The investment includes participation from Lululemon, KOMPAS VC, Happiness Capital, Extantia, Leitmotif, and others.
Agile Robots and Google DeepMind Partner
Agile Robots and Google DeepMind have teamed up to integrate AI foundation models into industrial robotics, targeting automation in sectors like manufacturing.
Siemens boss says Europe risks ‘disaster’ from prioritising AI independence
Roland Busch warns against throttling ‘innovation speed for the sake of creating sovereignty’
Unitree Robotics Applies for $610M IPO on Shanghai Stock Exchange
Unitree Robotics, a Chinese robotics startup, has applied for an IPO on the Shanghai Stock Exchange to raise approximately 4.2 billion yuan ($610 million). The funds will enhance AI models, develop new robots, and expand manufacturing.
BOxCrete: A Bayesian Optimization Open-Source AI Model for Concrete Strength Forecasting and Mix Optimization
Modern concrete must simultaneously satisfy evolving demands for mechanical performance, workability, durability, and sustainability, making mix designs increasingly complex. Recent studies leveraging Artificial Intelligence (AI) and Machine Learning (ML) models show promise for predicting compressive strength and guiding mix optimization, but most existing efforts are based on proprietary industrial datasets and closed-source implementations. Here we introduce BOxCrete, an open-source probabili...
Australia Proposes $13M AI Initiative
Australia's mining sector is advocating for a 13 million-dollar AI initiative in the federal budget to expedite regulatory decisions, potentially unlocking a billion dollars in economic benefits.
Kewazo Raises $35M in Funding
Kewazo, a robotics and AI company based in Munich and Houston, has raised $35 million in funding to enhance its automation solutions for heavy industry.
Musk Says Tesla, SpaceX, xAI Chip Project to Kick Off in Texas
Elon Musk said his Terafab project — a grand plan to eventually manufacture his own chips for robotics, artificial intelligence and space data centers — will be built in Austin and jointly run by Tesla, SpaceX and xAI.
'It's stupid': why western carmakers' retreat from electric risks dooming them to irrelevance
Iran war should be wake-up call about costs of not going full throttle towards EVs as Chinese have done, experts say
Jeff Bezos Seeks $100B for AI Manufacturing Fund
Jeff Bezos is seeking $100 billion for an AI manufacturing fund.
The Information: Nvidia Robotics Chief on AI Agents and ChatGPT Moment
Nvidia Robotics Chief says AI agents will bring about a ChatGPT moment for robotics.
Edge AI is pushing enterprise infrastructure beyond the cloud and into factories, ships and stores
The race to run AI models at the distributed edge is moving into the real-world environments where enterprise data is created.
Jeff Bezos is planning to raise $100 billion to speed up manufacturing automation
Jeff Bezos has reportedly been traveling around the Middle East and Southeast Asia trying to raise in the region of $100 billion to transform major industries with artificial intelligence. As first reported today by the Wall Street Journal, Bezos has met with some of the region’s largest asset managers and presented prospective investors with a plan […] The post Jeff Bezos is planning to raise $100 billion to speed up manufacturing automation appeared first on SiliconANGLE.
Jeff Bezos Reportedly Wants $100 Billion to Buy and Transform Old Manufacturing Firms with AI
Jeff Bezos Reportedly Wants $100 Billion to Buy and Transform Old Manufacturing Firms with AI. The Amazon magnate has a new project centered around acquiring industrial firms and revamping them with AI.
Project Prometheus Seeks $100B Funding
Jeff Bezos is seeking to raise approximately $100B for his Project Prometheus to enhance manufacturing automation through artificial intelligence.
Cologne’s Eternal.ag exits stealth with €8 million to automate greenhouse harvesting with AI-powered robots
Eternal. ag, a Cologne-based AgTech startup building autonomous harvesting robots for greenhouses, today announced that it has exited stealth mode and raised €8 million in funding to fuel European expansion and extend the technology’s capabilities to new crop types. The funding was secured from Simon Capital, Oyster Bay Venture Capital, EquityPitcher Ventures, and Backbone Ventures.
Cologne’s Eternal.ag exits stealth with €8 million to automate greenhouse harvesting with AI-powered robots
Eternal. ag, a Cologne-based AgTech startup building autonomous harvesting robots for greenhouses, today announced that it has exited stealth mode and raised €8 million in funding to fuel European expansion and extend the technology’s capabilities to new crop types. The funding was secured from Simon Capital, Oyster Bay Venture Capital, EquityPitcher Ventures, and Backbone Ventures.
Inside China’s robotics revolution
How close are we to the sci-fi vision of autonomous humanoid robots? I visited 11 companies in five Chinese cities to find out Chen Liang, the founder of Guchi Robotics, an automation company headquartered in Shanghai, is a tall, heavy-set man in his mid-40s with square-rimmed glasses. His everyday manner is calm and understated, but when he is in his element – up close with the technology he b
Foresight Raises $25M
Foresight, a UK provider of an AI-powered project delivery platform for large-scale infrastructure, raised $25M led by Macquarie, with Creandum, Isai Build, I2BF Global Ventures.
Jeff Bezos Aims to Raise $100 Billion to Buy Manufacturing Firms with AI
Jeff Bezos aims to raise $100 billion to buy and revamp manufacturing firms with AI.
Jabil Lifts Outlook as Profit, Revenue Rise
Jabil raised its full-year outlook after logging higher profit and a jump in revenue in its fiscal second quarter, boosted by strong demand across its intelligent infrastructure business.
From Tokens to Robotics: Inside Jensen Huang’s Blueprint for the Industrial AI Age
NVIDIA’s core argument is that while training is a one-time, compute-heavy task, inference is an ongoing industrial process. Huang described this through the concept of “ AI Factories”: facilities that take in electricity and “unstructured data” (like raw video or text) and output “tokens” (intelligence and actions) that generate revenue.
Tenkara Raises $7M to Develop Ops Agents for US Manufacturers
Tenkara, a San Francisco-based company developing ops agents for U. S. manufacturers, raised $7 million in funding.
WeSort.AI Raises €10M for AI and X-Ray-Based Material Recovery
WeSort.AI, a Germany-based AI recycling technology company, has raised €10 million to enhance its AI and X-ray-based material recovery platform. Founded in 2022, the company addresses the mis-sorting of e-waste and batteries, which leads to dangerous fires and loss of valuable materials.
Setsale Raises $2M for AI-Powered Sales Platform in Residential HVAC
Setsale, a Charlotte, NC-based developer of an AI-powered sales platform for the residential HVAC industry, raised $2 million in seed funding. The round was led by York IE, with participation from Palmetto and Finturf, bringing the company's total funding to date.
Agzen Raises $10M in Series B Funding
Agzen, an agricultural technology company, has raised $10 million in a Series B funding round to enhance crop spraying efficiency using real-time data and AI. The funding follows rapid adoption of its technology by growers and industry partners.
Roboforce Raises $52M in Funding
Roboforce, a Milpitas, CA-based physical AI-powered robo-labor company, raised $52 million in funding. The round was led by Zi Labs with participation from notable investors including Jerry Yang, Myron Scholes, and Carnegie Mellon University.
Zero RFI Raises $13.8M in Seed Funding
Zero RFI, an AI-native platform founded by KP Reddy, has secured $13.8 million in seed funding to modernize the construction industry. The funding round was led by General Catalyst, with the company aiming to acquire and scale complementary businesses while expanding its platform.
Nvidia Partner Hon Hai Sees AI Growth in 2026 After Profit Miss
Hon Hai Precision Industry Co. is projecting strong sales growth in 2026 after posting disappointing quarterly earnings, seeking to dispel concerns about demand for the Nvidia Corp.-powered servers that power AI applications.
TSMC Eyes $2 Trillion Market Cap Amid AI Boom
TSMC is on track to potentially reach a $2 trillion market-cap, driven by strong demand for advanced chip nodes and substantial AI investments from tech giants. The company's strategic geographic diversification and robust pricing power underscore its competitive edge despite geopolitical challenges.
Phyzify Revolutionizes Product Creation
OpenAI's first artist-in-residence, Alexander Reben, launches Phyzify, a company transforming text into physical products using AI-driven manufacturing.
Uber co-founder Travis Kalanick launches robotics venture Atoms
Travis Kalanick, the billionaire co-founder of Uber Technologies Inc. , today announced the launch of a new robotics startup. Atoms Inc.
AMC Robotics Partners with HIVE
AMC Robotics Corporation teams up with HIVE Digital Technologies to enhance AI-driven robotics using HIVE's GPU resources.
Qnity: New Delaware Facility Boosts CMP Materials Production For AI Chip Manufacturing
Qnity Electronics opened a new 385,000-square-foot manufacturing facility in Newark, Delaware, expanding its domestic production capacity for semiconductor materials used in advanced chip fabrication. I attended the ribbon-cutting event and learned that this facility represents part of a multi-year investment by Qnity to strengthen its advanced manufacturing footprint and meet increasing demand driven by artificial intelligence, high-performance computing, and advanced connectivity technologies. At the event, there was an emphasis on the “Stronger Together” brand strategy, meaning that progress in semiconductors and AI infrastructure happens through collaboration, connecting materials science, partners, customers, and talent to enable the next generation of electronics.
Why physical AI is becoming manufacturing’s next advantage
For decades, manufacturers have pursued automation to drive efficiency, reduce costs, and stabilize operations. That approach delivered meaningful gains, but it is no longer enough. Today’s manufacturing leaders face a different challenge: how to grow amid labor constraints, rising complexity, and increasing pressure to innovate faster without sacrificing safety, quality, or trust.
Europe’s second chance on AI: building an opportunity in factories, labs, and the real economy
As the next AI wave unfolds, Europe’s position as a commercial first-wave AI laggard may actually prove to be a strength.
World Models for General Purpose Robotics
This article explores the concept of world models, AI systems that learn representations of physical environments, to enable general-purpose robotics capable of interacting with the real world. Our analysts noted that the article serves as a useful primer explaining how robotics researchers are using large-scale video data and simulation to help AI learn physics and spatial reasoning.
ASI Acquires Scythe Robotics
ASI acquires Scythe Robotics, integrating its AI-powered Scythe Sight® and M.52 autonomous mower into ASI’s Mobius platform, accelerating industrial and landscaping automation with scalable, sustainable, and high-efficiency off-road vehicle solutions.
Rivian CEO’s AI-Powered Robotics Startup Raises $500 Million
Mind Robotics is building factory robots, joining up with the electric-vehicle maker on training and testing.
Portuguese startup Sybilion secures €3.6 million to build AI-powered decision layer for industrial companies
Today, Porto-based Sybilion announced a €3. 6 million ($4. 2 million) Seed round to build what it calls a decision layer, designed to give industrial companies the ability to act earlier and protect margins in volatile markets.
Neura Robotics and Qualcomm Join Forces
Neura Robotics and Qualcomm have partnered to advance humanoid and autonomous devices using next-gen robotics systems and physical AI.
Australian Plastics Recycling Company Targets Critical Minerals
Samsara Eco plans to tailor microscopic organisms to retrieve materials from electronic waste.
Boeing Says Wiring Issue Will Delay Some 737 Max Deliveries
The aerospace company said the delay would not prevent it from meeting its 2026 sales goal of about 500 Max jets.
China Highlights AI Laser Weeding and Seed-Breeding Model
China's agriculture and rural affairs minister highlighted AI applications in the country's agricultural modernization efforts, including AI-powered laser-weeding robots and a large model for seed breeding.
TCS Unveils AI Driven Manufacturing Hub
Tata Consultancy Services unveils its seventh Gemini Experience Center in Troy, Michigan, spotlighting Physical AI for manufacturing.
Integral AI Partners with Japanese Giants
Integral AI is teaming up with major Japanese companies like Toyota and Sony to enhance AI-driven manufacturing within Japan's robotics ecosystem.
Nvidia and ABB launch partnership for AI-enabled autonomous robots
Industrial robots that can be trained in virtual conditions are being trialled by Foxconn
A Blockchain-based Traceability System for AI-Driven Engine Blade Inspection
Aircraft engine blade maintenance relies on inspection records shared across manufacturers, airlines, maintenance organizations, and regulators. Yet current systems are fragmented, difficult to audit, and vulnerable to tampering. This paper presents BladeChain, a blockchain-based system providing immutable traceability for blade inspections throughout the component life cycle.
Former Google AI Researcher Sets Up AI Robotics Startup in Tokyo
A Silicon Valley-born AI startup is turning to Japan to prove AI can reshape one of the world’s largest industrial robot supply chains.
PartsPulse: $3 Million Raised For AI Platform To Streamline Aftermarket Parts Operations
PartsPulse, an AI-powered platform designed to manage aftermarket parts businesses, has officially launched with $3 million in backing from UP. Partners. The company introduced its platform at CONEXPO in Las Vegas, positioning the technology as a unified system to help manufacturers, dealers, and fleet operators better manage complex parts operations.
Toyota supplier Denso makes $8bn bid for Japanese chipmaker Rohm
Takeover proposal comes as Tokyo seeks to consolidate sector to compete against China.
The Sequence Opinion: How AI Chips are Made
The Sequence Opinion discusses how AI chips are made.
Tata Elxsi Launches DevStudio.ai
Tata Elxsi launched DevStudio.ai, a versatile GenAI platform for automotive software, supporting both cloud and on-premise setups. Early use cases are underway in multiple regions, enhancing productivity and time-to-market.
Lantronix Expands IoT and Edge AI Offerings
Lantronix is enhancing its embedded compute platform with new MediaTek Genio-based System-on-Module solutions to drive growth in Industrial IoT and Edge AI.
Nexperia China Resumes Most Operations After Account Disruptions
Nexperia China resumes most operations after account disruptions.
Tata Elxsi Launches DevStudio.ai
Tata Elxsi launched DevStudio.ai, a versatile GenAI platform for automotive software, supporting both cloud and on-premise setups.
China's EV Executives Push Beijing to Leapfrog L3, Scale Humanoid Robots
China's top auto entrepreneurs are urging the government to accelerate adoption of fully driverless cars and scale humanoid robots in factories, proposals that could reshape the global race for self-driving and AI-powered manufacturing supremacy.
Codelco and Microsoft Sign AI Deal for Mining Operations
Chile's Codelco and Microsoft signed a deal to evaluate joint initiatives in AI, advanced analytics, automation, and digital security for mining operations.
Iran Crisis Could Disrupt Supply of Key Chipmaking Materials
The US-Israel war with Iran could disrupt supplies of key semiconductor manufacturing materials, according to a South Korean ruling party lawmaker.
China’s Traditional Businesses Try to Buy Into AI Boom
Chinese ham producers and real-estate companies are jumping on the artificial-intelligence bandwagon, pouring millions of dollars into semiconductor companies.
Sonia S. - CEO @ AllAI | ex National AI Leader @ Deloitte | AI Engineer | Context Graphs Expert | Human-Augmentation Systems Specialist | LinkedIn
That moment confirmed why we launched the Manufacturer Committee within the " Artificial Intelligence & Innovation Association Hong Kong" (𝗔𝗜𝗜𝗔 𝗛𝗼𝗻𝗴 𝗞𝗼𝗻𝗴) to bridge the gap between AI talk and AI action.