# Manufacturing Published articles for Manufacturing. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Design in KiCad, Quote with AIVON: A Faster Path to PCB Prototyping (Sponsored) DevFeed: [Design in KiCad, Quote with AIVON: A Faster Path to PCB Prototyping (Sponsored)]() Original publisher: [Read original article]() Author: Sponsored Post Published: 2026-09-15T02:00:57Z Content type: article Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Hardware](), [systems]() Tags: [aivon](), [engineering](), [hardware](), [kicad](), [manufacturing](), [pcb](), [plugin](), [prototyping](), [sponsored](), [verification](), [workflow]() ### AI overview AIVON's official KiCad Plugin connects a completed PCB layout to an online quotation form. After design-rule checking, it prepares manufacturing data and reduces manual exporting, zipping, uploading, and form entry during PCB prototyping. ### Source excerpt Finished your PCB layout in KiCad? You don't necessarily need to leave the PCB Editor, export a separate set of manufacturing files, and manually upload them to a PCB manufacturer. AIVON's KiCad Plugin creates a direct path from your PCB design to an online PCB quote. AIVON has integrated an official KiCad plugin that connects a finished PCB layout to the company's online quotation page. After DRC, users can click the plugin in the PCB Editor, automatically prepare manufacturing data, and land on a pre-filled quote form instead of exporting, zipping, and uploading files by hand. Rather than introducing a new plugin framework, AIVON's integration leverages KiCad's existing Plugin and Content Manager ecosystem. For developers who already use KiCad for schematic capture and PCB layout, the integration provides another way to connect the design stage with PCB fabrication without manually repeating every manufacturing-file preparation step. Connecting KiCad PCB Design with [...] The post Design in KiCad, Quote with AIVON: A Faster Path to PCB Prototyping (Sponsored) appeared first on CNX Software - Embedded Systems News. ## MIT spinout turns plastic waste into resilient building materials DevFeed: [MIT spinout turns plastic waste into resilient building materials]() Original publisher: [Read original article]() Author: Zach Winn | MIT News Published: 2026-09-14T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [systems]() Tags: [3-d-printing](), [ai](), [aj-perez](), [alumni-ae](), [artificial-intelligence](), [atlas-composites](), [cleaner-industry](), [engineering](), [homes](), [housing](), [manufacturing](), [materials-science-and-engineering](), [matt-pouliot](), [mechanical-engineering](), [platform](), [pollution](), [production](), [recycled-plastic-building-materials](), [robotics](), [school-of-engineering](), [startups](), [sustainability](), [u-s-army](), [water]() ### AI overview MIT spinout Atlas Building Composites is commercializing an AI-powered robotic manufacturing platform that recycles single-use and low-grade plastic into durable building components. Its waterless process has been used for structures including a bridge supplied to the U.S. Army Corps of Engineers. ### Source excerpt Atlas Building Composites is commercializing MIT research to turn plastic waste into parts for buildings and other infrastructure. ## IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026 DevFeed: [IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-11T16:25:47Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [ibm](), [Quantum Computing](), [Supercomputing](), [Cloud](), [Algorithms](), [Optimization](), [Simulation and Design](), [Hardware]() Tags: [2026](), [ai](), [algorithms](), [amd](), [chemistry](), [cloud](), [collaboration](), [core](), [enterprise](), [financial-services](), [hardware](), [hub](), [ibm](), [infrastructure](), [manufacturing](), [optimization](), [processors](), [quantum](), [quantum-computing](), [science](), [simulation](), [supercomputing]() ### AI overview IBM and Lockheed Martin are establishing a quantum innovation hub at ETH Zurich, centered on an IBM Quantum System Two planned for installation at the Swiss National Supercomputing Centre by the end of 2026. The system will use IBM's 120-qubit Nighthawk r2 processor and support research in areas including chemistry, materials science, optimization, and financial services. ### Source excerpt IBM and Lockheed Martin are setting up a quantum innovation hub at ETH Zurich, and its core is Switzerland's first IBM Quantum System Two, to be installed at the Swiss National Supercomputing Centre (CSCS) in Lugano by the end of 2026. The hub comes out of an offset agreement with armasuisse, Switzerland's Federal Office for The post IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026 appeared first on StorageReview.com. ## From Wafer-Out to First Token: Codifying Supply Chain Expertise with Nemotron and Palantir Foundry DevFeed: [From Wafer-Out to First Token: Codifying Supply Chain Expertise with Nemotron and Palantir Foundry]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-10T09:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [datacenter](), [networking](), [Software](), [data]() Tags: [agentic-ai-generative-ai](), [ai-agent](), [blackwell](), [compute](), [cuopt](), [data-center](), [gb200](), [infrastructure](), [llms](), [manufacturing](), [memory](), [nemo](), [nemotron](), [networking](), [nvidia](), [nvidia-blackwell](), [nvl72](), [performance](), [production](), [real-time](), [software](), [supply-chain](), [vera-rubin]() ### AI overview NVIDIA describes how it measures and reduces the time from wafer-out to first token across complex Grace Blackwell and Vera Rubin supply chains. The article focuses on time-to-rack, critical material allocation, real-time visibility, redundancy, reliability, and codifying human expertise. ### Source excerpt NVIDIA has one of the largest and most complex supply chains in the world, and its performance is measured from wafer-out to first token. The interval is in two... ## Why Output Metrics Can Miss Problems in Complex Production Systems DevFeed: [Why Output Metrics Can Miss Problems in Complex Production Systems]() Original publisher: [Read original article]() Author: Remy Porter Published: 2026-09-02T06:30:00Z Content type: opinion Language: en Sources: [The Daily WTF]() Topics: [Monitoring](), [dashboards](), [robot sense of touch](), [Embedded Software Dev](), [Databases](), [Computer vision]() Tags: [algorithm](), [computer-vision](), [databases](), [embedded](), [feature-articles](), [manufacturing](), [metrics](), [monitoring](), [robotics](), [widget]() ### AI overview This commentary examines a metrics-driven manufacturing team whose automated production line combines robotics, embedded firmware, web-based monitoring tools, and PLC code. It argues that tracking output and limited performance metrics does not adequately explain how such a complex system behaves or why bottlenecks occur. ### Source excerpt Rachel joined a new team which was proudly "metrics driven". When she first met with her boss, Zane, he explained his thinking. "We need to be data-driven to make good decisions, right? We're a manufacturing company. We make widgets. At the end of the day, we need to make the most widgets for the lowest cost of goods sold. So we track that, and that feeds into every decision." The team oversaw an automated production line, which meant the software was a mix of robotics, embedded firmware, high-level web based monitoring tools, and thickets of dreaded PLC code. And because you can't build an entire factory for test purposes, they only way they could test real-world scales with real-world data was to roll changes out to production. They could simulate, they could run tests on subsets of the system, but a change in the production line software couldn't truly be validated until it rolled out into the real world. Rachel's first task on the new team involved making some changes to their metrics dashboard. It was viewed as a good way to get her feet wet with the new team. As it turned out, the metrics dashboard was a Google Sheet, with a complex series of formulas that involved multi-level INDEX functions- essentially querying the spreadsheets like they were a database. Why not use an actual database? Oh, they did -- six actually -- but the company obeyed Remy's Law of Requirements Gathering: "no matter what the requirements the users ask for, what they really wanted was Excel". The database data was pulled into the spreadsheet for reporting. Now, a complicated sheet pulling in data from not one, but six different databases, they must have a pretty complex model to explain how changes to their software would impact productivity. And since they needed to model the software to make predictions about how it'd behave in production, that model must be extremely useful. Of course it wasn't. The only metrics they tracked were output metrics, variations on "widgets produced per unit ## From voice command to robotic arm: how agentic AI on the edge is changing the factory floor DevFeed: [From voice command to robotic arm: how agentic AI on the edge is changing the factory floor]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-01T12:20:24Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [Artificial Intelligence](), [foundation-models](), [Automation](), [Arduino](), [UNO Q](), [AI Agent](), [Physical AI](), [multimodal]() Tags: [agentic-ai](), [ai](), [arduino](), [automation](), [featured](), [foundation-models](), [industrial](), [inference](), [latency](), [manufacturing](), [multimodal](), [robotic-arm](), [robotics](), [smart-factory](), [uno-q](), [usb](), [voice-commands](), [voice-control]() ### AI overview The article describes a demonstration in which Forgis uses a foundation model running on an Arduino UNO Q board to convert voice commands into robotic-arm actions. The system processes multimodal factory data and performs inference locally, enabling real-time control without a cloud round trip. ### Source excerpt For years, bringing real intelligence to industrial automation meant expensive infrastructure, proprietary systems, and steep learning curves. That's changing - fast. Foundation models powerful enough to run at the edge are turning natural language into machine control, and the factory floor is starting to look a lot more like a conversation. AI as the new [...] The post From voice command to robotic arm: how agentic AI on the edge is changing the factory floor appeared first on Arduino Blog. ## Mistral x HUMAIN DevFeed: [Mistral x HUMAIN]() Original publisher: [Read original article]() Published: 2026-08-24T16:02:41Z Content type: article Language: en Sources: [Mistral AI Blog]() Topics: [AI Strategy](), [AI Infrastructure](), [AI Models](), [Model Development](), [model-deployment](), [Localization (l10n)](), [datacenter](), [Cybersecurity]() Tags: [ai](), [ai-infrastructure](), [ai-platform](), [arabic](), [data](), [data-center](), [deployment](), [enterprise](), [europe](), [financial-services](), [manufacturing](), [model-development](), [public-sector](), [security]() ### AI overview Mistral and HUMAIN announce a strategic collaboration to advance sovereign AI in Saudi Arabia and across the Middle East. The initiative covers AI infrastructure, advanced model development, localized Arabic-capable models, and deployment of AI solutions for regulated industries. ### Source excerpt The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents, and multimodal AI with open models. ## GeoPT helps AI models simulate how objects respond to physical forces DevFeed: [GeoPT helps AI models simulate how objects respond to physical forces]() Original publisher: [Read original article]() Author: Alex Shipps | MIT CSAIL Published: 2026-08-10T19:25:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [AI Models](), [Simulation](), [AI Research](), [Computer Science and Artificial Intelligence Laboratory (CSAIL)](), [Robotics]() Tags: [3-d-imaging](), [ai](), [ai-models](), [artificial-intelligence](), [computational-fluid-dynamics-cfd](), [computer-graphics](), [computer-modeling](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [crash-simulation](), [design](), [electrical-engineering-and-computer-science-eecs](), [geometric-pre-training](), [geopt](), [haixu-wu](), [human-computer-interaction](), [kaiming-he](), [manufacturing](), [minghao-guo](), [mit-csail](), [mit-eecs](), [mit-schwarzman-college-of-computing](), [neural-physics-simulation](), [paper](), [physics](), [physics-aware-ai](), [physics-foundation-models](), [research](), [robotics](), [school-of-engineering](), [self-supervised-learning](), [simulation](), [surrogate-modeling](), [synthetic-dynamics](), [transformer-based-simulators](), [wojciech-matusik]() ### AI overview Researchers at MIT CSAIL and Tsinghua University developed GeoPT, a pre-training approach that uses 3D simulations of mechanical interactions to help AI models learn physics more efficiently. The article reports that models using the approach reached peak performance twice as fast and trained on up to 60 percent less data than leading models. ### Source excerpt "GeoPT" helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately. ## Tech Job Postings Are Up 27% Year-Over-Year DevFeed: [Tech Job Postings Are Up 27% Year-Over-Year]() Original publisher: [Read original article]() Author: Prasad Rao Published: 2026-07-30T16:39:53Z Content type: article Language: en Sources: [Big Tech Careers]() Topics: [Tech Careers](), [tech jobs](), [Artificial Intelligence](), [Automation]() Tags: [2026](), [ai](), [article](), [manufacturing](), [report](), [tech](), [tech-careers](), [tech-jobs](), [technology]() ### AI overview The article analyzes Dice's July 2026 Tech Jobs Report, based on more than 7 million US tech job postings. It reports 3% month-over-month growth in June and 27% year-over-year growth, with AI skill requirements appearing in 75% of postings. Manufacturing recorded the largest monthly increase, followed by Technology, Consulting, and Software. ### Source excerpt Here's Where the Growth Actually Is ## Advancing Semiconductor Innovation Across Materials Engineering and Manufacturing DevFeed: [Advancing Semiconductor Innovation Across Materials Engineering and Manufacturing]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-07-27T00:45:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [CUDA](), [GPU](), [Optimization](), [Nvidia](), [Simulation and Design](), [Hardware]() Tags: [ai](), [computational-chemistry-materials-science](), [compute](), [cuda](), [cuda-x](), [data-center-cloud](), [engineering](), [featured](), [gpu](), [hardware](), [industrial-digitalization-digital-twin](), [manufacturing](), [nvidia](), [optimization](), [physics](), [production](), [simulation-modeling-design]() ### AI overview Applied Materials and NVIDIA are presented as combining materials engineering, semiconductor manufacturing, CUDA-X libraries, GPU-accelerated simulation, physics-based modeling, and AI-driven digital twins in an end-to-end digital development model. The approach spans atomic-scale materials discovery, process development, and factory optimization, with Ginestra used to connect material defects and properties to predicted device performance. ### Source excerpt As AI workloads increase, explosive compute demand is pushing the semiconductor industry to meet unprecedented performance targets. Even small delays can have... ## MIT projects selected for funding under US Department of Energy's Genesis Mission DevFeed: [MIT projects selected for funding under US Department of Energy's Genesis Mission]() Original publisher: [Read original article]() Author: Office of the Vice President for Research Published: 2026-07-23T12:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Supercomputing](), [systems]() Tags: [administration](), [ai](), [artificial-intelligence](), [center-for-computational-science-and-engineering](), [chemical-engineering](), [department-of-energy](), [department-of-energy-doe](), [doe](), [eaps](), [engineering](), [faculty](), [funding](), [genesis](), [genesis-mission](), [industry](), [initiative](), [laboratory-for-nuclear-science](), [manufacturing](), [mathematics](), [mechanical-engineering](), [mission](), [national-security](), [nuclear-science-and-engineering](), [physics](), [plasma-science-and-fusion-center](), [projects](), [quantum](), [quantum-computing](), [quantum-systems](), [research](), [research-laboratory-of-electronics](), [school-of-engineering](), [school-of-science](), [science](), [supercomputing](), [us]() ### AI overview MIT researchers will contribute to 15 collaborative projects selected for funding under Phase I of the U.S. Department of Energy's Genesis Mission. The projects apply AI, supercomputing, quantum systems, and scientific instruments to research areas including energy, materials, fusion, and national security. Funding remains pending completion of award negotiations. ### Source excerpt Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more. ## MIT's JARVIS Challenge tests AI copilots in jet-engine design and manufacturing DevFeed: [MIT's JARVIS Challenge tests AI copilots in jet-engine design and manufacturing]() Original publisher: [Read original article]() Author: Department of Aeronautics and Astronautics Published: 2026-07-14T18:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [AI Development](), [Artificial Intelligence](), [Hardware](), [Software Engineering](), [Large language models (LLMs)]() Tags: [3-d-printing](), [aeronautical-and-astronautical-engineering](), [aerospace](), [ai-and-rapid-prototyping](), [ai-copilots](), [ai-native-engineer](), [aircraft](), [andreea-bobu](), [artificial-intelligence](), [chatgpt](), [classes-and-programs](), [claude](), [contests-and-academic-competitions](), [design](), [design-build-test-cycle](), [education-teaching-academics](), [engineering](), [gas-turbine-aero-engine](), [generative-ai](), [hardware](), [independent-activities-period](), [jet-engines](), [large-language-models-llms](), [lincoln-laboratory](), [logistics](), [machine-learning](), [manufacturing](), [masha-folk](), [mechanical-engineering](), [mit-aeroastro](), [mit-gas-turbine-laboratory](), [mit-iap](), [mit-jarvis-challenge](), [mit-lincoln-laboratory](), [mit-meche](), [mit-motorsports-team](), [mit-parley](), [mit-rocket-team](), [robotics](), [school-of-engineering](), [stem-education](), [students](), [undergraduate](), [zachary-cordero](), [zoltan-spakovszky]() ### AI overview MIT's JARVIS Challenge asked undergraduate teams to design, fabricate, assemble, and test small gas turbine aero engines with AI as their primary engineering partner. The challenge found that AI could accelerate parts of safety-critical hardware engineering, while engineering judgment remained essential and manufacturing was the main rate-limiting step. ### Source excerpt MIT students designed, built, and tested a jet engine with AI copilots, assessing AI's usefulness in developing high-performance aerospace systems. ## IoTorero joins Works with Home Assistant DevFeed: [IoTorero joins Works with Home Assistant]() Original publisher: [Read original article]() Author: Miranda Bishop Published: 2026-07-09T00:00:01Z Content type: news Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [Internet of things](), [Hardware](), [Open Source](), [Code](), [GitHub]() Tags: [community](), [customers](), [devices](), [firmware](), [github](), [hardware](), [internet-of-things](), [iot](), [manufacturing](), [open-source](), [products](), [remote-access](), [research-development](), [smart-home](), [works-with-home-assistant]() ### AI overview IoTorero joins the Works with Home Assistant program with seven certified devices pre-flashed with ESPHome. The company focuses on open source smart home hardware, including smart plugs and relays, and publishes device configuration files on GitHub. ### Source excerpt The Works with Home Assistant program powers up this month as we welcome our new partner, IoTorero! 🎉 Experts in pre-flashed smart home hardware, IoTorero bring the very first ESPHome-ready smart plugs and relays to the program (and that's not all). IoTorero enters the ring If you've spent any time browsing pre-flashed smart home tech online, there's a good chance you've come across IoTorero. And if you haven't, let us introduce you! Founded in 2020, the company (formerly Athom Technology) was tinkering with ESPHome right out of the gate. Their new name is a nod to the Internet of Things (IoT), but unlike standard IoT gadgets that stop working if your internet drops or a company closes its servers, IoTorero champion open source firmware. Other smart devices run manufacturer-written software, which is tuned to work well with Home Assistant for certification to the program. IoTorero go a step further to make sure their tech is accessible for all: all seven of their certified devices are pre-flashed with ESPHome, meaning there's no installation required - the devices will integrate into your Home Assistant setup straight out of the box. And because their devices are genuinely open, you can always tweak and customize them if you want to. "Since inception in 2020, IoTorero (Athom Technology) has been dedicated to the research, development, and manufacturing of open source smart home hardware products. We provide Home Assistant users with high-quality devices pre-flashed with ESPHome firmware. By joining the Works with Home Assistant program, we ensure that customers can select and purchase our products with complete confidence." - Aiden Tang, CTO and Co-Founder, IoTorero That same spirit of openness carried over to last year's Community Day, where IoTorero donated a stack of samples for attendees to try - a gesture we loved to see, and one that speaks to how seriously they take supporting our community 💪. It shows up in their approach to code, too: IoTorero maintain a pu ## Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T DevFeed: [Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-07-07T17:05:42Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Robotics](), [Model Development](), [Open Source](), [Training AI Models](), [datasets](), [multimodal](), [Deployment](), [Simulation and Design](), [Tooling]() Tags: [ai-foundation-models](), [apache](), [building](), [data](), [deployment](), [developers](), [development](), [evaluation](), [featured](), [humanoid-robots](), [images](), [integrations](), [isaac](), [isaac-sim](), [manufacturing](), [model](), [multimodal](), [nvidia](), [open-source](), [robotics](), [robotics-simulation](), [robots](), [simulation-modeling-design](), [software](), [tooling](), [training](), [workflows]() ### AI overview NVIDIA Isaac GR00T Development Platform unifies humanoid robot development workflows, combining data collection, simulation-based training, evaluation, and deployment. The article highlights the open Isaac GR00T 1.7 vision-language-action model, which accepts language and images and can be adapted to robots, tasks, and environments through post-training. ### Source excerpt As more teams move from humanoid robot bring-up to task-specific skill development, the need for repeatable development workflows is growing. Building humanoids... ## MIT in the media: For the future of tech, "Massachusetts can absolutely lead" DevFeed: [MIT in the media: For the future of tech, "Massachusetts can absolutely lead"]() Original publisher: [Read original article]() Published: 2026-06-18T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [AI Strategy](), [Robotics]() Tags: [ai](), [alumni-ae](), [applied-ai](), [articles](), [artificial-intelligence](), [biotechnology](), [cambridge-boston-and-region](), [computer-science-and-technology](), [courses](), [energy](), [faculty](), [funding](), [health](), [manufacturing](), [president-sally-kornbluth](), [quantum-computing](), [quantum-technologies](), [research](), [robotics](), [startup](), [startups](), [students](), [tech](), [technology-and-society]() ### AI overview MIT's research, AI initiatives, online courses, and entrepreneurship programs are highlighted in coverage of Massachusetts' technology ecosystem and its potential for continued leadership. ### Source excerpt Leaders, faculty across MIT discuss fostering innovation and talent in Greater Boston in special series of articles published alongside the outlet's annual list of 'Tech Power Players' ## Protecting legacy OT systems against modern cyberthreats DevFeed: [Protecting legacy OT systems against modern cyberthreats]() Original publisher: [Read original article]() Author: Tomáš Foltýn Published: 2026-06-17T08:45:00Z Content type: article Language: en Sources: [WeLiveSecurity]() Topics: [High Profile Threats](), [incident]() Tags: [attacks](), [authentication](), [critical-infrastructure](), [cybersecurity](), [incident](), [logging](), [manufacturing](), [networks](), [production](), [security](), [update]() ### AI overview Legacy operational technology in manufacturing can become a cybersecurity blind spot as industrial control systems connect to enterprise networks. The article highlights weak authentication, limited logging, insecure defaults, and difficult updates as risks that can lead to operational disruption. ### Source excerpt Many manufacturing plants depend on OT systems that stay in service for many years. That long run can hide significant cybersecurity risks. ## Emmi joins Mistral to accelerate the AI-native industry DevFeed: [Emmi joins Mistral to accelerate the AI-native industry]() Original publisher: [Read original article]() Published: 2026-05-23T12:00:26Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [Artificial Intelligence](), [Simulation and Design](), [AI Development]() Tags: [acquisition](), [ai](), [automotive](), [design](), [engineering](), [industry](), [manufacturing](), [physics](), [platform](), [real-time](), [science]() ### AI overview Mistral AI announces a definitive agreement to acquire Emmi AI, aiming to strengthen its industrial AI offering through Physics AI, engineering models, real-time simulations, digital twins, and AI agents that use existing engineering tools. The deal is intended to support engineering, manufacturing, and high-stakes industrial sectors. ### Source excerpt The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents, and multimodal AI with open models. ## How Temporal's Senior Developer Advocate Built 2,000 Interactive Badges for Replay DevFeed: [How Temporal's Senior Developer Advocate Built 2,000 Interactive Badges for Replay]() Original publisher: [Read original article]() Author: Shy Ruparel Published: 2026-05-20T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Hardware](), [developer-relations](), [keyboard](), [screen](), [Job]() Tags: [community](), [conference](), [developer](), [electronic](), [hardware](), [interactive](), [manufacturing](), [project](), [temporal-voices]() ### AI overview Temporal Senior Developer Advocate Shy Ruparel describes the design and manufacturing process behind 2,000 interactive electronic badges made for the Replay developer conference, including the project's hardware concepts and production challenges. ### Source excerpt Temporal's Senior Developer Advocate, Shy Ruparel, built 2,000 interactive electronic badges for Replay. Here's how he pulled it off. ## Partnering with industry leaders to accelerate AI transformation DevFeed: [Partnering with industry leaders to accelerate AI transformation]() Original publisher: [Read original article]() Author: David Thacker Published: 2026-04-21T14:54:15Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Artificial Intelligence](), [Frontier AI](), [AI Strategy](), [AI Development](), [Google](), [Cloud]() Tags: [agentic-ai](), [ai](), [cloud](), [data](), [enterprise](), [finance](), [frontier-ai](), [global](), [google](), [industry](), [leadership](), [management](), [manufacturing](), [media-and-entertainment](), [models](), [partnerships](), [real-time](), [responsibility-safety](), [retail](), [scale](), [solutions]() ### AI overview Google DeepMind describes partnerships with Accenture, Bain & Company, BCG, Deloitte, and McKinsey to help organizations adopt frontier AI at scale. The initiative focuses on industry-specific AI capabilities, early access to frontier models including Gemini, and leadership support for enterprise transformation across sectors such as finance, manufacturing, retail, and media and entertainment. ### Source excerpt Google DeepMind partners with global consultancies to bring the power of frontier AI to organizations around the world. ## How Critical Manufacturing uses ClickHouse to bring real-time intelligence to the factory floor DevFeed: [How Critical Manufacturing uses ClickHouse to bring real-time intelligence to the factory floor]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-03-10T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [real-time](), [Kafka](), [dashboards](), [Cloud](), [Streaming](), [sql-server](), [observability](), [systems]() Tags: [ai](), [analytics](), [clickhouse](), [cloud](), [dashboards](), [data](), [kafka](), [manufacturing](), [observability](), [real-time](), [telemetry]() ### AI overview Critical Manufacturing uses ClickHouse Cloud to turn billions of shop-floor events into sub-second analytics and operational intelligence. The article describes Kafka-based ingestion, real-time dashboards, scalable data storage, observability, and AI workloads, along with migration from SQL Server and techniques including ELT, ReplacingMergeTree, denormalization, and TTL. ### Source excerpt "ClickHouse was the perfect fit for what we were doing. It just worked." Ricardo Magalhaes, Lead Software Engineer ## 7 Reasons Why CEOs Should Modernize their Software DevFeed: [7 Reasons Why CEOs Should Modernize their Software]() Original publisher: [Read original article]() Author: Aisling Foley Published: 2026-02-18T07:23:00Z Content type: opinion Language: en Sources: [Federico Tomassetti]() Topics: [Software](), [cobol](), [Visual Basic](), [SAS]() Tags: [cobol](), [financial-services](), [growth](), [integration](), [leadership](), [legacy](), [legacy-modernization](), [manufacturing](), [security](), [software]() ### AI overview This commentary argues that CEOs should modernize legacy software because systems that remain stable can still create strategic, regulatory, security, integration, and knowledge-retention risks. It discusses legacy systems used in manufacturing and financial services, including COBOL, RPG, Visual Basic 6, and SAS. ### Source excerpt Key Takeaways Legacy software is tolerated because, let's face it, it works, and works well. But that's no longer good enough. Nowadays, it limits an organisation's strategic options. Legacy software can slow down, or make strategic plans more expensive or complicated than they need to be. Whilst legacy software is considered stable, the real risk [...] The post 7 Reasons Why CEOs Should Modernize their Software appeared first on Federico Tomassetti. ## Strengthening the U.S. AI supply chain through domestic manufacturing DevFeed: [Strengthening the U.S. AI supply chain through domestic manufacturing]() Original publisher: [Read original article]() Published: 2026-01-15T00:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [AI, ML & Data Engineering]() Tags: [ai](), [ai-infrastructure](), [compute](), [data-center](), [global-affairs](), [hardware](), [infrastructure](), [manufacturing](), [networking](), [openai](), [robotics](), [supply-chain](), [us]() ### AI overview OpenAI launches an RFP for U.S.-based manufacturing that supports AI infrastructure, including data-center hardware, consumer electronics, and robotics components. The initiative aims to strengthen domestic supply chains and scale advanced AI infrastructure. ### Source excerpt OpenAI launches a new RFP to strengthen the U.S. AI supply chain by accelerating domestic manufacturing, creating jobs, and scaling AI infrastructure. ## OpenAI and Foxconn collaborate to strengthen U.S. manufacturing across the AI supply chain DevFeed: [OpenAI and Foxconn collaborate to strengthen U.S. manufacturing across the AI supply chain]() Original publisher: [Read original article]() Published: 2025-11-20T14:50:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [AI Infrastructure](), [Artificial Intelligence](), [Hardware](), [datacenter](), [OpenAI](), [data centers]() Tags: [ai](), [ai-infrastructure](), [architecture](), [assembly](), [build](), [collaboration](), [company](), [components](), [compute](), [data-center](), [deployment](), [engineering](), [hardware](), [infrastructure](), [manufacturing](), [networking](), [openai](), [partnership](), [supply-chain]() ### AI overview OpenAI and Foxconn are collaborating on the design and U.S. manufacturing readiness of next-generation AI infrastructure hardware. The initiative covers multiple generations of AI data center racks, domestic supply-chain development, and U.S. production of components such as cabling, networking, cooling, and power systems. ### Source excerpt OpenAI and Foxconn are collaborating to design and manufacture next-generation AI infrastructure hardware in the U.S. The partnership will develop multiple generations of data-center systems, strengthen U.S. supply chains, and build key components domestically to accelerate advanced AI infrastructure. ## Expanding Stargate to Michigan DevFeed: [Expanding Stargate to Michigan]() Original publisher: [Read original article]() Published: 2025-10-30T13:30:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [stargate](), [AI Infrastructure](), [Artificial Intelligence](), [OpenAI](), [systems]() Tags: [ai](), [ai-infrastructure](), [capacity](), [company](), [energy](), [engineering](), [industrial](), [infrastructure](), [jobs](), [manufacturing](), [openai](), [partnership](), [stargate](), [us]() ### AI overview OpenAI announces a new Stargate campus in Saline Township, Michigan, developed by Related Digital as part of its partnership with Oracle. The campus is expected to add one gigawatt of capacity, support more than 2,500 union construction jobs, use closed-loop cooling, and contribute to broader AI infrastructure investment across the United States. ### Source excerpt OpenAI is expanding Stargate to Michigan with a new one-gigawatt campus that strengthens America's AI infrastructure. The project will create jobs, drive investment, and support economic growth across the Midwest. [Next page]()