Exponential Industry

[Overcapacity] Into the Lab for Industrial Scale Returns

David Rogers — Sun, 28 Jun 2026 16:02:52 GMT

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This weeks digest:

Into the Lab for Industrial Scale Returns

David Rogers — Sun, 28 Jun 2026 13:00:49 GMT

Shop Talk

Capturing this week’s zeitgeist

The rise of “Labs” is essential because large venture-scale industrial opportunities ignore traditional disciplinary boundaries and require teams to master disparate fields across thermodynamics, fluids, mechanical and electrical engineering, materials science, and semiconductor physics, often by learning them on the fly when no single set of experts exists. This model was exemplified by Elon Musk’s transition from PayPal to founding and scaling SpaceX and Tesla, and it is now enabled by applied Labs that create dedicated, low-friction environments for cross-discipline collaboration and rapid iteration, something traditional siloed organizations or pure SaaS teams cannot replicate when building full-stack physical systems. The approach continues to be validated by software-founded companies such as Boom Supersonic (led by ex-Amazon engineers now developing supersonic jets) and AI leaders like OpenAI and Anthropic that have moved into hardware (see below), where only boundary-spanning Labs deliver the enduring technical depth and commercial value that venture capital bets now require.

@cerebras team hadn’t studied thermodynamics at college.\n\nThe residential solar market didn’t care that the @Sunrun team hadn’t spent a day in the energy industry.\n\nCerebras ","username":"vassallo","name":"Steve Vassallo","profile_image_url":"https://pbs.substack.com/profile_images/707774773430882304/Y0bFygI__normal.jpg","date":"2026-06-22T13:54:17.000Z","photos":[{"img_url":"https://pbs.substack.com/media/HLbDyWRWoAAOMda.png","link_url":"https://t.co/lvbHI6LtKX"}],"quoted_tweet":{},"reply_count":3,"retweet_count":9,"like_count":62,"impression_count":4613,"expanded_url":null,"video_url":null,"belowTheFold":false}" data-component-name="Twitter2ToDOM">

Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

Beyond the solver: How Geometric Deep Learning is reshaping CAE

A finite element mesh is an irregular graph. A point cloud from a 3D scan is an unordered set. A CAD surface is a manifold. None of these live comfortably on a regular grid. If you try to flatten them into one, as early AI-for-engineering approaches did, you lose the very geometric relationships that make the physics meaningful. You’re essentially crumpling a map to fit it into a square box, then wondering why the roads don’t connect.

GDL extends deep learning to these non-Euclidean domains – graphs, meshes, point clouds, and manifolds – by building neural networks that respect the underlying geometric structure of the data. The theoretical backbone comes from the concept of symmetry: a well-designed geometric neural network should produce consistent predictions regardless of how you rotate, translate, or renumber the input. This property – known as equivariance – is not just mathematically beautiful but also physically essential.

Washington plant creates jet fuel from water, air and electricity

Alaska Airlines and Microsoft join Twelve to mark commercial operation of AirPlant One — the first plant in the United States to produce E-Jet fuel from CO2, renewable electricity, and water at scale /Twelve/. AirPlant is a eManufacturing factory that produces E-Jet® SAF and E-Naphtha with power-to-liquid technology that works like industrial photosynthesis—transforming CO2, water, and renewable electricity into hydrocarbons.

AquaPoro Raises $5M to Advance Technology that Generates Net New Water from Air /Business Wire/

ViserDex: Visual Sim-to-Real for Robust Dexterous In-hand Reorientation

Experiments show that the pose estimator trained with 3DGS data outperforms those trained using conventional rendering data in challenging visual environments. We validate the system on a physical multi-fingered hand equipped with an RGB camera, demonstrating robust reorientation of five diverse objects even under challenging lighting conditions. Our results highlight Gaussian splatting as a practical path for RGB-only dexterous manipulation.

New Product Introduction

Highlighting new and innovative facilities, processes, products, and services

OpenAI and Broadcom unveil LLM-optimized inference chip

OpenAI and Broadcom (NASDAQ: AVGO) unveiled Jalapeño, OpenAI’s first Intelligence Processor: an accelerator architected around OpenAI’s vision for the future of LLM inference, and the first AI accelerator in a multi-generation compute platform the companies are building together to make advanced AI faster, more reliable, and more accessible to more people.

Jalapeño was co-developed from initial design to manufacturing tape-out in just nine months, and the custom AI accelerator program represents what we believe to be the fastest ASIC development cycle ever achieved in high-performance advanced semiconductors. That speed reflects deep software-hardware co-development with OpenAI’s engineering teams, Broadcom’s silicon implementation expertise, and the use of OpenAI models to accelerate parts of the design and optimization process.

IBM Debuts World’s First Sub-1 Nanometer Chip Technology

IBM’s new sub-1 nm chip packs nearly 100 billion transistors onto a chip the size of a fingernail, nearly twice the density of IBM’s 2 nm chip, unveiled in 2021. Enabled by a series of structural and material innovations, including IBM’s groundbreaking three-dimensional nanostack architecture, the technology demonstrates how continued gains in performance and efficiency remain possible even as chip features approach atomic dimensions.

To produce this chip, IBM researchers developed an entirely new transistor architecture, called “nanostack,” the industry’s first known three-dimensional, nanosheet-based design /IBM Research/. Nanostack represents a major advance beyond nanosheet technology, the industry’s current leading-edge architecture, invented by IBM. The nanostack design vertically stacks and staggers transistors, taking advantage of 3D sequential integration to pack more transistors onto a chip. The design also unlocks the use of different material combinations within each stacked layer, optimizing performance and power efficiency of each transistor independent of the other.

Introducing Un-0: Generating Images with Coupled Oscillators

The best AI models today are conventional deep networks with transformer backbones. However, there is also a long history of alternatives that seek energy efficiency by leveraging the dynamics of a physical system, such as the noisy, time-varying behavior of analog circuits that compute with analog voltage and current instead of conventional digitized numbers.

To exploit these alternative computing methods, the AI task needs to be mapped efficiently to the dynamics of the physical system. Un-0 validates that modern AI workloads can run more efficiently on physical substrates than on today’s hardware.

Why oscillators? In the brain, rhythmic activity and synchronization are pervasive, and have long been hypothesized to do computational work like binding distributed features into coherent percepts, gating communication between regions, and organizing the timing of spikes (Gray et al., 1989; Buzsáki, 2006; Fries, 2015). Coupled oscillators are among the simplest mathematical models of that kind of behavior, which makes them a natural primitive to study for neuro-inspired models of computation (Winfree, 1967; Kuramoto, 1975; Ermentrout, 1996; Ermentrout et al., 2010).

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

Qualcomm to Acquire Modular

As AI scales, efficiency, not capability, becomes a constraint. Performance-per-watt drives the cost of inference, and cost determines what scales. Meeting this demand requires more than hardware. Developers need software that connects system-level optimization with heterogeneous, disaggregated compute, turning silicon performance into reliable and efficient AI services across accelerators, environments, and use cases.

Modular provides an open, AI-native software stack that enables AI to run efficiently across hardware architectures. Built by engineers who helped create much of today’s AI infrastructure, Modular’s unified platform runs models with industry-leading performance across CPU, GPU, NPU, and custom ASIC architectures without re-writes for each accelerator. For developers and enterprises, that means building once, deploying across any environment with lower total cost of ownership. Modular is supported by an open, industry-friendly, vendor-neutral developer community committed to improving the portability and efficiency of AI infrastructure.

Nearfield Instruments Secures $380 Million Series D Funding in Largest Ever Deep-Tech Funding Round in The Netherlands

Nearfield Instruments, a leader in advanced semiconductor 3D metrology and process control, announced the successful closure of a $380 million Series D funding round. The transaction values the company at $1.6 billion, marking a major milestone in Nearfield’s development into a global leader in semiconductor metrology and inspection.

Nearfield’s innovative metrology and inspection solutions provide the accurate, reliable and high-throughput measurements needed to control advanced processes, improve yield and ensure manufacturability. By enabling critical measurements for High Numerical Aperture Extreme Ultraviolet (High-NA EUV), Gate-All-Around (GAA) and Complementary Field-Effect Transistor (CFET architectures), and hybrid-bonded 3D integration, Nearfield plays a central role in making the next generation of AI computing scalable, energy-efficient, manufacturable and reliable.

Read more at Business Wire

Agility Robotics to Go Public Through Merger with Churchill Capital Corp XI

Agility Robotics, Inc., a leading humanoid robotics and physical AI company, and Churchill Capital Corp XI (NASDAQ: CCXI) (“Churchill”), a publicly traded special purpose acquisition company, announced they have entered into a definitive business combination agreement. Upon closing of the Transaction, the combined company is expected to operate as Agility and be listed on a major North American exchange under the ticker symbol “AGLT.”

Agility’s mission is to build robot partners that augment the human workforce and lead the adoption of humanoids everywhere. Its flagship humanoid robot, Digit, is a general-purpose, human-centric robot Made for Work™ and currently operating in manufacturing, distribution, and logistics environments to fill chronic physical labor shortages. Through more than a decade of development, Agility has established itself as one of the only humanoid robotics companies with multiple years of operational experience in real customer environments. The Company is supported by leading strategic investors and partners across the AI, technology, VC, and industrial ecosystem, including DCVC, NVIDIA, Amazon, SoftBank Vision Fund 2, Schaeffler, Foxconn, Abico, and Playground Global.

[Overcapacity] Are You Ready to Automate?

David Rogers — Sun, 21 Jun 2026 16:01:27 GMT

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This weeks digest:

Are You Ready to Automate?

David Rogers — Sun, 21 Jun 2026 13:00:29 GMT

Shop Talk

Capturing this week’s zeitgeist

The magic of the Automate Show is the feeling that you are stepping directly into the future, where the cutting edge of industrial tech becomes a tangible, hands-on reality. As thousands of engineers, founders, and industry leaders gather this week at McCormick Place, the show floor transforms into a high-energy hub of live demonstrations, breakthrough AI, and game-changing humanoid robotics. Whether you are watching groundbreaking ideas pitch live at the Startup Challenge or trading insights with peers between sessions, it is a unique space where the next big technology and the right connection come together to reshape your business.

A few interesting exhibitors I’ve had the pleasure of first connecting with at previous Automate shows:

Copia Raises $26M in Funding to Unify OT Code Management, Backup, and Recovery /PR Newswire/ used to accelerate Copia’s mission to bring modern code management and recovery capabilities to the operational technology (OT) teams who are the first responders in the event of an industrial cyberattack or downtime incident.
Podium Automation Raises $18M Series A to Modernize the Backbone of Industrial Automation /PR Newswire/
CESMII Releases i3X™ 1.0: A Complete, Implementation-Ready Open API Specification for Manufacturing Interoperability /CESMII/

Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

🇪🇺🏭🧠 AI for Industry Is Europe’s Hope to Salvage Manufacturing Edge

While Europe may have lost the consumer chatbot wars to the US and China, a critical new battleground is emerging on the factory floor. European manufacturers are racing to integrate industrial AI using real-time sensors, predictive maintenance software, and automated quality control to create highly efficient, autonomous “smart factories.” This transition is a matter of survival, with over $1 trillion in manufacturing value at risk of leaving Western Europe due to high costs and labor shortages. However, the clock is ticking: industry experts warn that Europe has a narrow two-to-three-year window to successfully deploy these advanced systems before falling irreversibly behind Asian competitors, who are moving rapidly to combine robotics and AI.

🖨️🔋 The Secret Revolution in Battery Technology: 3-D Printing

The core uniqueness of 3D-printed battery technology lies in its ability to transform energy storage from a rigid, predetermined component into a fluid structural element that can fill any arbitrary geometry or empty space within a device. Unlike traditional manufacturing, which relies on chemical innovations and standard cylindrical or pouch shapes, this additive manufacturing approach is entirely chemistry-agnostic—boosting existing lithium-ion, sodium-ion, and solid-state designs alike. Furthermore, it revolutionizes the production process itself by enabling a solvent-free dry manufacturing method that eliminates massive, energy-intensive drying ovens, drastically reducing production footprints while making complex, high-capacity material designs physically viable.

🦾🧠 An Overview of Modern AI Robotics from First Principles

There is a deceptively simple way to describe what physical AI is all about, a way in which anyone with a STEM background will intuitively understand. Like all other AI models, a model which controls a robot is also a function. It takes in observations (camera pixels, joint angles, the felt resistance of a gripper, etc) and it outputs actions, the next set of positions and torques for its motors. Everything else, all the complicated algorithms, training methodologies, and data scaling theories are in service of producing a good version of that function and embedding it into the weights of a neural network.

The way out is the way humans learn: practice, against a critic. This is reinforcement learning: letting the robot try, scoring the outcome, and reinforcing what worked. The catch is that you can’t supervise a robot at every moment or hand it an example for every possible situation, and in the real world (unlike a simulator) attempts are serial, slow, and require a human to reset the scene. RL in the physical world proves very difficult as a result. Self-improvement algorithms hence fix major bottlenecks in performance for robotics, especially with regards to generalization.

New Product Introduction

Highlighting new and innovative facilities, processes, products, and services

🧫 Launching Midjourney Medical & The Midjourney Scanner

The major computational task is figuring out how to change waves into images. Basically - as waves travel through the water and your body they change shape. The shape of these waves changes whenever there is a change in density or stiffness (i.e., going from water to skin to fat to muscle to bone). By looking at how the shapes of all the waves change, we reconstruct a detailed map or ‘image’ which basically lets us figure out what’s in there. All of these images come together to cover a 3D map of your body, down to a fraction of a millimeter, that looks a lot like today’s MRIs but at nearly a hundred times the speed.

The next 12 months are about refining our algorithms and hardware on a daily basis. We’ll be doing research trials to show off the raw capabilities of our system, moving towards a 2nd generation hardware design, and we’ll do build-out for our first “research spa” which will become the promethean site that enables mass-scale health scanning.

🦾🧠 Qwen-Robot Suite: A Foundation Model Suite for Physical World Intelligence

The Qwen family of foundation models already gives strong perception and reasoning about the physical world. But seeing is not acting: the gap between vision and language understanding and physical control remains the central bottleneck for embodied intelligence. The Qwen-Robot Suite bridges this gap with three foundation models — Qwen-RobotNav, Qwen-RobotManip, and Qwen-RobotWorld. Nav unifies five navigation task families through a controllable observation protocol. Manip turns heterogeneous robot data into a coherent canonical space, enabling cross-embodiment training at scale. World co-trains 20+ embodiments via a natural-language action interface under one world model. Together, they enable an agentic system where general intelligence translates directly into physical action.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

🇨🇭♻️ GR3N raises €15.5M to build the world’s first microwave-powered PET recycling plant / TNW/. GR3N’s technology, called MADE (Microwave Assisted DEpolymerisation), can process all PET.

🇪🇸🦾 THEKER raises €73M to deploy AI-native factory robots that learn on the job

THEKER, the Barcelona-based AI robotics company, has raised €73 million ($85 million) in a Series A to scale its generalist factory robots across industrial production environments. The round was led by CRV, with participation from Samsung, LVMH, Cathay Innovation, 20VC, Henkel Ventures, Korelya, and Bright Pixel Capital. It marks Samsung’s first-ever investment in a Spanish company, LVMH’s first bet on the Spanish startup ecosystem, and CRV’s first investment in Spain.

The round comes less than a year after THEKER closed Spain’s largest-ever seed round at €18 million. The speed from seed to Series A reflects what the company calls real commercial deployment momentum, not just lab demos.

THEKER’s pitch is a new category of industrial robot: AI-native, generalist machines that adapt in real time to changing environments, mixed SKUs, irregular shapes, and operational variability without manual reprogramming. Unlike traditional industrial robots that are rigid and costly to reconfigure, THEKER says its systems deploy in days and continuously learn in production.

🇺🇸🪙 Foundation Alloy Industrializes New Metals Platform with $22M Series A

Foundation Alloy, the 21st-century metals company building a new way to engineer alloys, today announced $22 million in Series A financing to scale production on its MetalsFIRST™ platform—a fully integrated, solid-state metallurgy technology—to industrial volumes. The round was led by Voyager Ventures, with participation from Trust Ventures, Yamaha Motor Ventures, America’s Frontier Fund, Overlap Holdings, Material Impact, Engine Ventures, and El Cap.

Foundation Alloy’s MetalsFIRST approach is a fully integrated, solid-state platform encompassing composition design, mechanical alloying, shape forming, and sintering, that produces engineered alloys without ever entering the molten state. This process enables faster, simpler manufacturing cycles, capital-efficient industrial scale up, and access to alloy compositions and properties impossible to achieve with legacy melt processes. Foundation Alloy’s specialty and stainless steels are engineered for the most demanding applications while requiring 80%–90% fewer production steps, while its Molyclast® product line includes MC1200, a molybdenum alloy that delivers more than 3x the strength of commercial alternatives. This combination of superior performance and manufacturability unlocks new capabilities for demanding applications across the industrial space.

The funding transitions Foundation Alloy into an industrial supplier. This summer, the company is opening a new 36,000 sqft facility in Massachusetts, standing up an additional modular production cell with Re:Build Manufacturing in southern New Hampshire, and doubling headcount across production, engineering, and commercial operations.

🇺🇸♨️ Critical Energy Raises $22M to Mass-produce Modular Geothermal Turbines

Based in Los Angeles and founded in 2024 by Spencer Jackson, Critical Energy just closed a seed round led by Susa Ventures and Upfront Ventures. Other investors include MaC Venture Capital, Susquehanna Sustainable Investments, Humba Ventures, Scribble Ventures, Underground Ventures, and Silicon Valley Bank, which provided venture debt.

Critical Energy designs modular geothermal turbines. These are container-sized units built in-house that turn heat into electricity using a closed-loop fluid system and custom machinery. The company says it can reduce deployment times from years to weeks by building most of the system off-site. It has already built a pilot facility in Los Angeles and is moving toward larger commercial projects.

[Overcapacity] Logistic Constraints to Scoring The Goal

David Rogers — Sun, 14 Jun 2026 16:01:46 GMT

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Logistic Constraints to Scoring The Goal

David Rogers — Sun, 14 Jun 2026 13:03:11 GMT

Shop Talk

Capturing this week’s zeitgeist

When we tune into a massive sporting event, we’re usually watching the athletes, but behind the scenes, a different kind of elite performer is keeping the whole show from collapsing. YOU. This year’s modern sports spectacles are high-stakes marvels of heavy industrial engineering, where prepping a venue means pushing logistics and science to their absolute limits. Whether it’s turfgrass scientists treating the 2026 World Cup pitches like a living "layer cake" /UT/, growing stadium sod in Colorado and racing it across the country in refrigerated trucks to beat the clock /YouTube/, or structural engineers dropping a 600-ton, 92-foot-tall steel behemoth nicknamed "The Claw" directly onto the historic White House lawn for UFC Freedom 250 /ESPN/, the margin for error is zero. This week we explore the incredible technology changing agronomy, role of the robots and AI, and precision logistics. Enjoy!

Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

Why robotic arms are now being integrated with CNC machines

✍️ Authors: Lou Ferrell

For years, automation in CNC environments meant a dedicated unit performing one task. Modern integrations look different. A robotic arm now loads a raw blank, transfers it between machines, inspects the finished part, and routes it downstream — all without human involvement.

The infrastructure being built today by FANUC, Universal Robots, KUKA, ABB and RoboDK is already functional. What remains an open question is how much further the role of the robot expands as artificial intelligence matures. A robot that loads a part today follows fixed logic. But one that monitors spindle load, detects tool wear in real time and decides autonomously whether a part passes inspection is an entirely different kind of participant in the manufacturing process.

What Can SLS 3D Printing Really Do? | The SLS Mindset

Selective laser sintering (SLS) is one of the most capable AND one of the most overlooked additive manufacturing processes for polymer parts. In this episode of the SLS Mindset series, Nate Stevens of Lifestyle Additive and explore what makes SLS different: no supports, complex geometry without compromise, assembly consolidation into single parts, and production-ready material performance.

Formlabs’ new 3D printer is poised to reshape manufacturing /Fast Company/. The Fuse X1 is designed to bring large-format SLS printing to more engineering teams and production lines. The new machine is a selective laser sintering (SLS) printer built for manufacturers, engineering teams, product developers, and 3D printing service bureaus. The printer can turn out production-quality parts in less than 24 hours. (It starts at $84,999, is available for order today, and is expected to begin shipping in the fourth quarter of 2026.)

BlueME: Robust Underwater Robot-to-Robot Communication Using Compact Magnetoelectric Antennas

✍️ Authors: Mehron Talebi, Sultan Mahmud, Adam Khalifa, Md Jahidul Islam

We present the design, development, and experimental validation of BlueME, a compact magnetoelectric (ME) antenna array system for underwater robot-to-robot communication. BlueME employs ME antennas operating at their natural mechanical resonance frequency to efficiently transmit and receive very-low and low-frequency (VLF/LF) electromagnetic signals underwater. We detail the system’s design, simulation, fabrication, and integration onto low-power embedded platforms, emphasizing portability and scalability. For performance evaluation, we deployed BlueME on mobile robot platforms in freshwater (lake) and saltwater (ocean) trials. Our tests demonstrate reliable signal transmission and detection using the BlueME antenna system at distances beyond 700 m while consuming less than 10 W of power. Ocean trials demonstrate that the system operates effectively under challenging conditions, such as turbidity, obstacles, and multipath interference, which are factors that typically degrade acoustic and optical methods. Our analysis also examines the impact of complete submersion on system performance and identifies key deployment considerations. This work represents the first practical underwater deployment of ME antennas outside the laboratory and implements the largest VLF/LF ME array system to date. BlueME demonstrates significant potential for marine robotics and automation in multirobot cooperative systems and remote sensor networks.

New Product Introduction

Highlighting new and innovative facilities, processes, products, and services

This Nvidia Challenger Says Its AI Chip Is 10x Faster Than A GPU

There’s a new challenger to Nvidia that says its chip can run AI inference at ten times the speed of a standalone GPU. The new chip from D-Matrix is called Corsair, and it’s now in volume production with commitments from hyperscalers, neoclouds and frontier AI labs. In an exclusive interview with CNBC, CEO Sid Shath explains how Corsair bypasses the DRAM shortage by relying on SRAM directly on the chip, and how that tight integration means Corsair can transfer data using five times less energy. It’s a novel approach to memory that’s led to huge gains for other chip startups in recent months. Cerebras’ blockbuster $95 billion IPO in May landed it among tech’s largest ever debuts, and Groq received $20 billion from Nvidia in the AI giant’s largest purchase ever in December. Now CNBC asks whether D-Matrix could be next.

Inside The Chip Factory 1,000 Times Cleaner Than An Operating Room /YouTube/
Rapidus Completes 150 Billion Yen Funding Round from Japan Government /PR Newswire/ to support its evolution from the R&D stage to full-scale 2nm logic semiconductor manufacturing by 2027.
TensorWave Raises $350 Million Series B at $1.55B Valuation to Expand Global AMD-Powered AI Infrastructure /Business Wire/
Granarium Technologies raises EUR 1 million to commercialise the world’s first renewable, affordable supercapacitors for grid stability and industrial reliability /PR Newswire/

Claude Fable 5 and Mechanical Design (V8 engine)

Claude Fable 5 and Claude Mythos 5 /Anthropic/. Fable 5 is state-of-the-art on nearly all tested benchmarks of AI capability, showing exceptional performance in software engineering, knowledge work, vision, scientific research, and many other areas.

Statement on the US government directive to suspend access to Fable 5 and Mythos 5 /Anthropic/. Anthropic suspends new AI tools over US government security concerns /BBC/.
Will AI-augmented CAD make manufacturability easier to integrate into design? /Brain Ratliff on X/
Robotics will not have a clean Llama moment /The Robot Report/

We’re Raising the Curtain: Introducing Azumuta Labs

It’s a working space where we run real experiments, put prototypes in front of real operators and engineers, document what happens, and share it here before we have all the answers.

That means you’ll see results that surprised us. Approaches that didn’t work out. Ideas that are solid in a controlled environment but need more work before they’re production-ready. We’ll share all of it, including the failures, because the path to useful manufacturing AI is shorter when we stop repeating each other’s dead ends.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

NEURA Robotics Announces Record Series C of up to $1.4 Billion to Accelerate the World’s Leading Physical AI Platform

NEURA Robotics, the pioneer in cognitive robotics and creator of the Neuraverse, announced a landmark Series C financing with a total round size of up to $1.4 billion to accelerate its mission of building the world’s leading Physical AI platform. The financing brings together global leaders across AI, robotics, compute, manufacturing and industrial infrastructure, including Tether, Qualcomm Technologies, Inc., Amazon, NVIDIA, imec.xpand, Bosch, Schaeffler, European Investment Bank, Lingotto Horizon, InterAlpen Partners and others.

NEURA is building a new category of AI infrastructure where cognitive robots continuously learn, collaborate and operate across real world environments through a shared intelligence ecosystem called the Neuraverse. Unlike traditional robotics companies focused on isolated machines or narrow industrial automation, NEURA combines robotics, AI, sensors, edge compute and large scale learning infrastructure into one unified platform architecture designed for global deployment.

Read more at Business Wire and The Robot Report

PhysicsX Announces $300M Series C to Accelerate Physics AI for Industrial Engineering

PhysicsX, the physics AI company for industrials, announced an oversubscribed $300 million Series C financing at a valuation of approximately $2.4 billion. The round is led by Temasek, with participation from new investors M&G Investments and Intrepid Growth Partners, alongside existing investors including Applied Materials, Atomico, General Catalyst, July Fund, NGP, NVIDIA, Radius, and Siemens. Temasek first invested in PhysicsX in 2025, and has played an instrumental role in supporting the company’s international expansion and growth.

This round will accelerate the company’s global growth, the expansion of its platform capabilities, and frontier research, including the development of larger, more powerful pre-trained physics AI models, known as Large Physics Models /arXiv/.

Standard Bots Raises $200 Million Series C At $1 Billion Valuation To Scale AI-Native American Robotics

Standard Bots, the largest U.S. manufacturer of AI-native industrial robots, announced a $200 million Series C financing led by RoboStrategy and existing investor General Catalyst, valuing the company at $1 billion.

The funding will support the expansion of the company’s manufacturing footprint in Glen Cove, New York, where Standard Bots is increasing its facility to 70,000 square feet. The company said the expanded operation will strengthen its ability to design, assemble, and deploy American-made robots at scale.

Read more at PR Newswire and The Robot Report

Mesoware Announces $1.5M to Build AI-Powered Robots for Manufacturing /Manufacturing Tomorrow/

Innovafeed raises $59m, scales production, cuts R&D headcount as insect ag hits “industrialization phase”

French insect ag firm Innovafeed has raised a €51 million ($59 million) round and unveiled plans to consolidate activities at its commercial-scale black soldier fly larvae production facility in Nesle, France.

The round, which takes its cumulative funding including grants to over $500 million, was backed by existing shareholders Creadev, QIA, Temasek, FFC, ABC Impact, and ADM along with banking partners, said Innovafeed, which was founded in 2016 by Aude Guo, Bastien Oggeri, and Clément Ray.

Maneva Raises $27M to Tackle Inefficiencies Across the $46T Manufacturing Industry

Maneva, the Video-to-Action AI company building the intelligence layer for modern manufacturing, announced $27 million in Series A funding, accelerating its mission to close the $18 trillion global manufacturing efficiency gap. The Series A round was led by U.S. Venture Partners (USVP), with participation from returning investors Bling Capital and Freestyle Capital, alongside a group of leading angel investors and funds. This fundraise brings Maneva’s total capital raised to $38.4M.

Maneva’s Video-to-Action AI turns existing factory cameras into real-time operational decisions. It begins with deep learning computer vision, giving factories the ability to see, understand, and act on what’s happening on the floor, then expands into agentic systems that connect, coordinate, and optimize the entire operation. It is the deep learning engine for modern manufacturing, and the foundation of everything Maneva builds.

[Overcapacity] Glass Half Full of Pinball Manufacturing

David Rogers — Sun, 07 Jun 2026 16:01:30 GMT

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This weeks digest:
https://substack.exponentialindustry.com/p/glass-manufacturing-ai-pinball

Glass Half Full of Pinball Manufacturing

David Rogers — Sun, 07 Jun 2026 13:00:28 GMT

Shop Talk

Capturing this week’s zeitgeist

The enduring success of Stern Pinball offers valuable lessons in managing production complexity at the intersection of heritage craftsmanship and modern tech. While often perceived as a nostalgic pastime, manufacturing a pinball machine is an intensive engineering challenge that requires balancing thousands of unique parts within a highly constrained physical footprint. As an avid player myself, I closely followed Austin Weber’s coverage of Stern’s operational evolution and took away the following core lessons:

Intricate Packaging & Multi-Disciplinary Design: Each machine represents a dense engineering and spatial challenge. Design teams must integrate thousands of distinct parts, from mechanical solenoids to digital HD displays, within a fixed footprint. This requires tight synchronization between mechanical, electrical, and software engineering during a long development cycle.
The Physics of Quality Control: Because pinball is an entirely physical, physics-based experience, there is zero margin for error in geometry. A fraction of a degree in playfield tilt or a millimeter of deviation in a ramp’s placement completely alters the game’s flow, making precision physical placement a critical quality baseline.
Labor Efficiency Over Automation: Stern demonstrates that for certain high-complexity, high-variety products, manual craftsmanship remains superior to robotics. With 18 to 24 labor hours required per unit, the assembly line relies on highly organized human cells to navigate the unique wiring harnesses and mechanical subassemblies specific to each title.
Technological Convergence: A modern machine is a complex hybrid system. It must seamlessly balance legacy electromechanical feel (pop-bumpers and flippers) with modern digital infrastructure like IoT connectivity and advanced animatronics, forcing a design philosophy that respects tactile tradition while adopting modern software standards.
Operational Flexibility: Because the company juggles multiple high-profile pop-culture licenses and various model tiers (Pro, Premium, Limited Edition), the factory floor must remain highly agile. The lesson here is the value of a flexible manufacturing layout that can pivot production focus rapidly to align with real-time market demand.

Some of my favorite pinball machines over the years. I recommend stopping into the Pinball Hall of Fame in Las Vegas next time you’re there!

Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

☀️ How One Man Powers a Global App from a Dutch Cow Barn

Just outside Amsterdam, a converted cow barn is quietly running a global payment app used by over a million people around the clock. To keep it online, Wietse Wind and his installer Danny built a massive 540 kWh LiFePO4 storage system with 150 solar panels, multiple Quattro-II and MultiPlus-II inverters, and full grid redundancy using Victron Energy equipment. This is the story of the largest residential ESS install either of them had ever built.

🐂 A North Dakota startup raised $10 million from ranchers and neighbours to build the operating system for beef cattle /TNW/

🎛️ State of Digital in Process Manufacturing

✍️ Author: Dimitris Paraskevopoulos

Prior IoT Analytics research, specifically on IoT use cases, has found that process manufacturers typically lag behind discrete manufacturers in adopting digital technologies. This is largely due to long asset replacement cycles (more than 50 years in some cases), among other reasons. Oil & gas, though, is often regarded as ahead of other process industries due to its remote nature, with established SCADA and remote connectivity architectures.
Smart sensors top the list of most deployed technologies for process manufacturers. Companies are also adopting bolt-on wireless sensors, such as US-based industrial AI company Augury’s bolt-on Halo sensors, which monitor machine parameters such as vibration, temperature, and magnetic field data and transmit insights to the cloud for AI-driven analysis.

🫙 AI for the Glass Industry

Georg Katzlinger explores the surprising complexity of the flat glass industry and the unique challenges it faces including how AI solutions are revolutionizing the way custom glass orders are processed, from deciphering handwritten requests to integrating with legacy ERP systems. Georg shares his journey from engineering to AI entrepreneurship, revealing why deterministic, human-in-the-loop automation is essential for manufacturers.

💿 A new way to build chips: Sequentially stacking silicon to extend Moore’s law

✍️ Author: Michael O’Boyle

The most efficient approach, known as monolithic three-dimensional integration, builds each layer directly on top of the previous one to maximize interlayer connectivity. However, achieving this has been a longstanding technical challenge. Preparing high-quality silicon and fabricating high-performance devices normally require processes operating at 1,000 degrees Celsius, hot enough to destroy the metal wiring. For upper layers beyond the first, the temperature constraint, or “thermal budget,” is strictly set to 400 degrees.
Current commercial three-dimensional chips are made by fabricating semiconductor devices on separate wafer substrates first and then bonding those wafers or dies together. While this approach has enabled successful products such as high-bandwidth memory and 3D V-Cache chips, it comes with substantial limitations. The alignment between layers is necessarily coarse, and the micron-scale vertical connections between layers called through-silicon via or TSV are relatively large and sparse.

Read more at University of Illinois and Nature

💿🤝 NVIDIA and TSMC Bring AI Into Fabs to Advance Semiconductor Design and Manufacturing /NVIDIA/

🚀 Tom Mueller: SpaceX’s #1 Employee Built the Merlin Engine. Now He’s Building Impulse Space

🚀 Impulse Space Raises $500M Series D to Build In-Space Mobility Infrastructure for the Space Economy /GlobeNewswire/

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Siemens powers the next phase of industrial AI with Intelligence Center X

Siemens announced Intelligence Center X, new industrial AI orchestration software designed to help organizations turn industrial AI from isolated experimentation into scalable, real world business impact through a hybrid workforce where people and AI agents work together with shared context, workflows and lifecycle intelligence.

By connecting data, models and workflows on a single governed foundation, Intelligence Center X enables companies to deploy AI-driven applications and agents faster, with full traceability and control. Intelligence Center X combines the Mendix™ low-code platform with Siemens’ Graph Studio and AI Studio software from the Rapidminer® portfolio to create the enterprise context, business-specific lifecycle intelligence, and orchestrated agents and intelligent applications businesses needed to turn AI ambition into real value gains. Across industries, companies have invested in AI but are struggling to scale beyond pilots because data is fragmented, governance is inconsistent, and AI insight does not connect to real workflows. Intelligence Center X is designed to close that gap as the production-ready system that orchestrates people and AI agents together, on top of what enterprises already own, with full auditability and policy controls.

🖨️🛥️ Voltage Vessels and CEAD developed a demonstration platform using LFAM, which is informing Voltage Vessels’ basalt fiber-reinforced PETG material developments

✍️ Author: Grace Stubbins

Voltage Vessels (Maui, Hawaii, U.S.), a startup founded by Sam Young, has submitted a 6-meter 3D printed rigid hull inflatable boat (RHIB) prototype for U.S. maritime defense evaluation. The hull’s technical execution was led by CEAD (Delft, Netherlands), using its large-format additive manufacturing (LFAM) system — an industrial-scale printer used by multiple defense contractors for hull-scale composites production — and HDPro thermoplastic composite (TPC) materials.
Separate third-party testing commissioned by Voltage Vessels measured the materials’ tensile strength along the print direction at roughly 108 MPa, versus approximately 49 MPa for the HDPro composite used as a benchmark. Eclipse X9 also retained more than 90% of its strength after long-term saltwater immersion, with water absorption below 0.4%. Additional testing performed at the University of Maine’s Advanced Structures and Composites Center (UMaine ASCC) further validated the material’s mechanical performance under project ID UM-TC-23-1008.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

🤝 Fanuc, Google advance industrial robotics as part of recent AI deals /Manufacturing Dive/

🇩🇪🦾 SoftBank in Early Talks to Back $800 Million Agile Robots Round

Agile Robots is in discussions to raise about $800 million in new funding from backers including SoftBank Group Corp., as investors seek out companies deploying artificial intelligence in real-world settings. SoftBank is in talks to contribute more than $300 million, according to people familiar with the matter, who asked not to be identified as the information is private. The company previously led a funding round in Agile Robots.

🇮🇱 DriveNets secures $410 million in latest funding round, AMD joins as investor

DriveNets, an Israeli networking software firm, said it has raised $410 million in its latest funding round led by Bessemer Venture Partners ‌and Atreides Management, taking its total capital-raise so far to $1 billion. New investors AMD and Red Dot Capital joined the round, while existing investors Pitango and D1 Capital Partners also participated. The company would ⁠use the proceeds to meet the surging demand for large-scale AI infrastructure, CEO Ido Susan said.
DriveNets allows telecommunications operators and data centers to build and manage networks using standard, off-the-shelf hardware, rather than costly proprietary systems. ⁠Its technology supports high-speed connectivity and AI workloads.

🇺🇸⛏️🧠 Terra AI raises $20M to Accelerate Mineral and Reservoir Exploration to Meet Global Critical Mineral and Energy Demands

Terra AI, the artificial intelligence platform helping solve subsurface uncertainty for mineral and energy development, announced it raised $20 million Series A led by Khosla Ventures and strategic investment from BHP Ventures.

Terra AI’s patented technology integrates nearly every type of exploration data to generate millions of geological models, enabling teams to evaluate a comprehensive range of potential subsurface scenarios. This allows project teams to identify the best drilling and geophysical approaches to reduce key uncertainty and rigorously assess project economics earlier than ever before. By going beyond geological visualization and delivering risk-quantified decision insights, Terra AI helps explorers on virtually every important decision across their portfolio from determining which assets to acquire in a portfolio to accelerating and de-risking resource development efforts. The outcome: resource pipelines are developed faster and more efficiently to help the world meet its resource needs.

🇺🇸👓 Phosio Raises $4 Million Seed Round to Bring Affordable AR/AI Glasses to Mass Market

Phosio announced the closing of a $4 million seed financing round to accelerate commercialization of its thin-film materials platform for next-generation AR/AI glasses. The round was led by MESH, with participation from Sierra Ventures, TEL Venture Capital, Silicon Catalyst Venture, Willamette Valley Capital, and Silicon Catalyst Angels.

As AI shifts from phones to ambient interfaces, the industry is racing toward lightweight, all-day wearable glasses. But optics and display costs remain the biggest barrier to mass adoption. Today’s AR/AI glasses rely on complex, costly display systems that are bulky, power-hungry, and difficult to manufacture at scale. Phosio’s proprietary thin-film platform integrates high-performance display functionality directly into lightweight, everyday eyewear, eliminating the cost, bulk, and power demands that have slowed mainstream adoption.

Read more at Business Wire

🇺🇸🪪 Alitheon Secures $8 Million Series A1 to Scale “Biometrics for Things” Across Global Supply Chains /PR Newswire/

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Constraint Capital #6 - June 2026

David Rogers — Mon, 01 Jun 2026 13:03:41 GMT

In his May 20th, 2026 interview on Invest Like The Best, Gavin Baker /X/ outlines several profound transformations and strategic maneuvers taking place within the AI infrastructure and data center landscape. Constraint Capital #6 tackles these maneuvers and the technology bottlenecks behind the SpaceX’s identified $28.5 trillion TAM /SEC/.

The three most important technology shifts and product development strategies Gavin highlights are:

The Disaggregation of Prefill and Inference and its Impact on Hardware Lifespans

One of the most critical structural shifts in how AI models run is the architectural decoupling of the “prefill” phase from the “decode” phase during inference [49:46].

The Shift: Baker explains that prefill—where the model processes and understands the prompt or input context—is fundamentally a memory capacity-bound problem [51:17]. Conversely, decode—the subsequent generation of output tokens—is a memory bandwidth-constrained process [51:25].
The Competitive Strategy: This canvas allows chip designers to make highly targeted, optimized trade-offs [51:32]. Startups (such as Groq or Cerebras) can build hyper-specialized chips optimized specifically for one part of this loop.
The Financial Impact: Crucially, Baker points out that companies can now stick specialized custom chips (like Cerebras wafer-scale hardware or Groq LPUs) in front of existing, older hardware architectures like Nvidia Hoppers or Amperes [49:46]. This approach uses the legacy GPUs for the prefill stage and custom silicon for decode, extending the useful economic lifespan of data center GPUs from 1–2 years to potentially 10–15 years [49:28].

Ongoing question for investors: How long before a GPU depreciates? /CNBC/

The Transition to Custom ASICs and the “Terafab” Talent Strategy

As standard GPU architectures face physical limits and intense market constraints, product strategy is shifting toward hyper-specialized ASICs (Application-Specific Integrated Circuits) and alternative foundry setups [43:30].

The Shift: Major players are leaning away from general GPUs to develop custom internal accelerators (e.g., Amazon’s Trainium 3) [43:30, 43:46]. To win, startups can’t just try to make a “better GPU”; they have to choose unique trade-offs within the “iron triangle” of hardware design (optimizing tightly for speed, memory, or cost) and do something fundamentally difficult to replicate [44:14, 47:58].
The Competitive Strategy: Baker highlights a major domestic foundry initiative (a joint venture involving SpaceX/Tesla, dubbed the “Terafab,” partnering with Intel) to establish bleeding-edge semiconductor manufacturing capacity in the U.S. [27:48].

The Financial Impact: Rather than operating like traditional corporate entities, Baker states that hardware leadership requires an aggressive, human-centric recruiting approach to compete with Taiwan Semiconductor (TSMC) [28:45, 29:59]. This includes recruiting elite global engineering talent and building highly accommodating cultural enclaves specifically tailored to entice the absolute best hardware minds to move and work domestically [30:15, 30:28].

All content published on this newsletter is based on public information and independent research. Opinions are authors own and have been sanitized through AI engines which can make mistakes. This newsletter is not financial advice, and readers should always do their own research before investing in any security.

Which leads to the last of the major maneuvers and the focus on this article…

The Move Toward “Orbital Compute” (Racks in Space)

[Overcapacity] Make Hardware as Nimble as Software

David Rogers — Sun, 31 May 2026 16:00:59 GMT

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Make Hardware as Nimble as Software

David Rogers — Sun, 31 May 2026 13:00:59 GMT

Shop Talk

Capturing this week’s zeitgeist

The magic of the "Apollo Moment" is about finding a buyer with a non-negotiable physical constraint who is willing to pay any price. That desperate buyer single-handedly seeds an immature technology until the cost curve drops enough for commercial adoption to take over. Diego Prats’ notes in his essay While everyone watches for the “ChatGPT Moment in Robotics”, don’t underrate the “Apollo Moment” that NASA and the military served as patron for integrated circuits. However, during this exact same 1960s Apollo era, the exact same thesis, that government backing or venture capital could bridge the gap for radical new tech with strict constraints, led to massive, historic bets that went completely awry:

The Supersonic Transport (SST) Race: The U.S. government spent over $1 billion on Boeing’s Mach 3 passenger airliner before canceling the program in 1971 due to insurmountable weight issues, soaring costs, and severe sonic boom restrictions.
The “Timesharing” Capital Collapse: Tech conglomerates like Xerox and General Electric lost hundreds of millions betting on premature decentralized computer networks before the underlying software infrastructure and market demand actually existed.
The 1961–1962 “Tron” Bubble: Speculative investors poured millions into any startup with a space-sounding name, resulting in a violent market crash when these companies failed to secure actual buyers with non-negotiable technical constraints.
Commercial Automotive Fuel Cells: Automakers bet heavily that the lightweight hydrogen fuel cells powering Apollo capsules would rapidly replace internal combustion engines, but the costs of space-grade catalysts never declined far enough to be viable.

This is exactly why we launched Constraint Capital. Issue #6 drops tomorrow, where we focus on the high-stakes, unyielding bottlenecks defining the Second Space Age led by companies like SpaceX. Upgrade to a paid subscription today to back our research and power the publication. 👇

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How engineer Ernest Eldridge advanced the art of supercharging in the 1920s /IMechE/

Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

🦾🧠 This $440 Million Startup Is Solving Robotics’ Biggest Problem

Meet Generalist, the startup that says the next big leap in robotics won’t come from fancier humanoid hardware. It will come from applying AI scaling principles to physical work, and turning messy everyday tasks into killer training datasets.

🗣️ Jagdeep Singh built QuantumScape and Infinera. His next company Rhoda trains robots to become fully operational by watching YouTube videos — in 10 hours, not 10,000. /CLIMB on YouTube/

⛴️ How Candela’s flying ferries could bring commuters back to the water

At Candela, they make hydrofoiling electric boats and ferries that are the first to combine long range with high speed. Their innovative hydrofoil technology cuts energy use by 80%, creating silent, fast, zero-emission vessels with unmatched efficiency.

⛏️ What 16 Drones Across 4 Mining Sites Looks Like: Real-Time BVLOS Drone Operations in Queensland

RocketDNA has deployed 16 drones across 8 pads at four BMA sites in Queensland, delivering real-time geospatial intelligence across 80km+ of continuous mining operations.

⛏️ Rock Zero’s new extraction process could unlock the world’s lithium /MIT Technology Review/ which could cut costs and carbon emissions from lithium production.

🔋 Why This Mars Battery Could Beat Lithium-Ion

Noon’s system pulls CO2 from the air and splits it into solid carbon and oxygen using electricity. The oxygen vents back to the atmosphere; the carbon is what stores the energy ... it’s the fuel sitting in the tank. To discharge, the carbon is reoxidized inside a solid oxide fuel cell, recombining with oxygen back into CO2 and releasing electricity as it goes. No net carbon released over a full cycle.

🌬️ China launches offshore wind-powered underwater AI data centre /Techwire Asia/

📐🧠 “Our Goal Is to Build an Electrical Engineer.” (Davide Asnaghi, Co-Founder & CEO of Diode)

Since its founding just two years ago, Diode has landed Physical Intelligence and Saronic as customers and partnered with Anthropic to help Claude become a better electrical engineer. The company’s ultimate ambition: to make hardware as nimble as software.

📐🧠 Itera Exits Stealth With $12M to Bring Real-Time Prototyping to Electronics /Business Wire/
📐🧠 Quanscient raises €10 million to scale its multiphysics simulation platform for the AI era /EU Startups/

Crucible Capital

Reshaping a Broken Industrial Robot Market: Introducing the Era of Physical AI + Robotics as a Service with Verne

If I held a gun to your head and asked you to guess the market value of a century-old industry that out-precisions human laborers by a factor of five and has reduced manufacturing injuries by more than 60 percent, you would probably guess something massive. Industrial robotics is only worth roughly ~$20 billion (Estimates vary by source; this is the bal…

a month ago · 10 likes · Aditya Jha, Neil Nie, Kelly Greer, Honour Masters, and Meltem Demirors

Former NASA Robotics Chief: America is building the wrong kind of robots — and China knows it /Fortune/

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📶 RNG: Flat Datacenter Networks at Scale

We design and deploy in production the first flat datacenter networks. Our design, called RNG, is based on quasi-random graphs. While the cost and fault-tolerance benefits of such topologies have been long known, their practical realization has been hampered by a lack of scalable routing and cabling approaches. RNG has a new distributed routing protocol that exploits the properties of random graphs to find a large number of edge disjoint paths between pairs of endpoints. It uses a novel passive optical device that internally shuffles cables, which makes its cabling complexity similar to that of fat trees. We show that RNG matches or exceeds the performance of fat trees for a range of traffic patterns, despite being up to 45% cheaper. RNG is now the default datacenter network for most workloads at Amazon.

🖨️💡 High-efficiency multi-scale holographic volumetric 3D printing with a phase light modulator

✍️ Authors: Maria Isabel Álvarez-Castaño, Riccardo Rizzo, Viola Sgarminato, et. al.

Light-based 3D printing with photocurable resins enables the rapid fabrication of complex structures with high resolution and fidelity. Tomographic Volumetric Additive Manufacturing (TVAM) employs a digital micromirror device (DMD) to project amplitude light patterns into rotating resin volumes, producing 3D geometries through photopolymerization. Typically, the light projection efficiency in such binary amplitude modulator-based systems is below a few percent. Recent advancements introduced phase encoding in TVAM using binary amplitude modulators and the Lee Hologram method, increasing axial control and boosting light efficiency to about 10%. In this work, we present the first 3D printing platform utilizing a phase light modulator (PLM), based on an array of micro-electro-mechanical piston mirrors. Compared to amplitude encoding, phase encoding with the PLM yields a 70-fold increase in laser power efficiency. By coupling this efficient light engine with a speckle reduction method in holographic volumetric additive manufacturing (HoloVAM), we experimentally demonstrate printing 3D objects across different scales from hundreds of micrometers to centimeters and with various materials from acrylate-based resins to soft hydrogels, including cell-laden hydrogels with a concentration of 1 million cells per mL. Micro-CT revealed a as the smallest positive feature printed. Moreover, we introduce the use of gelatin Thiol/Norbornene as a material for printing with the Holographic VAM technique, which allows us to print large-scale objects (up to within 2 minutes using only a 150 mW laser diode. The PLM opens up new avenues in volumetric AM for holographic techniques using low-cost single-mode laser diodes.

Read more at Light: Science & Applications

Rocket, Satellite Stocks Surge as SpaceX IPO Fuels Euphoria /Bloomberg/ Form S-1 Space Exploration Technologies Corp. /SEC/. Index providers waived the profitability requirement and cut the seasoning window from 90 days to 5 /Hedgeye on X/

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

💰🚛 Backed by Prologis and the American Bureau of Shipping, the $200M TMV Logistics fund will tap in to growing interest in supply-chain efficiency and resilience /WSJ/
🤝 Autodesk to acquire MaintainX, advancing unified platform in operations /PR Newswire/ in an all-cash transaction valued at approximately $3.6 billion.

🇩🇪⚡ Focused Energy Raises $240 Million in Series A Financing

Focused Energy, the world’s leading laser fusion company, has raised $240 million in a Series A financing round, making it the largest fully secured Series A financing in the global fusion industry to date. In addition to RWE, the investors include the Federal Agency for Breakthrough Innovation SPRIND, the European Innovation Council Fund, and the previous lead investor, Prime Movers Lab.

The new capital is to be invested into the former RWE power plant site in Biblis, Hesse. Using the site’s infrastructure and RWE’s power plant expertise, Focused Energy aims to accelerate fusion system development and establish Biblis as a blueprint for industrial laser fusion.

Read more at Business Wire

🇺🇸⚡ Thea Energy Raises $100 Million Series B Funding to Build Scalable Fusion Power Plants /GlobeNewswire/
🇬🇧🌊 Caudal Energy lands €4.9 million to develop predictable renewable power from tidal flow /EU Startups/

🇨🇭🚀 Stellar Alpina Raises CHF 3.5M to Build Detonation-Based Propulsion for Mobility After Launch

The Zurich-based startup is developing compact rotating detonation rocket engines (RDRE’s) to make movement between orbits faster, smaller, and more efficient. Just 82 days after incorporation, Stellar Alpina completed Europe’s first known commercial RDRE hotfire campaign, turning a deep-tech concept into tested hardware at exceptional speed. The CHF 3.5 million, approximately USD 4.5 million pre-seed round is led by Founderful, Switzerland’s leading pre-seed venture fund, with participation from LP&E.

🇩🇪🧊 Qurie: €2.2 Million Raised For Electrocaloric Refrigeration Systems

Qurie, a Freiburg-based startup developing next-generation electrocaloric cooling systems, has secured €2.2 million in Seed funding. The round was jointly backed by HTGF | High-Tech Gründerfonds (HTGF), Technology Transfer Fund TT49, and Aepikur GmbH.

The company is developing electrocaloric refrigeration systems that operate without compressors, refrigerants, or pressure build-up. Qurie said its technology is designed to deliver quieter, more efficient, and more sustainable cooling solutions compared to conventional refrigeration systems.

The company’s technology is targeting the HVAC market as the industry faces increasing regulatory, technological, and economic pressures to transition toward cleaner and more energy-efficient systems. Qurie’s approach is based on electrocaloric cooling technology, which aims to eliminate the need for traditional refrigerants and compressor-based architectures.

[Overcapacity] Software Guy with Soft Hands Gets a Laser

David Rogers — Sun, 24 May 2026 16:02:57 GMT

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Software Guy with Soft Hands Gets a Laser

David Rogers — Sun, 24 May 2026 13:00:39 GMT

Shop Talk

Capturing this week’s zeitgeist

Detroit grew into a major industrial powerhouse in the early 20th century primarily because of the explosive rise of the automobile industry, which was enabled by abundant open land for massive factories, access to Great Lakes shipping for raw materials like iron ore and coal, a surging labor force from The Great Migration, and pre-existing mechanical expertise in carriage-making and metalworking that innovators like Henry Ford adapted into revolutionary assembly-line mass production.

Will the rise of AI Factories bring the same prosperity? /Bloomberg/

Quote of the Week

At first they didn’t want to sell it to me. They’re like, “All right, let’s talk about your sheet metal shop. Why are you upgrading to a laser?” And I was like, “Well, I don’t really have a sheet metal shop. I’m just starting one.”
They had sent out a salesman. He’s like, “You are a moron. You’re a software guy with soft hands. You don’t know what you’re doing.”
“But I like you, and I’m going to vouch for you. If this thing all blows up, I don’t give a shit. I’m going to come pick up the machine. It’s 50,000 pounds. You can’t move it. I’ll come get it if you don’t make your payments.”
And I was like, “This sounds like an awesome deal.” So we were able to bootstrap because of debt. And that’s really how we run.
Jim Belosic, Co-founder and CEO of SendCutSend /Turner Novak on X and Spotify/

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Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

The Manufacturing Startup That’s Outcompeting China | Jim Belosic, SendCutSend | Round II

Why SCS raised $110M, finding buildings with enough power and great capital partners, and plenty more!

I finally raised some money. Here’s why I waited so long. /Jim Belosic on X/

AI in machine building 2026: Adoption, barriers, use cases, and leading sub-industries

✍️ Author: Raghav Kadian

AI use in the machinery industry is becoming widespread. 96% of machine builders have started to deploy AI in internal operations, and many have started to bring AI features into machine software and into the machines themselves, according to IoT Analytics. The research, which surveyed 120 decision-makers directly involved in machine building across 22 machinery sub-industries, found that machine builders vary widely in their AI motivations and use cases, and that adoption rates vary widely by subindustry.

Real-time inference for robots at Physical Intelligence

For standard local inference, Pi models are trained in the cloud then downloaded locally to run using on-board GPUs attached to each robotic system. This provides a reliable system with good performance and straightforward debugging, but requires a GPU on each robot. Off-board remote inference provided a more lightweight solution for robots without an onboard GPU.

Because Pi’s robots sit inside a continuous control loop, even small amounts of jitter or head-of-line blocking can degrade behavior, which means the nature of TCP was not necessarily the right architectural choice for the setup. To match Tunnels-like performance gains without introducing the potential for request-response stalls in the control loop, Pi worked with Modal to build a more specialized transport: a QUIC-based portal running over UDP with automatic NAT traversal. This system establishes a persistent, bidirectional channel between the robot runtime and the Modal GPU container. Instead of issuing independent TCP requests, the robot connects once and streams observations while receiving action outputs over the same channel.

On Modal, PI can allocate larger, data-center-class GPUs per deployment and run GPU-intensive experiments immediately. This lets the team experiment with larger models that couldn’t even fit on the on-board GPUs, so engineers can test ambitious architectures first and optimize later, if needed.

Inside the YASA YM360: Axial Flux Motor Engineering Explained

In this teardown, we take a closer look at the YASA YM360 axial flux motor and the engineering decisions driving its impressive performance. We analyze the motor’s compact architecture, rotor and stator design, cooling strategy, material selection, and power density advantages while comparing it to conventional radial flux motors.

Unitree GO-M8018-6 Motor Reverse Engineering /Hackaday/

Contents May Shift

Bitch less, build more

On a recent North Bay weekend hike, a friend and I stopped to take in the Windows-XP-esque scenery and noticed that we had just spent the last three miles complaining…

2 months ago · 58 likes · 5 comments · Kristin Ellis

New Product Introduction

Highlighting new and innovative facilities, processes, products, and services

LeRobot Humanoid: An Open, Low-Cost, 3D-Printed Humanoid for Robot Learning

LeRobot Humanoid is designed for a specific niche: an open humanoid platform that is affordable enough to reproduce, simple enough to modify, and complete enough to support real robot-learning experiments.

If you are looking for the most advanced humanoid robot, this is not it.
If you are looking for a humanoid you can build, understand, repair, instrument, simulate, and use for learning experiments, this is the robot we are trying to make.

This is why the release includes more than a robot model or a controller. It includes hardware files, assembly documentation, simulation assets, runtime tools, identification pipelines, and training environments. The goal is to make the full humanoid learning loop accessible, from mechanical design to real-world control.

Dassault Systèmes became a test case in the repricing of industrial software

Investors are no longer asking only whether a software company is sticky. They want to know where it fits in the AI value chain. Does it generate direct financial gains from AI adoption? Does it control unique data that AI relies on? Or does it operate at the application level, vulnerable to automation, pricing pressures, and valuation compression?

The new test is harder. What does the platform control that AI cannot easily bypass? Where does the real product value reside? Where is engineering authority preserved? Where is lifecycle accountability maintained when decisions are made more rapidly and with increased automation? If industrial software vendors respond with generic AI feature talk, they will continue to be squeezed. “We also have copilots” is not a strong investment case. It is a defensive slogan.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

🇨🇦 Inside ventureLAB’s bid to bring AI to Ontario’s critical industries /BetaKit/
💰🇺🇸 IXSAR Capital Launches Focused Venture Platform Backing the Future of Space Technology, Autonomy, and Robotics /PR Newswire/. IXSAR is particularly focused on companies where engineering depth creates durable advantages and where execution requires navigating complex markets, supply chains, and regulatory environments.
💰🇨🇳 BAI Capital Announces First Close of New US$800 Million Fund, Continues to Back Asia Growth and Globalization Opportunities /PR Newswire/. BAI Capital has been deeply rooted in China’s technology and industrial ecosystem, while continuously expanding its global perspective and cross-regional capabilities.

🇺🇸💿 Plural backs CircuitHub with $28M to use robots that manufacture electronics in days

CircuitHub has announced new funding to accelerate a new era of electronics production. The company’s latest funding injection stands as a $28 million Series A round. The investment was spearheaded by Plural, an operator-led venture capital firm founded by an experienced team of European tech heavyweights, including Taavet Hinrikus, Sten Tamkivi, Ian Hogarth, and Khaled Helioui.

Today they operate what they believe is the world’s most advanced PCBA factory /CircuitHub/. Their Grid system is a factory-scale robot that looks more like a semiconductor fab than a contract manufacturer. As a matter of routine they ship 1-off prototype PCBAs in 2 to 3 days without charging white-glove prices. 2M+ boards shipped, 133M+ parts placed, 20,000 engineers served so far. In time, prototyping electronics should look a lot more like 3D printing, and they plan on keep driving lead times and prices down until it does.

🇦🇹🛣️⚡ REPS gets $23.6M to turn road traffic into clean electricity at scale

REPS was built to recover wasted mechanical energy and convert it into clean electricity at scale, using infrastructure that already exists. REPS has announced a $23.6M equity financing round to scale its Road Energy Production System, a patented “road power plant” that converts vehicle traffic into electrical energy.

REPS stands for Road Energy Production System. Its core product is a patented road power plant that installs directly into existing road infrastructure and harvests energy from trucks and cars driving over it, without disrupting traffic flow or logistics operations. The technology is particularly effective where vehicles naturally slow down or brake, or where slopes create additional force. REPS is initially targeting ports, logistics hubs, cities, industrial sites, and other high-traffic infrastructure operators that want to reduce energy costs while improving sustainability.

🇨🇭🛠️ AVIAN raises $2.6M to scale AI thermal monitoring for the world’s most fire-prone industrial sites

Industrial operators across Europe and North America are facing a problem they can’t inspect their way out of. Fine dust, friction, electrical faults, and aging equipment are pushing fire and downtime risk into territory that insurers will no longer underwrite at viable premiums. Sites that were insurable five years ago are being deemed too risky today. Against that backdrop, AVIAN – the Zurich-based industrial AI company building 24/7 thermal monitoring for the world’s most fire-prone facilities announced it has raised a $2.6M pre-seed round, led by Founderful.

[Overcapacity] Shared Vision, Shared Values, and Complimentary Capabilities

David Rogers — Sun, 17 May 2026 16:01:19 GMT

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Shared Vision, Shared Values, and Complimentary Capabilities

David Rogers — Sun, 17 May 2026 13:03:29 GMT

Shop Talk

Capturing this week’s zeitgeist

In the industrial technology sector, the software-driven urge to "move fast and break things" invariably collides with the rigid realities of heavy manufacturing, where displacing entrenched supply chains requires an uncompromising commitment to long-term validation. For deep-tech innovations entering highly regulated fields like aerospace, maritime, or defense, true market disruption cannot be rushed through aggressive early commercialization; instead, it hinges on spending years gathering empirical performance data, achieving stringent certifications, and systematically de-risking the hardware. Ultimately, building a groundbreaking system is only the first step, as the real triumph lies in having the operational endurance to fully master and validate your science before asking a skeptical market to change its mindset. The story of Caracol embodies this journey /Tech.eu/.

Quote of the Week

To become “the best salmon farming company in the world,” defined by the highest margins and the lowest salmon mortality rate, his son is embracing new technology. “I want us to be pioneers,” he said. “We want to take care of both people and the ocean, if you don't evolve as a company, you die.”
Norwegian Billionaire Bets Fortune on ‘World’s Best Fish Farm’ /Bloomberg/

Assembly Line

This week’s industrial breakthroughs and frontier technologies of the built world.

🗣️ The Untold Story of Koch Inc. : 130K Employees, 60 Countries, $150B Empire

Driving Sustainable Transformation: Endress+Hauser CEO Peter Selders /Spotify/
Capgemini Warns CEOs: Physical AI Can No Longer Be Ignored /Forbes/

🦾🤖🦿 Humanoid Robots Running an 8-hr shift - F.03 livestream

Per CEO Brett Adcock:

We previously showed this task running for 1 hour. Today we’re pushing for 8 hours straight. High odds something breaks
The use case is small package sorting. F.03 must detect the barcode, pick up the package, and reorient it barcode face-down onto the conveyor. The robots have to reason purely from camera pixels
Humans average ~3 seconds per package. F.03 is now around human parity
The robots are fully autonomous running Helix-02, our in-house neural network running entirely onboard F.03 (e.g. AI inference is done on device)
Multiple humanoids are networked together and communicating with each other to maximize conveyor uptime. The system is designed to run 24/7
A robot will work until battery is low (~3-4 hours), then autonomously request another robot to swap in to minimize conveyor downtime
It’s a multi-robot coordination with autonomous failover strategy. If a robot detects an issue - it will self diagnose itself and if there’s an issue it autonomously walks to maintenance and requests a replacement from the fleet - no humans in the loop

Figure AI’s 8-Hour Gamble Becomes a Livestream Marathon: over 33,000 Packages and No “Robot Failures” /Humanoids Daily/
Silicon Valley’s latest binge-watch is a humanoid warehouse worker /Business Insider/

🛢️ Why Big Oil is opening new frontiers

🛢️ Why the oil futures curve is not a crystal ball /FT/
☢️ Making New Nuclear Fuel for an Atomic Renaissance /Bloomberg Originals on YouTube/

🏭⚗️🧠 Physics-informed neural network-based multi-horizon model predictive control of chemical plants with renewable supply

✍️ Authors: Javad Tousi, Daniel Görges

To reduce carbon footprint and production costs, the chemical industry is increasingly integrating renewable energy into plant operations. Since renewable generation depends on variable weather, incorporating power forecasts is essential for effective planning, and production schedules must be continuously updated. Model Predictive Control (MPC) can use such forecasts to optimize control inputs, but extending its prediction horizon to capture long-term variations often becomes computationally intractable. This paper proposes a novel multi-horizon MPC framework based on a Physics-Informed Neural Network (PINN) model that combines short-term control accuracy with long-term predictions while addressing uncertainty and maintaining computational efficiency. An average production goal is included to enhance flexibility and ensure that the final target is met under power constraints. Simulation results on a chemical plant demonstrate the performance of the proposed approach in both computational efficiency and energy costs reduction.

Read more at Journal of Process Control

Humba Ventures

Hand Held Laser Welders

Never say Twitter hasn’t contributed to the rebirth of American manufacturing. One of my favorite anecdotes in the unfolding story of that rebirth is Elon Musk scrolling Twitter, seeing a video of a Chinese hand-held laser welder, ordering it for a few thousand bucks off of Amazon and thereafter transforming how rockets at SpaceX are assembled. More on …

2 months ago · 24 likes · Anna-Sofia Lesiv

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⚡🧠 GridSFM: A new, small foundation model for the electric grid

Microsoft releases a lightweight foundation model that can predict AC optimal power flow in milliseconds, boosting efficiency and unlocking cost savings in grid analysis.

At a glance:

Microsoft introduces GridSFM, a small foundation model that approximates AC optimal power flow in milliseconds, unlocking decisions that can directly impact up to $20B/year in congestion losses and 3.4 TWh of renewable curtailment.
Beyond estimating generator dispatch and costs, GridSFM produces full AC system states, giving operators direct visibility into congestion, stability, and overall system health.
It provides a foundation for the community to build advanced power grid simulators and planning tools without recreating data or models from scratch.

🔋 Introducing Ford Energy

For the better part of a year, we have operated quietly to build a foundation for this business. We haven’t just been planning; we have been executing — securing supply chains, readying our manufacturing sites and aligning our technology with the massive demand for domestic energy storage.

Ford Energy is a wholly owned subsidiary of Ford Motor Company. We will provide United States-assembled battery energy storage systems (BESS) for utilities, data centers and large industrial and commercial customers in the United States.

By leveraging more than a century of manufacturing expertise, Ford Energy plans to deploy at least 20 GWh annually, with first customer deliveries planned for late 2027.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

🇺🇸🦾 Mind Robotics Announces $400M in New Funding to Expand Industrial Robotics Deployment

Mind Robotics announced a $400 million financing led by Kleiner Perkins, bringing total investment in Mind Robotics to more than $1 billion. This financing included participation from new investors including Meritech Capital, Redpoint Ventures, SV Angel, Incharge Capital, A-Star Capital, and Garuda Ventures as well as existing investors including Accel, Andreessen Horowitz, Eclipse, Prysm Capital, Bain Capital Ventures, and Greenoaks. This follows a seed financing of $115M in late 2025 and a Series A of $500M in March 2026.

Mind Robotics is building the world’s leading industrial robotics platform, combining foundation models, robust hardware, and deployment infrastructure to automate dexterous, reasoning-intensive manufacturing tasks at scale. The company operates with Rivian as a key partner and shareholder, providing a live, high-volume manufacturing environment for model training and deployment.

Read more at Business Wire and The Robot Report

🇨🇳🦿 Unitree Robotics founder/CEO Wang Xingxing details the first bipedal robot he developed for around ¥200 ($30) /Mike Kalil on X/
🇨🇳🦾 China’s Caifu Robot More Than Doubles World Record for Industrial Robot Payload /YiCai/

🇺🇸 🛰️🔌 Star Catcher Raises $65 Million to Build the First Power Grid in Space

Star Catcher Industries, Inc., the company building the first power grid in space, announced it has raised $65 million in an oversubscribed Series A round. The new investment — led by B Capital and co-led by Shield Capital and Cerberus Ventures, the venture arm of Cerberus Capital Management — brings Star Catcher’s total capital raised to $88 million.

Founded less than two years ago, Star Catcher is developing a space-based energy infrastructure layer that delivers electricity on demand to satellites and other spacecraft using optical power beaming. Following an industry-leading seed round and exceptional customer traction, the company set the world record for optical power beaming, completed a critical on-orbit subsystem demonstration, and validated its end-to-end system architecture. The Series A positions Star Catcher to move from validated technology to scalable infrastructure.

🇫🇷 Mantle8 raises €31 million to fund the world’s most advanced natural hydrogen exploration and drilling campaign

Mantle8, a Grenoble, France-based natural hydrogen exploration company, has raised €31 million in Series A funding. This round brings the company’s total funding to €37 million (US$44 million). The round was led by Sandwater and includes Breakthrough Energy Ventures, Ecotechnologies 2 fund managed on behalf of the French government by Bpifrance, IP Group, Wind Capital and Calderion (an Audacia-backed investment platform).

Mantle8 claims that its technology for identifying commercially viable natural hydrogen reserves reduces exploration risk and cost, with economic models projecting production costs as low as €0.80/kg. This significantly contributes to a much lower average cost of clean hydrogen supply.

[Overcapacity] Decentralized Autonomous Factory Networks

David Rogers — Sun, 10 May 2026 16:01:24 GMT

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This weeks digest:

Decentralized Autonomous Factory Networks

David Rogers — Sun, 10 May 2026 13:02:24 GMT

Shop Talk

Capturing this week’s zeitgeist

The industrial giants of the future are deploying industrial technology across decentralized, autonomous networks that prioritize resilience and agility over the outdated pursuit of sheer scale /c&en/. By integrating AI-driven analytics, modular manufacturing, and self-optimizing systems, these leaders will move away from concentrated megastructures toward flexible, regionalized facilities /New Electronics/, akin to the "minimills" that upended the steel industry, capable of pivoting in real-time to counter geopolitical shocks or supply shortages. This transition, fueled by a shift toward geographically dispersed renewable feedstocks like biomass and captured CO2, redefines competitiveness through ecosystem-based collaboration rather than simple cost-cutting. Ultimately, the next generation of titans will be those who treat autonomy as a strategic enabler to augment human decision-making, proving that in a volatile global market, being fast and adaptable beats being large and rigid every time.

🇺🇸 Magrathea raises $24M to build demo magnesium smelter /Axios/
🇺🇸 Trillium Raises $13M to Launch World’s First Demonstration Plant for Bio-based Acrylonitrile /GlobeNewswire/

Quote of the Week

The most damaging misconception in industrial AI today is a false binary: Either AI can solve everything now, or it isn’t ready for serious industrial use. Both claims miss the point. /EETimes/

HM26: Whitelabeled AI and the hope for the API /Industrial AI Podcast/

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Assembly Line

This week’s Industry 5.0 breakthroughs and frontier technologies of the built world.

🦾🤖🦿 Humanoid Robots Are the Next Phase of the AI Hype Cycle

The humanoid industry remains stymied by the Three B’s: balance, battery, and brains alongside the immense difficulty of replicating human-like fine motor skills. Investors are betting billions on a Robots-as-a-Service (RaaS) model to address labor shortages and demographic shifts, aiming to turn human-shaped machines into a universal, adaptable platform for industrial and service work.

🚙 Tesla Vision can Deploy Airbags up to 70ms Earlier

🔋 CATL Unveils Six Major Innovations: Multi-Chemistry Systems to Redefine New Energy Mobility Experience /CATL/. The Engineering Behind CATL’s 30-Second EV Charging Battery Breakthrough /Geeky Gadgets/
🚗 Inside Cadillac’s IQ Door Manufacturing Process /Munro Live/
🛻 Inside Ford’s efforts to build an affordable electric truck /Manufacturing Dive/
🛻 EV Startup Slate Hires Ford, Lucid Veteran Ahead of Production Start /EV/
🧠📐🚙 What an AI-designed car looks like /The Verge/

🧠📐 How Dassault Systèmes Is Building AI That Understands Physics

🗣️ AI Takeover: Qualcomm’s Big Bet on AI Agents, Robots and 6G /YouTube/
🗣️ How AI Agents Are Transforming Workflows on the Factory Floor with Apprentice CEO Angelo Stracquatanio /Manufacturing Happy Hour/
Agentic AI in Manufacturing: How Bosch Makes the Shop Floor Smarter /Bosch Global/
🗣️ Large Engineering Models: Reimagining Design, Simulation, and Manufacturing | EMMI AI | CDFAM BCN 26 /YouTube/

🧠📐 Zero-to-CAD: Agentic Synthesis of Interpretable CAD Programs at Million-Scale Without Real Data

Computer-Aided Design (CAD) models are defined by their construction history: a parametric recipe that encodes design intent. However, existing large-scale 3D datasets predominantly consist of boundary representations (B-Reps) or meshes, stripping away this critical procedural information. To address this scarcity, we introduce Zero-to-CAD, a scalable framework for synthesizing executable CAD construction sequences. We frame synthesis as an agentic search problem: by embedding a large language model (LLM) within a feedback-driven CAD environment, our system iteratively generates, executes, and validates code using tools and documentation lookup to promote geometric validity and operation diversity. This agentic approach enables the synthesis of approximately one million executable, readable, editable CAD sequences, covering a rich vocabulary of operations beyond sketch-and-extrude workflows. We also release a curated subset of 100,000 high-quality models selected for geometric diversity. To demonstrate the dataset’s utility, we fine-tune a vision-language model on our synthetic data to reconstruct editable CAD programs from multi-view images, outperforming strong baselines, including GPT-5.2, and effectively bootstrapping sequence generation capabilities without real construction-history training data. Zero-to-CAD bridges the gap between geometric scale and parametric interpretability, offering a vital resource for the next generation of CAD AI.

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Highlighting new and innovative facilities, processes, products, and services

🧠 Introducing SubQ: The First Fully Subquadratic LLM

Transformers defined the last decade of AI — the “T” in ChatGPT. They unlocked modern language understanding, reasoning, and much of what we now think of as AI. Yet one fundamental limitation has shaped everything built on top of them: compute requirements scale quadratically with context length.

Subquadratic is an AI company building a new class of large language models. Our first model, SubQ 1M-Preview, is the first LLM built on a fully subquadratic architecture, one where compute grows linearly with context length. With a research result at 12 million tokens, SubQ’s architecture reduces attention compute by almost 1,000x compared to other frontier models.

Starting today, SubQ will be available for early access via:

API — The full-context API for developers and enterprise teams.
SubQ Code — A coding agent built on SubQ, available via command line interface (CLI). SubQ Code loads entire codebases into a single context window, enabling developers to plan, execute, and review across a full repository in a single pass — without the coordination overhead of multi-agent systems.
SubQ Search — A long-context search tool providing Deep Research capabilities with chatbot speed.

📥 Neurocad early access program is now open

Who we’re looking for: engineers who rebuild schematic symbols from datasheets, create PCB footprints from package drawings, generate mechanical models for placement, or work in Altium, SolidWorks, or similar tools. Our goal is to validate that the structured component model accurately reflects real-world manufacturing tolerances before scaling the platform.

This is not a beta launch. It’s a focused evaluation with a small group of engineers working on a specific problem. We review each application manually.

Apply at Neurocad

🤝 Nominal Acquires Fid Labs to Bring Domain-Expert AI to Hardware Engineering /Nominal/
📥📐 SimScale Opens Waitlist for Engineering AI Simulation Agents /Simscale/. Apply at Engineering AI Waitlist.
🇩🇰 Atech raises €681k with Lovable backing to make hardware prototyping more accessible /EU-Startups/. Atech introduces ‘vibe-engineering’ for hardware.

BYD in talks to take over part of Volkswagen’s Dresden plant /CNC/. VW Open to Chinese Partners Sharing Underused EU Plants /Bloomberg/.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

💰 EQT secures €3.1bn for European logistics fund /Private Equity Wire/
💰 Atlantic Packaging Launches New Earth Ventures to Accelerate Packaging Technology and Supply Chain Innovation /PR Newswire/

🇬🇧🔋 Nyobolt Closes Series C Round at $1B Valuation, to Power the Rise of Autonomous Machines, Physical AI Applications and AI Data Centres

Nyobolt, a pioneer in ultra-fast, high-power, energy technology, announced it has raised $60 million in funding to accelerate its development pipeline and bring its power performance solutions to the autonomous machines that need them most. The round was led by Symbotic (NASDAQ: SYM), a leader in AI-enabled robotics technology for the supply chain, with participation from IQ Capital, Latitude (Phoenix Court), Scania Invest and CBMM. The raise follows a period of rapid commercial momentum, with Nyobolt revenues growing five times year-on-year, reflecting accelerating demand surge across physical AI applications and AI data center infrastructure.

Nyobolt’s commercial traction spans some of the most advanced autonomous robotics deployments in the world. For Symbotic’s SymBot™ autonomous mobile robots, Nyobolt’s performance battery delivers six times more energy capacity than the ultracapacitors previously used, is 40% lighter, and achieves at least ten times the cycle life of traditional Lithium-Ion technology, enabling continuous, high-intensity 24/7 operations across Symbotic’s warehouse deployments.

🇳🇱⚛️ QuantWare Raises $178 Million to Build World’s Most Powerful Quantum Processors at an Industrial Scale

QuantWare, the leading industrial quantum processor company, announced a $178 million (€152 million) Series B equity funding round following the announcement of VIO-40K™, a quantum processor architecture for 10,000 qubits, 100x larger than the state of the art today. The company is building KiloFab, the world’s largest dedicated quantum open architecture fab, increasing the company’s production capacity by 20x to meet strong global customer demand.

QuantWare is the only company that designs, fabricates, and integrates modular quantum processors on an open architecture at an industrial scale. Its proprietary VIO™ technology — a modular Quantum Processor Architecture — allows the creation of the world’s most powerful quantum processors that provide the most compute per Watt.

Read more at Business Wire

🇬🇧⚛️ Quantum Motion Raises $160 Million Series C to Deliver Quantum Computing’s “Transistor Moment” /Business Wire/. Quantum Motion’s silicon transistor-based approach enables delivering utility-scale systems with 100-fold reduction in cost and space requirements, and 1,000-fold reduction in energy consumption compared to alternatives. Its systems are designed for deployment into standard data-centre racks, avoiding the need for bespoke facilities and the heavy energy overhead associated with alternative architectures.
🇳🇱⚛️ Delft-based FrostByte secures a cool €1.3 million to scale cryogenic electronics for quantum computing /EU-Startups/
⚛️📐 Why Quantum Hardware Will Be Designed in Simulation First /Dassault/

Where we’ve seen this before: Microsoft’s Majorana 1 /Microsoft/

🇺🇸⚡ Panthalassa Raises $140 Million to Power AI at Sea

Panthalassa, a renewable energy and ocean technology company, announced $140 million in Series B financing led by Peter Thiel, with participation from new investors John Doerr, Marc Benioff’s TIME Ventures, Max Levchin’s SciFi Ventures, Susquehanna Sustainable Investments, Hanwha Asset Management (USA)’s venture fund, Anthony Pratt, Fortescue Ventures, Future Positive, WTI, Nimble Partners, Super Micro Computer, Sozo Ventures, Dylan Field, Planetary VC, Leblon Capital, Resilience Reserve, Portland Seed Fund, and the Intrepid Oregon Fund. They are joined by returning investors Founders Fund, Gigascale Capital, Lowercarbon Capital, Unless, and WovenEarth.

The funding will complete the company’s pilot manufacturing facility near Portland, Oregon, and accelerate deployment of its Ocean-3 series of nodes, which will perform AI inference computing at sea using power generated from ocean waves.

Read more at Business Wire

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Constraint Capital #5 - May 2026

David Rogers — Mon, 04 May 2026 13:03:14 GMT

According to Goldman Sachs, the required ~$7.6 TRILLION of capital between 2026 and 2031 across compute, data centers, and power of the global AI build-out hinges on four supply-side assumptions /Goldman Sachs/. First, the economic useful life of silicon dictates the frequency and cost of massive replacement cycles /WSJ/. Then comes data center complexity. To support specialized hardware, operators must pay top dollar for advanced liquid cooling and dense power infrastructure /DCD/. Furthermore, compute elasticity determines whether chip efficiencies actually reduce hardware needs or simply trigger more demand /CIO/. Finally, severe physical bottlenecks in the power grid and labor market can dangerously elongate construction timelines /National Academies/. Just a few delays can stall monetization entirely.

Companies offering solutions to these physical bottlenecks and infrastructure constraints are moving swiftly to capitalize on the AI boom. By unlocking these critical supply-side challenges, they are aggressively tapping the capital markets to secure the massive funding needed for the next phase of growth. Those that are well positioned for scale may be investable, others may be just cashing in. Within the last month the following firms related to these bottlenecks have announced:

AI Factories

Cerebras Systems (AI inference chips/supercomputers for data centers): Filed S-1 for IPO on April 17, 2026 (Nasdaq: CBRS planned). Expected raise ~$2 billion at a valuation over $35 billion. Directly supports AI workloads in data centers as a Nvidia alternative. /Cerebras and SEC/
Forge Nano (advanced materials/Atomic Layer Deposition tech for AI-era semiconductor chips and batteries): Announced definitive SPAC merger on April 21, 2026, with Archimedes Tech SPAC Partners II (to trade as Nasdaq: NANO). ~$1.6 billion total equity value (pre-money ~$1.2 billion + PIPE). Enhances chip manufacturing and energy storage relevant to data centers. /GlobeNewswire/
Sivers Semiconductors AB evaluates a potential dual listing of its shares on the Nasdaq New York /Sivers/. Sivers develops photonics and wireless components (lasers, optical transceivers, etc.) used in high-speed data transmission for AI datacenters, HPC, and telecom infrastructure.

Energy Systems

Fervo Energy (next-generation geothermal energy developer): Filed S-1 for IPO on April 17, 2026 (Nasdaq: FRVO planned). Estimated raise ~$250 million. Unicorn status (valuation crossed $1 billion pre-IPO via prior funding); focuses on clean, reliable power for high-demand AI data centers. /Fervo Energy/
X-energy (advanced nuclear small modular reactors): IPO priced April 23 and began trading April 24, 2026 (Nasdaq: XE). Raised ~$1.02 billion (upsized) at ~$9.1 billion market cap initially (now higher, around $11–12+ billion post-debut). Targets clean baseload power for AI data center energy needs (e.g., backed by Amazon). /X-energy/

Mineral Frontier

The Elmet Group Co. (precision-engineered critical materials/components like tungsten/molybdenum, plus high-energy/microwave systems for semiconductors, energy, aerospace/defense): IPO priced April 22 and began trading April 23, 2026 (Nasdaq: ELMT). Raised ~$125.5 million (upsized) at ~$411–438 million market cap. U.S.-based producer of critical materials used in semiconductor/electronics and energy applications. /VoxelMatters/
Copper and Silver Miner Lumina’s Toronto IPO Raises $297 Million /Bloomberg/. The pricing gives Lumina Metals a market value of as much as roughly C$1.3 billion based on the outstanding shares listed in its filing. Accounting for employee stock options and restricted stock units, the company would have a fully diluted value of up to about C$1.4 billion.

Which brings us to the “The Great Data Center Delay” which we will break down in the rest of this article…

[Overcapacity] Direct Numerical Control World Models

David Rogers — Sun, 03 May 2026 16:02:43 GMT

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This weeks digest:

Direct Numerical Control World Models

David Rogers — Sun, 03 May 2026 13:02:23 GMT

Shop Talk

Capturing this week’s zeitgeist

Following the rush of Hannover Messe /Interact Analysis/, I visited Munich for a different kind of immersion. Here, science and high-tech is part of the civic fabric. On a walk from the central station to the city's East Side, I crossed paths with the bronze monument of Joseph von Fraunhofer (celebrating 200 years on June 7), a silent prelude to the massive, historic halls of the Deutsches Museum. Wandering through those sprawling galleries, I was completely surrounded by centuries of every engineering discipline.

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Assembly Line

This week’s Industry 5.0 breakthroughs and frontier technologies of the built world.

🗣️🦾🤖🦿 The $10 Trillion Bet on Humanoid Robots with Figure Founder Brett Adcock

Brett shares why humanoid robots are already working today, how Figure plans to scale from thousands of units this year to 1 million per year, and why he believes this could become the biggest business in the world. Backed by nearly $2B across rounds — including investment from Jeff Bezos, Microsoft, Nvidia, and Amazon — Figure 15x’d its valuation to $39B in just 18 months. Also covered is Brett’s decision to part ways with OpenAI, the challenges of building physical intelligence, and what it takes to solve one of the hardest problems in engineering.

🗣️ Zane Hengsperger on Building Nox Metals and the Future of Manufacturing /YouTube/

🚘 Rotary Engine Shows Why Internal Combustion Still Matters

Despite the global trend toward electrification, internal combustion remains vital for consumers, defense, and aviation, sparking a renewed interest in reviving and reinventing technologies like the rotary engine. Innovators like LiquidPiston and Mazda are redesigning the century-old Wankel rotary engine to create smaller, more efficient power sources for everything from military drones to plug-in hybrid sports cars.

Ultimately, as the growth of electric vehicle sales slows, gas engines are serving as generators in extended-range electric vehicles (EREVs) to act as a practical bridge technology toward full electrification.

✈️⛓️ Boeing and the Supply Chain Cost of Industrial Complexity

✍️ Author: Jim Frazer

Boeing’s recent problems are often described as quality failures. That is accurate, but incomplete. The deeper issue is industrial complexity. Boeing operates one of the most demanding supply chains in the world: highly engineered products, long-cycle programs, strict certification requirements, specialized suppliers, and little room for error. In that environment, quality is not a department. It is an outcome of supply chain design.

Boeing is an extreme case, but the pattern applies broadly. As supply chains become more specialized and distributed, companies need stronger control mechanisms: more disciplined supplier quality systems, better sub-tier mapping, real-time production status visibility, earlier detection of process drift, clearer ownership of engineering and manufacturing interfaces, and stronger governance over outsourced critical work.

🎛️☁️ Cloud-Direct NC: A new generation of numerical control technology

✍️ Authors: Shivam Garg, Liang Tung Chen, Aryan Shroff, Ricardo Toro, Shiv G. Kapoor, Jorge E. Correa, and Placid M. Ferreira

Artificial Intelligence, Industrial Internet of Things (IIoT), and Cloud Manufacturing technologies, along with rapidly evolving computing infrastructure, require that the fifty-year-old CNC architecture be reexamined to better address the changing needs of manufacturing automation as it evolves from programmed to perceptual automation. This paper introduces Cloud-Direct Numerical Control (C-DNC), an architecture that recruits the services of different computing (cloud, edge, and embedded/real-time) resources, matched to different tasks in the NC workflow.

Comparing the generation and execution of motion commands in (a) conventional CNC systems and (b) the Cloud-DNC system. The C-DNC workflow offloads real-time computation by pre-compiling G-code into a bytecode file.

It introduces the concept of a ‘compiled motion program’ to reduce the workload on real-time computing resources by eliminating the repetitive tasks of interpreting G-codes and performing real-time trajectory interpolation. A portion of the freed-up real-time resource bandwidth is used to demonstrate NC-embedded monitoring and IIoT services that not only provide high-bandwidth data collection but also ensure tight temporal alignment of this data with machine instructions. The remaining bandwidth can be used for real-time inferencing and advanced controls to realize truly intelligent NC systems. Finally, this cloud-integrated version of Direct Numerical Control reduces investment costs through the efficient shared use of computing resources, enables new modes for the democratization of NC via subscription and pay-per-use models, and integrates with upstream design and planning software tools.

Read more at Journal of Manufacturing Systems

True Bearing

AI Leaves the Desk

4 months ago · 3 likes · Charlie Warren

New Product Introduction

Highlighting new and innovative facilities, processes, products, and services

🇩🇪🚜 World First: Inside Liebherr’s New 100-Tonne Mining Excavator

From remote jungle mines to extreme tropical conditions, Indonesia is one of the toughest proving grounds in the world. With intense rainfall, challenging material, and nonstop operations, it’s the perfect place for Liebherr to push new machines to their limits; collecting real-world data and refining performance before launching them globally.

📐🧠 Bringing Autodesk Fusion onto Claude for Creative Work

AI makes it easier than ever to turn ideas into something real. But in design and engineering, moving from intent to an editable, manufacturable design still takes time and manual work.

With Fusion, that looks like two things:

Autodesk Assistant brings AI directly into Fusion, helping users understand context and take action in their workflows
Fusion Model Context Protocols (MCPs) lets third-party AI systems connect to Fusion, enabling them to access design context and perform actions securely.

🇩🇪☀️⚡ Colored films enable patterns on PV modules

Scientists at the Fraunhofer Institute for Solar Energy Systems ISE have succeeded in creating colored films with transparent cutouts, thereby producing realistic-looking designs on photovoltaic modules. In this way, roof tiles, for example, can be imitated. The film cutout patterns utilize MorphoColor® technology, an invention of Fraunhofer ISE that creates a color impression without significantly impairing the efficiency of a PV module.

The foil cutting patterns can be used, for example, to imitate roof tiles without significantly impairing the efficiency of the PV module.

The technology can be applied to all standard photovoltaic and solar thermal modules; the desired pattern is cut into the films with MorphoColor® coating using laser or CAD-controlled processes.

Business Transactions

This week’s top funding events, acquisitions, and partnerships across industrial value chains.

💰 Eclipse raises $1.3B to reshore manufacturing, strengthen supply chains /Manufacturing Dive/. The main Eclipse fund is dedicated to startups that go through the venture firm’s incubation program called Venture Equity. It is also focused on spinning out smaller firms from larger companies, such as Mind Robotics from Rivian, and traditional seed and series A funding, Reichow said.
🇩🇪💰 BMW i Ventures Announces $300 Million Fund to Back AI Startups Reshaping the Automotive Ecosystem /BMW/. Fund III will invest in physical AI, agentic AI, and software automating complex workflows across manufacturing, supply chains, and the broader automotive ecosystem
💰 KOMPAS VC closes €160M Fund II /Tech.eu/ aiming to support early-stage companies developing technologies that improve productivity, resilience, and decarbonisation across industrial sectors.

🇩🇪🦾🧠 Sereact Raises $110M Series B

Sereact has raised a $110 million Series B round led by Headline, with participation from Bullhound Capital, Daphni, and Felix Capital. Existing investors Air Street Capital, Creandum (lead of Sereact’s 2025 Series A), and Point Nine all returned for this round. The round funds two priorities: scaling Cortex 2.0, the next generation of Sereact’s robotic brain, and entering the United States. Sereact opens its first US office in Boston and hires commercial, application, and engineering staff locally.

Cortex 2.0 augments a vision-language-action (VLA) model with a world model. From the current state, it generates a set of candidate future trajectories, runs them against a learned model of physics and object behavior, and scores each one for stability, risk, and efficiency. The robot commits only to the best-scored branch - and updates the rollout in real time as the scene changes. World models are the next frontier in AI, and most of that work is happening in research labs on synthetic data. Cortex 2.0 is the one trained on more than a billion picks of real production.

🏴󠁧󠁢󠁳󠁣󠁴󠁿💿 Cnuic secures $3M pre-seed to unlock next-generation photonic chip production

Cnuic has raised $3 million in pre-seed funding led by Tensor Ventures, together with the Silicon Valley-based Blank Space Ventures. The round also saw participation from Silicon Roundabout Ventures, Phasechange, SANDS, and Superlative.

The company based in Edinburgh has developed a working prototype of a completely new type of photolithography device, which makes use of the properties of light, enabling rapid, reconfigurable production of photonic chips with enhanced 3D control, something that was previously impossible. In practice, Cnuic asserts this could be the biggest innovation in this field since the invention of the transistor.