Exponential Industry

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.

We are gifting a 1-year paid subscription to the first person to identify the content link AND cultural reference to the title/subject line of this week’s digest. Comment on this post with your guess before next week’s digest is released to be eligible!

2 months ago · 3 likes · Charlie Warren

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

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.

[Overcapacity] Factories Can No Longer Outrun AI

David Rogers — Sun, 26 Apr 2026 16:02:31 GMT

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Bonus Media

This weeks digest:

Factories Can No Longer Outrun AI

David Rogers — Sun, 26 Apr 2026 13:03:36 GMT

Shop Talk

Capturing this week’s zeitgeist

Robots have moved beyond the laboratory to dominate physical spaces, now consistently outperforming humans across industrial, athletic, and high-skill environments. Through the integration of physical AI, these machines are now essential enterprise assets that identify safety risks and inefficiencies with a level of precision that exceeds human capability /Assembly/. From shattering marathon world records /BBC/ to defeating elite table tennis players /Reuters and nature/, the rapid advancement of robotics have achieved their AlphaGo moment.

Quotes of the Week

That is a very different picture from 2025. Last year, every robot in the field was remote-controlled, and the fastest finish took 2 hours, 40 minutes and 42 seconds. This time, autonomy was one of the main things the race was there to test. /TechRepublic/

We’re in the GPT-2.5 moment for robotics. Capabilities are real, but the gap between lab performance and field deployment remains wide. /Bessemer/

🎁 Gift subscription answer: The Railroad was its Own Biggest Customer

Industrial trade show season in full swing; This week we cover Hannover Messe, Rapid + TCT, Google Cloud Next, and MMA Ops. Looking for Data Centre World London and MODEX? Let us know in the comments.

Honor's Autonomous Humanoid Robot "Lightning" Wins Beijing Half Marathon. Shattering the Human World Record.

Assembly Line

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

🎪🇩🇪 Hannover Messe 2026 Show Report

It was a privilege to connect with nearly 100 of you across 4,000 exhibitors at Hannover Messe 2026 /YouTube/, spanning the diverse fields of industrial AI, product design, and automation. The energy on the floor was electric, signaling a definitive turning point in how our industry perceives the relationship between hardware and software. This year truly felt like the moment the physical and digital realms finally converged into a single, seamless ecosystem unified by the transformative power of AI.

Major Announcements

NVIDIA and Partners Showcase the Future of AI-Driven Manufacturing at Hannover Messe 2026 /NVIDIA/
Siemens brings AI to the physical world with Eigen Engineering Agent /Siemens/

PTC Showcases Bobcat’s Use of the Intelligent Product Lifecycle at Hannover Messe 2026 /PR Newswire/
Rockwell Automation to Demonstrate AI‑Orchestrated Factory System Design at Hannover Messe 2026 /PR Newswire/
Bosch focuses on the interplay between humans and AI /Bosch/
Lenovo Brings Production-Scale AI to Hannover Messe 2026, Delivering Up to 85% Faster Lead Times for Manufacturers /Lenovo/

Litmus Edge Bridge for Databricks /Litmus/ and Litmus Data Catalog (Private Preview) /Litmus/
Sight Machine Advances Autonomous Agents for Manufacturing with AI Agent Crews /Sight Machine/

🎪🖨️ Rapid + TCT 2026

RAPID + TCT 2026, North America’s largest additive manufacturing event, took place April 13-16 in Boston, MA, showcasing over 450 exhibitors and highlighting the industry’s shift from prototyping to industrial production.

New Creality IPO Prospectus Shows Record Revenue Alongside Competitive Pressure /3DPI/
Did Industry Misjudge AM’s Value? Findings from AMGTA Explain The Bias /3DPI/
Sinterit’s 3D Printing Academy Makes Serious Manufacturing Education Free and Accessible /Sinterit/
MAM-PhyGNN: A Physics-Hardcoded Graph Neural Network for fast and accurate thermal simulation in metal additive manufacturing /Additive Manufacturing/

💿 Google Cloud Next: Inside the eighth-generation TPU

Recognizing that the infrastructure requirements for pre-training, post-training, and real-time serving have diverged, our eighth-generation TPUs introduce two distinct systems: TPU 8t and TPU 8i. These new systems are key components of Google Cloud’s AI Hypercomputer, an integrated supercomputing architecture that combines hardware, software, and networking to power the full AI lifecycle.

While both systems share the core DNA of Google’s AI stack and support the full AI lifecycle, each is built to address distinct bottlenecks and optimize efficiency for critical stages of development. Additionally, by integrating Arm-based Axion CPU headers across our eighth-generation TPU system, we’ve removed the host bottleneck caused by data preparation latency. Axion provides the compute headroom to handle complex data preprocessing and orchestration, so that TPUs stay fed and don’t stall.

🏭🏴󠁵󠁳󠁭󠁩󠁿 MMA Operations Conference 2026

The annual MMA Operations Conference provides actionable solutions to operational challenges for Michigan manufacturers, offering proven strategies, tools and best practices in the areas of organizational culture, human resources, marketing and community relations, cybersecurity and technology, production and operational efficiencies, purchasing, finance and environmental health and safety.

🏆 SkillReal took home 1st in Judge’s Choice and People’s Choice Awards!

Read More at Michigan Manufacturers Association

Opinion: Michigan can win in AI. But only if we stop trying to replay the last game. /Crain’s Detroit/
Robotics Growth Drives FANUC’s Major Michigan Investment /Control.com/

The CRC Substack

A smartphone company's humanoid robot, developed in under one year, won the world's first branded humanoid robot half marathon on April 19, 2026, finishing in 50 minutes and 26 seconds, faster than the human world record of 57:20…

16 days ago · 9 likes · ChinaResearchCollective

New Product Introduction

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

📐🧠 Can AI Design IoT Hardware?

In this episode of the IoT For All Podcast, Matthias Wagner, Founder and CEO of Flux, joins Ryan Chacon to discuss AI-assisted hardware design for IoT. The conversation covers the historical challenges of hardware design, the current capabilities of AI tools, compressing the hardware iteration cycle, integration challenges, the limitations of AI, and enabling IoT innovation.

America’s Largest Landowner Is Using AI to Digitize the Forest /WSJ/. Weyerhaeuser is pursuing autonomous logging equipment and hopes to double its profits by 2030 independent of any increase in lumber prices.

Business Transactions

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

🇺🇸☢️💰 Blue Energy Raises $380M to Build World’s First Project-Financeable Nuclear Plant

Blue Energy, a developer of financeable, prefabricated nuclear power plants, announced that it has raised $380 million in financing to advance its turnkey approach to nuclear plant development. The fundraise was led by VXI Capital with significant backing from Engine Ventures and participation from other existing investors, including At One Ventures and Tamarack Global. Proceeds will support procurement of long-lead equipment, project development activities, and general corporate purposes.

Blue Energy is developing prefabricated nuclear power plants designed to be compatible with leading reactor technologies and delivered on an accelerated timeline in as little as 48 months. The complexity of bespoke nuclear plant construction has historically contributed to delays, cost overruns, and financing uncertainty. This uncertainty and risk have sidelined private capital and created an overreliance on taxpayer dollars and consumer rate hikes. Blue Energy believes it can address those challenges through an innovative development model centered on reducing construction risk through centralized advanced manufacturing, skilled labor and more predictable schedules.

Read more at PR Newswire

🇺🇸 C-Infinity Raises $16M to Eliminate the Manufacturing Bottleneck Between Design and Production

C-Infinity, the AI platform that automates how digital designs are translated into production-ready plans, announced it has raised $16 million in funding led by Canaan Partners, with participation from Inventus Capital, Bee Partners, and Radius Capital. As global manufacturers race to increase speed, resilience, and output, C-Infinity is introducing a new layer of industrial intelligence embedded directly within engineering workflows. C-Infinity’s AutoAssembler addresses this challenge. By operating inside existing engineering workflows, the platform automates process planning, accelerates engineering change order reviews, and generates production-ready assembly instructions.

Read more at Business Wire

How Rivian and VW’s Joint Venture Uses AI to Ship the Future of Vehicle Software /Cognition/
Bombardier signs multimillion-dollar contract with CoLab to design jets using AI software /The Globe and Mail/

🇩🇪 Project A backs Linexa with €2M to make production lines AI-ready

Linexa secured a €2 million pre-seed round led by Project A, with angel investments from Thomas Böck, Bastian Nominacher, and Christian Schlögel. Linexa addresses machine-level control code, specifically PLC logic that operates production lines.

Linexa translates this code into a unified data model compatible across vendors and legacy systems. AI agents then monitor and optimise production autonomously. For example, a cosmetics manufacturer switching a filling line from liquid soap to hand cream uses Linexa to analyse the control logic, identify risks before downtime occurs, and significantly reduce changeover time. The platform provides manufacturers with a comprehensive and accessible view of their operations.

[Overcapacity] The Railroad was its Own Biggest Customer

David Rogers — Sun, 19 Apr 2026 16:01:28 GMT

Thank you for being a paid subscriber! This week’s bonus board is available until 2026-05-17.

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This weeks digest:

The Railroad was its Own Biggest Customer

David Rogers — Sun, 19 Apr 2026 13:01:29 GMT

Shop Talk

Capturing this week’s zeitgeist

The buildout of the American railroad system in the 19th century was more than just a transportation project; it was the creation of the world’s first truly modern industrial operating system. By solving the massive logistical challenges of a continent-sized nation, railroads established the management, financial, and technical frameworks that defined the 20th-century global economy. Today, AI factories are poised to execute a parallel transformation by industrializing the production of intelligence for the 21st-century economy.

Quote of the Week

It’s one of the things that we can do that is hard for someone else to do. We’ve made enormous commitments upstream. Some of it is explicit, these commitments that you mentioned. Some of it is implicit. For example, a lot of the investments that are upstream are made by our supply chain because I said to the CEOs, “Let me tell you how big this industry is going to be, let me explain to you why, let me reason through it with you, and let me show you what I see.”
As a result of that process of informing, inspiring, and aligning with CEOs of all different industries upstream, they’re willing to make the investments. Why are they willing to make the investments for me and not someone else? The reason for that is because they know that I have the capacity to buy their supply and sell it through my downstream. The fact is that Nvidia’s downstream supply chain and our downstream demand is so large, they’re willing to make the investment upstream.

Jensen Huang, Founder and CEO, NVIDIA /Dwarkesh Podcast/

New in 2026: We are gifting a 1-year paid subscription to the first person to identify the content link AND cultural reference to the title/subject line of this week’s digest. Comment on this post with your guess before next week’s digest is released to be eligible!

Last week’s answer: Ella Langley artist of Choosin’ Texas /YouTube/ released her sophomore album, Dandelion, on April 10, 2026 while manufacturers are weighing AI’s energy demands /Manufacturing Dive/

Assembly Line

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

🌱🧠 Inside Syngenta’s AI Driven Approach To Modern Agriculture

Syngenta is embedding AI and data analytics across four strategic pillars: research, supply chain, enterprise operations, and farmer-facing tools, to transform traditional agricultural inputs into a digitally-driven ecosystem. By leveraging interdisciplinary teams in computational agronomy and treating modern farm machinery as “data centers on wheels,” the company democratizes expert knowledge through real-time AI diagnostics and predictive disease modeling across 150 million acres. This digital transformation creates significant business value by optimizing resource allocation and increasing crop yields on existing land, positioning the firm to address global food security while paving the way for autonomous agricultural robotics.

Read more from Syngenta’s CIDO, Feroz Sheikh, at Forbes

🚛🧠 Autonomous Trucking Is Fragmenting Into Distinct Market Entry Models /Logistics Viewpoints/
🏭💿🧠 “Intel is substantially improving on its current “Intel Foundry Portal” by providing new AI enabled data metrics that go far beyond what TSMC provides customers” /@christophauto on X/. “Intel under LBT is leaning hard into Pat’s “systems foundry” differentiation while tweaking it in his own way by providing much deeper co-design and richer data services, while also addressing customer concerns regarding IP protection by creating more explicit firewalls within the company”

📸🧠 Turning Computer Vision Into Real‑World Value at Enterprise Scale

A major shift is underway as enterprises move from lab‑ready computer vision to the far more complex reality of deploying visual intelligence across messy, variable, high‑stakes physical environments. In this episode, Joseph Nelson, Co‑founder and CEO at Roboflow, examines how dependable visual data, models tuned to real operating conditions, and integration with existing production and safety systems determine whether visual AI delivers meaningful value.

⚗️🧠🔁 How Close Is the Chemical Industry to True Autonomy?

The chemical industry is transitioning toward autonomy by implementing state-based automation and digital twins that shift operators from manual routine tasks to high-level process supervision. Although AI breakthroughs like the FKDPP algorithm demonstrate rapid learning in complex operations, full adoption remains hindered by fragmented data connectivity, cybersecurity risks, and the cultural challenge of evolving workforce roles. The primary business value lies in achieving tighter closed-loop integration and safer, optimized transitions between operating modes, which drives greater plant efficiency while keeping humans in the loop to ensure system reliability.

New Product Introduction

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

🦾🧠🔁 Gemini Robotics-ER 1.6: Powering real-world robotics tasks through enhanced embodied reasoning

Introducing Gemini Robotics-ER 1.6, a significant upgrade to our reasoning-first model that enables robots to understand their environments with unprecedented precision. By enhancing spatial reasoning and multi-view understanding, DeepMind is bringing a new level of autonomy to the next generation of physical agents.

This model specializes in reasoning capabilities critical for robotics, including visual and spatial understanding, task planning and success detection. It acts as the high-level reasoning model for a robot, capable of executing tasks by natively calling tools like Google Search to find information, vision-language-action models (VLAs) or any other third-party user-defined functions.

🔋 Deep Dive: Inside the Verge TS Pro Solid-State Battery Pack

Bloom Energy surged 26% over the past month, propelled by a landmark multi-gigawatt expansion of its partnership with Oracle /Business Wire/. Analysts project significant revenue acceleration as the company addresses critical power shortages for AI data centers (mentioned in CC #1 & #4.1). For Success in Solid Oxide Cells We Need to Harness Defects, New Review /AZO Materials/

Business Transactions

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

🇪🇺💰💿 How Europe Actually Finances Semiconductor Investments /EETimes/

🇺🇸🛻 Slate Raises $650 Million in Series C Round

Slate Auto possesses the operating capital to reach the next stage of development, thanks to visionary investors dedicated to developing the affordable and customizable vehicle. TWG Global continues its strong support of Slate and led the round. Slate has taken over 160,000 reservations and will deliver its first vehicles to customers in late 2026.

The Slate Truck will cost in the mid-$20,000s. Every Slate Truck will be built in the same configuration, ready for accessorization after delivery. The manufacturer’s retail price will be announced in June 2026.

Read more at PR Newswire

🇺🇸🛻 Rivian’s Illinois Factory Will Run on Recycled EV Batteries /WSJ/. Rivian and Redwood Materials Announce Energy Storage Partnership for Manufacturing /Business Wire/
🇺🇸🚙 Tesla is developing a new smaller, cheaper EV, sources say /Reuters/. A key question is whether this latest effort to develop a smaller SUV signals a strategy shift back to mass-market human-driven EVs or whether the new model would align more with Tesla’s vision for fully autonomous vehicles.

🇩🇪📐🧠 Synera Raises $40M Series B to Scale Agentic AI Engineering for Global Manufacturers

Synera, the agentic AI platform orchestrating the full industrial engineering value chain, announced a $40 million (€35M) Series B round led by Revaia, with participation from Capgemini through ISAI Cap Venture. The round also includes all existing Series A investors, including UVC Partners with a substantial commitment from its growth fund, BMW iVentures, Cherry Ventures, Venture Stars, and Spark Capital—marking a step change in Synera’s trajectory as it moves from early adoption to large‑scale industrial deployment.

Unlike solutions that require replacing existing infrastructure, Synera integrates with more than 80+ engineering tools and enterprise systems, enabling automation while keeping data and engineering intellectual property secure through on‑premises deployment. The result is a major leap in engineering productivity: faster development cycles, KPIs, reduced material usage, innovative product designs, and cost efficiencies that directly influence competitiveness and production economics.

Read more at Business Wire

🇬🇧 StirLight raises £1.25M to bring real-time quality assurance to friction stir welding at scale

StirLight has secured £1.25 million to commercialize its technology and accelerate the adoption of advanced manufacturing processes at scale by major industrial original equipment manufacturers. The company combines friction stir welding expertise with StirSense, a proprietary real-time process-monitoring and quality-assurance platform. The funding comprises over £750,000 in pre-seed investment from Haatch Ventures, The British Business Bank, D2N2 and angel investors, alongside approximately £500,000 in grant funding from Innovate UK and The Aerospace Technology Institute (‘ATI’) across two R&D projects.

Constraint Capital #4.1 - Apr 2026

David Rogers — Mon, 13 Apr 2026 13:03:38 GMT

We left off Constraint Capital #4.1 discussing the components of AI Factories in critically short supply ⤵️

Since then, multiple folks have commented on the energy costs, correctly placing the chip bottleneck as more acute than the power bottleneck:

Even if energy costs double, a GPU goes from $1.40/hr to $1.50/hr. Nobody notices a dime when the models are improving so fast the value dwarfs the cost.

Even if you don't add more power, but simply add more batteries, you can unlock 20% more of the US's terawatt scale power grid. This is because grid utilities want to make sure they're sized for peak summer load that hits a few hours a year. With enough batteries, you can make this guarantee, even without turning on more power plants!

Fundamentally, there's a lot of different ways to bring power online over the next few years. Building more logic and memory is far more difficult and centralized, so that's where Dylan thinks the bottleneck will be.

@dylan522p on why power isn’t gonna be the big one over the next few years /Dwarkesh on X/

But terrestrial AI factories aren’t the only data centers needed.

Tell me a little bit about data centers. Do you envision putting them on the moon or in low Earth orbit or higher?
Putting them around Earth, probably around the moon, and then maybe ultimately, around the sun would be incredible. The gravitational pull on the Moon is much less, about a sixth of what it is on Earth, so if we’re building these satellites on the moon with elements and materials from the moon, it would be much faster and cheaper [to launch them].
Read TIME’s Full Interview with SpaceX’s Gwynne Shotwell /TIME/

So we will start at energy systems and explain the bottlenecks along the way to the space economy…

[Overcapacity] Choosin' Texas for Manufacturing Energy

David Rogers — Sun, 12 Apr 2026 16:01:20 GMT

Thank you for being a paid subscriber! This week’s bonus board is available until 2026-05-10.

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This weeks digest:

Choosin' Texas for Manufacturing Energy

David Rogers — Sun, 12 Apr 2026 13:03:13 GMT

Shop Talk

Capturing this week’s zeitgeist

The Texas triangle of Houston, Austin, and Dallas have secured a manufacturing renaissance by doubling down on the gritty “substrate” of the physical world /SightBringer on X/. These cities have positioned themselves as the masters of hard power, offering the energy /Manufacturing Dive/, logistics, and buildable land necessary to turn AI abstractions into physical output. By prioritizing functional scale and industrial competence over aesthetic vibes, Texas has built a resilient machine capable of powering, cooling, and housing the future of global industry.

Key Drivers of Texas Expansion

Texas CHIPS Act: Governor Abbott signed legislation in 2023 to establish the Texas Semiconductor Innovation Fund /Texas Gov/ to attract and support these massive investments.
Workforce Development: Projects like Texas A&M’s $200M semiconductor project are being developed to support the expanding talent needs through 2028. /YouTube/
AI Demand: The surge in AI and data center needs is the primary driver, with companies aiming for vertical integration and increased localized production. /Manufacturing Dive/

Up Next: Hannover Messe 2026, April 20 - 24

Hannover Messe coming up next week and it’s a great place to see the entire exponential ecosystem!

The top 10 smart manufacturing technology vendors /IoT Analytics/

I will be focusing on the leaders and startups of scalable Data, AI, and Intelligence:

Databricks at Hannover Messe /Databricks/
Litmus at Hannover Messe 2026: The Industrial Data Foundation for Enterprise AI /Litmus/
HighByte at Hannover Messe 2026: Ecosystem in Action /HighByte/
AVEVA at Hannover Messe 2026: Harness your industrial intelligence /AVEVA/
Meet Zeta Alpha at Hannover Messe 2026 /Zeta Alpha/. See how Agentic AI is transforming how engineers and R&D teams discover, organize, and act on technical knowledge.
Connect With Azumuta at Hannover Messe 2026 /Azumuta/

Reply to this email if you would like to catch up in Hanover!

Last week’s answer: From Industrial Versailles to Man on the Moon: Earthset From the Lunar Far Side /NASA/

Assembly Line

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

This Is How AI Will Automate Every Industry

Sorcery got rare access inside Applied Intuition’s commercial garage with Co-Founders CEO Qasar Younis and CTO Peter Ludwig, where they’re building AI systems that power cars, trucks, mining equipment, defense systems, and more. In a never-before-seen tour to the public, Applied Intuition showcases where/how real machines across industries are being rebuilt with AI.

Qasar and Peter break down how one platform can run everything from a car to a boat to a mining site, and why the future of AI is no longer just software, but systems that move the real world.

A New Chapter for Pronto: We Have Officially Been Acquired by Atoms /Pronto/. As of today, Pronto is proud to become the core technology engine of Atoms Mining, one of three divisions within the company dedicated to digitizing the physical world through purpose-built, intelligent machines.

Inside a Warehouse Automation Project: How Sumitomo Drive Technologies Is Transforming Logistics and Reshoring Operations

Ocado to launch AI-powered Ocado IQ software at MODEX /AutomatedWarehouse/
Auditors for Dexory have issued a rare warning over gaps in its financial records after the British robotics firm Dexory reported surging revenues alongside deepening losses /City AM/. The accounts come just days after Dexory secured £8.5m from the British Business Bank as part of a wider Series C round, with backing from investors including Eurazeo, Atomico and Lakestar.

NOTE: MODEX 2026 is on display April 13th-16th in Atlanta, GA as the largest manufacturing and supply chain event in 2026.

X-Force Threat Intelligence Index 2026

For the fifth consecutive year, the manufacturing sector remained the most attacked industry, representing 27.7% of all incidents within the top industries. This ongoing targeting reflects its critical role in global supply chains and the high value of operational and intellectual property data.

Share of incidents by industry in 2025 and 2024. Source: IBM X-Force.

Attackers leveraged several methods to breach manufacturing systems, with exploitation of public-facing applications (32%) emerging as the most common vector. Valid accounts (domain) (16%) and external remote services (11%) were also prominent, reflecting attackers’ reliance on exploiting misconfigured or insufficiently secured access points.

Information to Atoms

Below are simulations and printed-on-silicon images from a scanning electron microscope (SEM) of a complex metal one (M1) layer printed in a single exposure with Substrate’s X-ray lithography tool, enabled by AlphaEvolve-optimized simulations. The printed patterns are equivalent in resolution to “high numerical aperture” (High-NA) lithography, which is equivalent to the requirements of the 2 nm semiconductor node.

Beyond optimizing for success, the real power of this framework is its ability to predict not just that something will fail, but why. When we understand where and why printing fidelity breaks down, we can compensate by adjusting other parameters, simulate, and then validate with real-world printing.

We are now using AlphaEvolve in other areas, from material discovery to automated circuit layouts. We are also exploring ways to combine AlphaEvolve with other models and techniques to speed up research. One promising area is integrating AlphaEvolve with models focused on scientific knowledge, such as Gemini 3 Deep Think, in a semi-autonomous research loop.

New Product Introduction

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

Intel Foundry Achieves Breakthrough with World’s Thinnest GaN Chiplet Technology

✍️ Author: Han Wui Then

Researchers at Intel Foundry have demonstrated a first-of-its-kind GaN chiplet technology built on 300 mm GaN-on-silicon wafers, marking a significant leap forward in semiconductor design. Presented at the 2025 IEEE International Electron Devices Meeting (IEDM), this work tackles one of the most pressing challenges in modern computing: how to deliver more power, speed, and efficiency in an increasingly compact space. To meet the demand of graphics processors, servers, and wireless networks for ever-greater performance, the Intel Foundry team developed an ultra-thin GaN chiplet — its base silicon measuring just 19 μm thick, roughly one-fifth the width of a human hair — along with the industry’s first fully monolithic on-die digital control circuits, all built using a single integrated manufacturing process.

Thinning a semiconductor wafer sounds straightforward, but doing it on a fully processed 300 mm GaN-on-silicon wafer — one that already contains all the transistors and metal wiring layers — without damaging those structures is a formidable engineering challenge. The Intel Foundry team accomplished this using a technique called stealth dicing before grinding (SDBG) /DISCO/, which uses a precisely controlled laser to create microscopic fracture lines inside the wafer before a mechanical grinding step reduces its thickness. The result is a GaN chiplet with an underlying silicon base of just 19 μm.

Real-Time Injection Molding Simulation, Powered by AI

Introducing Cadmould AI Solver, the world’s first neural physics engine for plastic injection molding. This technology is set to revolutionize design for manufacturing by combining the accuracy of physics engines with the speed of neural networks to deliver simulation results in seconds.

This interactive research preview allows you to test-drive our AI model live. Instead of waiting for results, you receive instant feedback on filling pattern, pressure, and temperature in seconds. It is capable of modeling complex physical interactions, including multi-gate scenarios, with accuracy that rivals traditional solvers. Please note that this preview is a focused showcase of the filling phase only.

Business Transactions

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

🚀🕴️ Inside the SpaceX founder factory—and the race to solve the next generation of impossible problems /Fast Company/. Fast Company built a database of 400+ ex-SpaceX employees turned company builders, the largest ever. What they learned, how they’re applying it, and the future they’re building.

🇺🇸💿 SiFive Raises $400 Million to Accelerate High-Performance RISC-V Data Center Solutions; Company Valuation Now Stands at $3.65 Billion

SiFive, the gold standard for RISC-V processor IP, announced it has raised $400 million in an oversubscribed Series G financing to accelerate its high-performance data center roadmap. This equity funding round was led by Atreides Management with Apollo Global Management, NVIDIA, Point72 Turion, and T. Rowe Price Investment Management, Inc., alongside repeat investors Prosperity7 Ventures, and Sutter Hill Ventures. The financing values the company at $3.65 billion and will accelerate SiFive’s RISC-V CPU and AI IP solutions for the data center.

CPUs are critical in agentic AI systems because they excel at orchestrating complex system level coordination tasks that GPUs and accelerators aren’t designed to handle efficiently. As AI evolves toward more complex agentic models, efficient CPU performance is critical to expanding compute capacity within existing power envelopes. SiFive enables this transition by replacing complex, power-hungry legacy architectures with modern RISC-V CPUs that are inherently lower power. RISC-V integrates scalar, vector, and matrix compute into a single, standards-based interface that helps customers scale rapidly, significantly accelerating hardware development to match the speed of AI innovation.

Read more at Business Wire

🇺🇸⚗️ Membrane Technology & Research Secures $27 Million Investment to Accelerate Global Deployment of Membrane-Based Solutions

Membrane Technology & Research, Inc. (MTR), a global leader in membrane-based separation technologies, today announced it has secured a $27 million equity investment led by Climate Investment, with participation from Hartree Partners. Combined with MTR’s commercially-proven and scalable technology platform, this investment strengthens the company’s position to accelerate global deployment in industrial separations and carbon capture applications.

Read more at Business Wire

Constraint Capital #4 - Apr 2026

David Rogers — Mon, 06 Apr 2026 13:03:35 GMT

In the history of industrial revolutions, we didn’t just invent the engine; we built the factory. March 2026 has officially marked that same transition for the digital age. We have moved past the era of singular crafted AI models and entered the era of the AI Factories.

Demand for intelligence has effectively outstripped our ability to house it. In this fourth edition of Constraint Capital, we set the stage of the dual seismic events of this month: NVIDIA’s GTC 2026 /YouTube/ and the joint SpaceX/Tesla TERAFAB announcement /SpaceX on X/.

As NVIDIA CEO Jensen Huang recently declared, “I love constraints... because in a world of constraint, you have no choice but to choose the best.” /Tom’s Hardware/

If 2025 was about the ‘what’ of AI, 2026 is about the ‘where’ and ‘with what.’ We are mapping a future where the bottlenecks are no longer just in the code, but in the very atoms required to stand up a factory.

Priority 1: The “Triple Wall” (Land, Power, and Shell)

Huang identifies these as the ultimate gatekeepers. When land, power, and shell are constrained, an AI firm cannot afford to experiment with arbitrary hardware.

The Flight to Quality: Because you cannot easily expand a 1-gigawatt footprint, you must populate it with the highest-performing silicon to maximize revenue-per-watt. As Huang notes, “If I choose poorly, my revenues are affected... they can’t choose poorly.”
The TERAFAB Pivot: Musk’s move to orbital compute is the ultimate admission that the terrestrial “Triple Wall” has become impenetrable. 80% of Terafab’s output is heading for space specifically to bypass the land and power constraints of Earth.

Priority 2: The “Atoms” (Wafers, CoWoS, and HBM)

The physical production of chips remains the most immediate bottleneck. NVIDIA has moved from a just-in-time to a “total-security” model.

Secured Supply: Huang has confirmed NVIDIA has “all the memories (HBM), all the wafers, and all the CoWoS (packaging).” By securing the entire DRAM and TSMC production lines for years in advance, NVIDIA has turned a component shortage into a competitive moat.

Money is the most obvious challenge for Elon Musk’s chip venture. To build 1 TW of AI silicon per year, Elon Musk’s TeraFab will need to process the equivalent of 22.4 million Rubin Ultra GPU wafers per year, 2.716 million Vera CPU wafers per year, and 15.824 million HBM4E wafers per year, according to estimates from premier semiconductor analysis firm Bernstein. To do so, TeraFab will need from 142 to 358 fabs, the report claims.

From “Analyzing Elon Musk’s TeraFab — A step towards Tesla and SpaceX’s partial vertical integration, or an unattainable dream?” /Tom’s Hardware/

The 2% Problem: Musk’s TERAFAB is a response to this exact constraint. If NVIDIA has secured the atoms, Tesla/SpaceX have no choice but to build their own recursive loop fab to bypass the global supply ceiling.

Priority 3: The “Unseen” Essentials (Copper, MLCCs, and Cables)

The most overlooked constraints are the passive components that hold the factory together.

Everything from Copper to Capacitors: Huang highlighted that NVIDIA has secured everything down to multilayer ceramic capacitors (MLCCs), connectors, and cables.
The Infrastructure Burden: The transition to GTC 2026’s 800V DC power architectures and liquid-to-chip cooling requires a massive influx of specialized copper and thermal components that are currently in a state of fantastic scarcity for those who own the supply.

Among the most important talks at GTC was Jeff Dean and Bill Daly exploring “the critical intersections of hardware innovation, systems scaling, and algorithmic advancement needed to propel AI into the 2026–2030 era of agentic systems, ultra-low-latency reasoning, and energy-efficient scaling.” Rewatch below.

While the TERAFAB announcement sparked speculation about non-conventional AI compute…

So what could this unconventional compute be? Let’s dive in…

[Overcapacity] From Industrial Versailles to Man on the Moon

David Rogers — Sun, 05 Apr 2026 16:02:56 GMT

Overcapacity

Thank you for being a paid subscriber! This week’s bonus board is available until 2026-05-03.

Click to access ⤵️

This weeks digest:

From Industrial Versailles to Man on the Moon

David Rogers — Sun, 05 Apr 2026 13:02:07 GMT

Shop Talk

Capturing this week’s zeitgeist

In 1956, the GM Tech Center was hailed as an “Industrial Versailles” /JSTOR/ a sprawling monument to the belief that the future could be manufactured through sheer precision and architectural grandness. But as we’ve learned over the last 70 years /Assembly/, the most iconic leaps often happen in the frantic, unpolished spaces between the prototype and the finish line.

In this week’s issue, we look at the man on the moon mindset that bridges Detroit’s mid-century dominance with today’s silicon-and-intelligence frontiers. Apple’s own “man on the moon” project the high-stakes was a six-month sprint to replace the iPhone’s plastic screen with glass just weeks before launch.

Flash forward to today, and the legacy of these high-pressure tech centers is alive and well this morning. The four-person crew of Artemis 2 streaks past the halfway point between Earth and the Moon, we see the ultimate result of turning impossible prototypes into operational reality which is what Exponential Industry is all about.

Quote of the Week

And what confirms that the site is very competitive is that in the current market environment and all the headwinds we are facing from what’s happening in the Middle East, still, after a smooth startup of our plants, the plants are running at a very high utilization rate, while our competitors, many of them had to reduce their run rate, some even had to declare force majeure. Given that we are having very good cost positions and we are having a mixed-feed cracker that allows us to shift feedstocks between naphtha and butanes, we can run full.
Stephan Kothrade, CTO BASF /Yicai/

Failed AI tractor company, Monarch Tractor, lays off all employees, abandons Bay Area headquarters /SFGATE/

Last week’s answer: Agency to Build Thinking Factories

Assembly Line

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

🚀 Artemis II Launches Astronauts to the Moon

Artemis II’s SLS (Space Launch System) rocket lifted off from Launch Pad 39B at NASA’s Kennedy Space Center in Florida, at 6:35 p.m. EDT (2235 UTC) on April 1, 2026, sending NASA astronauts Reid Wiseman, Victor Glover, Christina Koch, and CSA (Canadian Space Agency) astronaut Jeremy Hansen on an approximately 10-day test flight around the Moon and back aboard their Orion spacecraft.

🚀 Liftoff! NASA Launches Astronauts on Historic Artemis Moon Mission /NASA/
🚀💰 SpaceX Has Filed Confidentially for IPO Ahead of AI Rivals /Bloomberg/ seeking a valuation in the IPO of more than $1.75 trillion while raising as much as $75 billion.

🚗 Reimagine marketing at Volkswagen Group with generative AI

✍️ Author: Liam Byrne, Kim Robins, Philipp Hinderberger, Sebastian Angersbach, Philip Trempler, and Weiran Zhang

The first step in Volkswagen’s generative AI journey was deceptively simple: could foundation models (FMs) generate photorealistic images of their vehicles? Initial experiments with base diffusion models revealed two critical gaps. First, while these models could produce impressive automotive imagery, they lacked decades of Volkswagen design language. The tiniest features matter: the exact texture of a grille mesh, the precise geometry of headlight housings, the specific wheel spoke patterns for each model line. The models would generate a Volkswagen, but with generic wheels and grille patterns that didn’t match an actual model year. Second, base models had no knowledge of unreleased vehicles. They couldn’t generate images of next year’s models still under development, severely limiting their utility for forward-looking marketing campaigns.

The solution required fine-tuning foundation models on Volkswagen’s proprietary visual assets. Working with SolidMeta, the team used DreamBooth fine-tuning techniques with training data collected from digital twins in NVIDIA Omniverse. The following diagram illustrates this process for the Volkswagen Tiguan. DreamBooth training works in two parts: first, the model learns from VW Tiguan images paired with a unique identifier token ‘VW Tiguan’ that teaches it this specific vehicle. Second, the model trains on generic car images to preserve its general capabilities and help prevent overfitting to the training set.

Autonomous CNC Programming

Tanmay Aggarwal, CEO of Lambda Function, in a deep conversation about autonomous CNC programming, real-time shop floor integration, and why memory and causal inference matter for the next wave of physical AI.

🎨🦾 A New Way to Spray Paint Color

✍️ Author: Sandesh Manik, a mechatronics engineer and the founder of a stealth startup focused on 3D modeling for hardware.

I wanted my solution to be inexpensive and simple enough to build as a DIY project and functional enough for an artist to use, without breaking their flow. So I began prototyping a system that combines base colors while they are still in pressurized form from off-the-shelf cans.
Even though the system worked, the solenoid valves I used constantly clogged up. Designed for water purifiers, the valves didn’t prevent paint from entering the mechanism, where the paint would harden. Moreover, when the valves were turned off, they could stop backflow only if the inlet remained pressurized. So disconnecting a paint can from the system would cause instant leaking. Other off-the-shelf valves I tried couldn’t cycle fast enough and were too expensive.

Performant rotary pinch valve design

So I created my own mechanism: a high-speed, electronically controlled, rotary pinch valve. It has a stepper motor that rotates a lever with a rolling bearing to constrict fluid flow inside a flexible tube. This concept isn’t new—there’s something like them in every peristaltic pump. But I added a spring to firmly hold the lever in the closed position against any back pressure when the motor isn’t powered, making it a normally closed valve that isolates the attached can. Additionally, the valve is fast enough to be open for as little as 30 milliseconds.

🚗🧠🔧 Can AI Predict Loose Bolts in Automotive Assemblies?

Standardized test methods, such as DIN 65151 and DIN 25201, are effective in terms of performance evaluation for single bolt and nut types. However, the rigid conditions in those tests are not necessarily applicable to bolted joints in automobile chassis. The conditions are different, and the external loads acting on the joints have variable frequency.

Our approach consisted of three steps. In the first step, we collected external loading values from mechanical testing of engine suspension joints. In the second step, we performed Taguchi method experiments with actual joint conditions to obtain training and test data for the neural network. In the third step, we created a neural network with the Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms to create a relationship between the controlled factors and the loosening rate. We then collected the mean squared error (MSE) values to evaluate the prediction errors of the neural network.

Read more at Assembly and Machines

New Product Introduction

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

🏭📊🧠 HighByte Brings AI to Industrial Data Pipelines with Version 4.4: Federated Namespaces and AI-Driven Pipelines

✍️ Author: Jeffrey Schroeder

HighByte Intelligence Hub version 4.4 is built for exactly that environment. This release introduces Central Data for composing federated namespaces and pipelines with remote data sources, new connectivity options including native Databricks Zerobus support and the CESMII i3X Server interface, and a Pipeline AI Agent that makes pipeline configuration more accessible across teams and skill levels. Taken together, they extend what Industrial DataOps teams can do and who can do it.

Read more at Business Wire and HighByte

🏭📊 Unified Namespace, Revisited: Toward a Composable Industrial Architecture /Solace/
🏭📊🧠 HP Indigo boosts manufacturing yield (from 60% to 92%) and traceability with Databricks and Unity Catalog /Databricks/

📶📐🧠 Introducing Atlas RF Studio: Toward a Foundation Model for Electromagnetics

✍️ Author: Christopher Bryant, Tommaso Dreossi, Hao Liu, Nathan Mirman, Noah Kessler, Usman Farman, Daniel Pedraza, Trevor Beaton, Akshay Kumar, Ben Gelb, Mike Frei, Arun Natarajan, Harish Krishnaswamy

Atlas RF Studio is powered by two models that mirror the two fundamental problems of electromagnetic engineering. Both develop an understanding of how geometry and electromagnetic behavior relate, but they apply this understanding in opposite directions.
We call the forward model Heaviside-0, after Oliver Heaviside, who reformulated Maxwell’s equations into the compact vector form that made modern electromagnetic analysis possible. Heaviside was the great characterizer. He gave engineers the mathematical language to describe what fields do. Our forward model carries that legacy. Given a circuit layout, it predicts S-parameters in milliseconds rather than the significant compute time required by a numerical solver. This is what makes rapid design iteration possible.
We call the inverse model Marconi-0, after Guglielmo Marconi, who invented and built the first practical radio systems through relentless experimentation, turning desired wireless behavior into physical reality. Our inverse model does the same thing. Given a target S-parameter response, it generates a physical geometry that produces it. This is the creative half, the one that proposes designs a human might never think to try.
These two models work in tandem. Marconi-0 proposes a collection of designs that it thinks will produce your target behavior, and Heaviside-0 quickly checks whether the proposed designs exhibit that behavior. Based on that feedback, Marconi-0 can then iteratively propose new designs that are more likely to produce the desired behavior, and Heaviside-0 can then characterize them again to see if they are any better.

Business Transactions

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

🇺🇸 Saronic Closes $1.75B Series D at $9.25B Valuation to Accelerate a New Era of Maritime Autonomy

Saronic Technologies announced it has closed $1.75 billion in Series D funding to advance its mission of ensuring maritime superiority for the U.S. and its allies by delivering autonomous platforms at scale across defense and commercial sectors. The round was led by Kleiner Perkins and values the company at $9.25 billion.

An important component to Saronic’s efforts is the development of Port Alpha — its next generation shipyard — alongside the rapid expansion of its existing production facilities in Louisiana and Texas. This capital will allow Saronic to accelerate the growth and maturation of its shipbuilding enterprise, one that is defined by innovation, scalability, and strategic impact.

Read more at PR Newswire

🇺🇸 iBase-t Announces Strategic Growth Investment from TA to Accelerate AI-Powered Digital Manufacturing and MRO Transformation in Aerospace & Defense /Business Wire/

🇺🇸🛰️ Starcloud Raises $170M Series A at $1.1bn Valuation Led by Benchmark and EQT Ventures

Starcloud, the company building data centers in space, announced it has raised a $170 million Series A, at a $1.1 billion valuation. Achieving unicorn status just 17 months after its Y Combinator demo day, Starcloud is now the fastest unicorn in Y Combinator history. The round is also more than double the size of the next largest YC Series A, and brings the company’s total capital raised to $200 million.

Starcloud has demonstrated a pace of execution previously unseen in the aerospace or tech industries. With just $3 million in pre-seed funding, the company designed, built, and launched its first satellite, Starcloud-1, in a record 21 months. Launched in November 2025, the mission achieved several historic industry firsts:

First NVIDIA H100 in orbit: Successfully deployed the most powerful GPU in space, delivering a 100x increase in AI compute.
First orbital AI training: Successfully trained an AI model in space.
First orbital inference on Gemini: Successfully ran a version of Gemini in orbit.
First orbital fine-tuning: Demonstrated high-powered inference and model fine-tuning in space.

Read more at Business Wire

🇪🇺⚡🛰️ TerraSpark advances space-based solar power with €5M funding /Tech.eu/. TerraSpark is developing space-based solar power to deliver continuous energy independent of weather or time of day, starting with wireless transmission on Earth before scaling to orbital systems.

Founders Factory & Rio Tinto invest in reduced-impact mining through AI & Breakthrough Technologies

The six investments are:

Durin, automated drilling rigs to accelerate mineral discovery and reduce exploration costs (Los Angeles, US)
Rock Zero, zero-waste, cost-efficient process to extract lithium from hard rock deposits (Cambridge, US)
Terra AI, AI for mineral exploration to reduce drilling costs and improve accuracy (Palo Alto, US)
Ekion, electrokinetic in-situ recovery (EK-ISR) technology to extract metals from stranded deposits with minimal waste and emissions (Perth, Australia)
Rainstick, agriculture & nature restoration using electrical fields to mimic the natural effects of lightning, boosting seed yields faster and more sustainably (Cairns, Australia)
Thunderstone, reduced-impact mining using underground electric stimulation to extract critical metals with minimal waste and cost (US)

What Could Bezos Buy?

David Rogers — Wed, 01 Apr 2026 13:03:49 GMT

Back on February 27th, the Financial Times broke the news on Jeff Bezos’ Project Prometheus /FT/ and its associated ~~$30~~ $100 billion /WSJ/ "manufacturing transformation vehicle." It appears Jeff Bezos and Vikram Bajaj are targeting a specific profile of business that blends traditional heavy industry with high-complexity engineering.

Exponential Industry first started tracking the Project in the November 23rd digest.

The Project strategy seems to not just to invest in AI, but to buy legacy companies that are currently being devalued or disrupted by AI, then use proprietary World Model /NVIDIA/ technology to radically improve their margins and speed.

Last week, following the Wall Street Journal update, the gentleman at TBPN proposed five options: Lear, BorgWarner, Hexcel, Goodyear, and Rockwell Automation /TBPN/ with a caveat:

This is all mostly a wild guess at this point, the fact that Bezos could potentially link to this Project Prometheus means there’s a chance this whole project will be much more aligned to the traditional software singularity path, and there’s always a chance we get an Elon-style megacorp with Blue Origin involved at some point. Either way, it’s a big move from an experienced operator with lots of opportunity ahead. Will be fun to follow along.

Now that speculation is abound, I figured its time to outline the 'target profile' and raise several companies to share with you and see how well they fit the criteria.

My speculation began back on March 4th.

[Overcapacity] Agency to Build Thinking Factories

David Rogers — Sun, 29 Mar 2026 16:02:52 GMT

Thank you for being a paid subscriber! This week’s bonus board is available until 2026-04-26.

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Connect with Allie Systems on LinkedIn for an invite

This weeks digest:

Agency to Build Thinking Factories

David Rogers — Sun, 29 Mar 2026 13:03:31 GMT

Shop Talk

Capturing this week’s zeitgeist

I am excited to continue my collaboration with Allie Systems with a virtual round table on "Fact vs. Fiction: What It Really Takes to Build a Factory That Thinks”, this Tuesday, March 31 at 11 AM CST. The session is designed to get past the hype cycle and share what's working on the floor. We will dig into the data foundation problem, change management, use case mapping, and what "autonomous operations" actually looks like in practice.

Quote of the Week

Build samples. Test them. Analyze deeply why things fail. Build tests that catch those failures. Correlate your module-level tests with system-level FATP tests. Go back to the process, tune it. Build more samples. Repeat.
This is how you observe the “reinforcement learning” of manufacturing. Not by reading about it — by running the loop yourself, staring at failure pareto charts, arguing with the process engineer about whether the epoxy dispense volume is drifting, and watching the yield numbers tick up over weeks as you close the gaps.
Read more at “The Dark Matter of Hardware Engineering” /Dark Matter/

🧪📊🧠 53 Years of Trade Secrets, Locked in Software That Will Never See an AI /Dan Thompson on X/

Last week’s answer: The Automation High Point Story ends as a new era takes over.

This is the written version of a talk I gave at the OSU HAMMER Engineering Research Center in February 2026…

Assembly Line

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

👕♻️ How Renasens Cracked Textile Recycling And Raised $11.5 Million

✍️ Author: Brooke Roberts-Islam

The engineer’s technology uses supercritical carbon dioxide (a fluid) as the solvent (dissolving solution) rather than water or harsh chemicals, thereby reducing water and energy use and the overall footprint of the recycling process. While the use of supercritical CO₂ is not novel, the application for textile recycling is.

🎛️🖥️ What Happens When Manufacturers Build Their Own MES Applications in Two Days

✍️ Author: Jenna Gabriel

Production Lab is a two-day, hands-on building event where MachineMetrics customers work side by side with our engineering team to design and build custom applications on the MachineMetrics platform. The tools they used: Max AI for data exploration and prompt development, Lovable and Cursor for AI-assisted application building, and Carbide, MachineMetrics’ custom application builder, for deploying production-grade applications directly into the platform. Every team shipped a working solution tied to real, live machine data by the end of day two.

The execution gap is real. It lives between what your ERP plans and what your shop floor actually does, and it costs manufacturers margin, capacity, and hours every single shift. Closing it requires software that fits how your operation actually runs, not a generic template you adapt yourself.

📐🧠 Engineering intent to compiled into engineering artifacts

In our setup, a textual description of a production environment and the objects to be placed is enough to generate USDA files, the native scene description format used by NVIDIA Omniverse to describe 3D scenes, assets, transformations, materials, hierarchies and layouts.
The workflow looks like this:
An engineer describes what they want to visualize.
Claude (Opus 4.6) compiles this description into machine-readable USDA files.
Omniverse loads the scene and the factory layout appears.
What sounds simple is actually a big shift. In the future, engineers will no longer interact directly with engineering tools.

Read more at Dr. Dirk Alexander Molitor on LinkedIn

📐🧠 Continuous Design Reviews with AI, in addition to manual human reviews is the future. /Dalus on X/
📐 The Myth of CAD as Code /emm0sh on X/
📐🧠 Synopsys Brings Agentic Engineering Into Focus as AI-Driven Design Tests Productivity Limits /EETimes/

Spectech Newsletter

Fungible Factories

a month ago · 24 likes · 1 comment · Ben Reinhardt

New Product Introduction

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

🏆 The most innovative manufacturing companies for 2026

The most consequential changes are unfolding across materials and components that form the foundation of industrial supply. Hertha Metals and Electra are disrupting the carbon-intensive economic model of steel and iron production with electrified, cost-effective methods that can be integrated into existing infrastructure. Abstrax is stabilizing climate-volatile agricultural inputs with precision-engineered flavor systems that enable beverage makers to maintain product consistency despite climate variability. Likewise, TerraSlate is disrupting coated and laminated materials with a recyclable waterproof paper that can withstand industrial use, without relying on plastic.
At the factory level, Acerta AI and Sight Machine are embedding diagnostics and analysis directly into live operations so defects can be traced and corrected in minutes instead of days. Freeform’s high-throughput metal printing architecture and Cellares’s automated cell therapy facilities showcase that machine learning and robotics can maintain tight tolerances while dramatically increasing throughput.

💿 Arm expands compute platform to silicon products in historic company first

Arm Holdings plc (NASDAQ: ARM) today announced the next evolution of the Arm compute platform, extending into production silicon products for the first time in the company’s history. This begins with the launch of the Arm AGI CPU, an Arm-designed CPU for AI data centers, built to address a rising class of agentic AI workloads.

For more than three decades, the industry has innovated on the Arm compute platform to deliver scalable, power-efficient computing across hundreds of billions of devices. As AI transforms global computing infrastructure, partners across the ecosystem are asking for ways to deploy Arm technology at scale. In response, Arm is expanding its platform strategy beyond IP and Compute Subsystems (CSS) to include Arm-designed silicon products – giving partners the broadest set of options to build on Arm and enabling faster innovation across the AI ecosystem.

🛢️🧠 Aker BP, Armada to deploy offshore modular data center for AI-driven drilling operations

Aker BP and Armada have entered into an agreement to deploy Armada’s Galleon modular data center for use in an offshore drilling environment on the Norwegian Continental Shelf. Under the agreement, Armada will deliver a Galleon designed to operate in offshore conditions, enabling local processing and analysis of drilling and operational data directly on the rig.

By deploying compute infrastructure directly offshore, the Galleon strengthens operational resilience and standardizes adoption and use of critical vendor applications. Running AI models locally allows energy companies to predict and prevent equipment failures before they occur, reduce unplanned downtime, and maintain continuity during connectivity disruptions. Local compute infrastructure also enhances cybersecurity by minimizing reliance on external networks.

Read more at PR Newswire

🛢️🧠 Onshore Well Exploration & Intervention Demo /Cognite/
🛢️🧠 Cognite and NVIDIA Operationalize NV-Tesseract to Transform Industrial Forecasting /Business Wire/

“Despite heightened market volatility amid the ongoing Middle East turmoil, bankers and analysts say capital markets remain open, particularly for oil ⁠and gas issuers” /Reuters/ as HMH Holding seeks $948 million valuation in US IPO.

Business Transactions

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

🇺🇸🦾🧠 Physical Intelligence in Talks to Raise $1 Billion at $11 Billion Valuation

✍️ Authors: Natasha Mascarenhas, Rebecca Torrence, and Shirin Ghaffary

Physical Intelligence, a two-year-old robotics startup founded by AI academics and former Google DeepMind researchers, is discussing a new funding round of about $1 billion that would bring the company’s valuation to more than $11 billion including dollars raised, according to people familiar with the matter.
The ultimate goal, the company has said, is building models that enable robots to perform any function requested by the user through “vision-language models,” in the same way that large-language models complete digital tasks on command. In recent weeks, the company has released new research about improving memory in robotic software models as well as performance on precise tasks that require careful and detailed manipulation of objects.

🇺🇸🖥️🎛️ DOSS raises $55M to Build the Operations Cloud for the Real World

DOSS raised a $55M Series B, co-led by Madrona and Premji Invest, with Greyhound, Commerce Ventures, and Intuit Ventures as new investors, and continued investment from Theory, General Catalyst, Contrary Capital, Mintaka, and Pathlight VC, and 47th Street Partners.

This raise enables them to: invest deeply in core platform and unified data model, so companies can go live faster with intelligent systems that adapt as fast as their business grows, develop agentic systems that remove the human bottleneck from configuring operations, further define a new category around adaptable operations, not static systems

🏴󠁧󠁢󠁷󠁬󠁳󠁿⚗️ Biomanufacturing Pioneer Cauldron Raises $13.25M

Cauldron Ferm, a leader in advanced biomanufacturing, announced a $13.25 million Series A2 priced round. The round was led by Main Sequence Ventures, with participation from Horizons Ventures, SOSV, and NGS Super, bringing Cauldron’s total funding to $26 million.

Cauldron’s develops a continuous “hyper-fermentation” platform – a proprietary technology designed to deliver step-change improvements in bioprocess efficiency. Biomanufacturing uses living cells as programmable factories, where bio-engineered microbes convert simple inputs like sugars into valuable products. Cauldron’s key advantage is keeping these microbes in a highly productive steady state and running processes continuously for long periods. This increases output while significantly lowering production costs, helping bioproducts compete with conventional industrial alternatives.

Read more at Business Wire

🇺🇸 Helix Earth Secures $12 Million in Oversubscribed Seed 2 Funding to Revolutionize Energy Efficiency and Humidity Management in Commercial HVAC Systems

Helix Earth, a Houston-based hardware company built on proprietary liquid-gas chemistry with roots in NASA aerospace technology, announced today the successful close of its $12 million oversubscribed Seed 2 funding. The oversubscribed financing round was led by Veriten, an energy research, strategy, and investing firm, with participation from Rua Ventures, Carnrite Ventures, Skywriter LLC, Textbook Ventures, and others.

Helix Earth is developing a one-of-a-kind, cost-effective commercial air conditioner add-on that bifurcates the energy required for temperature management from moisture control. The result is healthier indoor air, lower energy bills, reduced building maintenance, and more comfortable spaces for building owners and occupants.

Read more at Business Wire

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[Overcapacity] The Automation High Point Story

David Rogers — Sun, 22 Mar 2026 16:01:52 GMT

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This weeks digest:

The Automation High Point Story

David Rogers — Sun, 22 Mar 2026 13:01:59 GMT

Shop Talk

Capturing this week’s zeitgeist

According to a research tool by Andrej Karpathy /Karpathy's Blog/ industrial engineering technologists face a moderate 6/10 AI exposure because their data-driven CAD and cost-analysis tasks are perceived as highly automatable, yet protected by the physical buffer of on-site floor inspections. In contrast, manual manufacturing roles like assembly and welding maintain low 2/10 to 3/10 exposure scores due to the persistent difficulty of replicating human dexterity in unstructured environments. Broadly, the analysis reveals a paradox where higher-paying, education-intensive roles are significantly more vulnerable to digital AI than the foundational labor powering the factory floor.

What do you find interesting about this analysis?

US Job Market Visualizer with Digital AI Exposure /GitHub/

Last week’s answer: The Catalina Wine Mixer is a scene in the movie Step Brothers and inspired an annual event by the Catalina Island Company.

Assembly Line

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

🏭🦾 Inside Rockwell Automation’s Factory Where Automation Is Built

✍️ Author: David Petersen

The assembly line, fabricated in large part by Calvary Robotics, incorporates the iTRAK modular conveyance system, along with plenty of Rockwell controllers, drives, and I/O, to progress the product along the assembly stages.
The assembly stations themselves are nearly all operated robotically. Depending on the needs, the robots are gantry, SCARA, articulated, or delta styles, some floor-mounted and others mounted above the line. Specialized grippers pick each piece as it builds the contactors according to the order specifications.

📐 Engineering journey of a lightweight drone rotor blade with tape‑sandwich injection moulding

Developing a next generation drone rotor blade calls for new material concepts, accurate process control and smart manufacturing strategies. The objective behind this project was to design a blade that combines very low weight with strong mechanical robustness in demanding flight conditions.

Together with specialists in composites, simulation and moulding technology, a fully automated tape sandwich injection moulding workflow was created. Continuous carbon fibre thermoplastic tapes form the outer structure and are positioned in the mould with high accuracy. The centre of the component is then formed by injecting a short fibre reinforced compound that expands slightly during processing.

🦾 Rapid Operator AI - Hardware, Vision, and Physical AI in One Solution /Vention on YouTube/
Arburg Reveals Production Plans, New Technologies and Results /Plastics Technology/

🧠 Unlocking Industrial Knowledge with AI Agents

We sit down with Jakub from Zeta Alpha to uncover how companies like Festo are leveraging advanced search, RAG, and agentic AI to unlock decades of expertise buried in documents and data silos. We share practical examples, discuss integration challenges, and debate the future of specialized versus generic AI in the industrial landscape.

📑 Factory data could unlock £129bn in UK output report from FourJaw /The Engineer/

🚛🧠 Inside Kodiak AI and the Future of Driverless Freight with Founder and CEO Don Burnette

🚛🧠🤝 Nissan, Uber, Wayve unveil robotaxi tie-up /Reuters/
🚛🧠🤝 Uber and Rivian Partner to Deploy up to 50,000 Fully Autonomous Robotaxis /Rivian/

Should Robot Generalists Get Off Their High Horse?

A conversation between @AnneliesGamble and @Ken_Goldberg, professor of Robotics and Automation at UC Berkeley

The assumption has been: just collect data on everything out there and throw it all together, and it will suddenly start to become general. That has not panned out, and that’s not what customers are looking for.
Even if generalist systems improve, most customers aren’t looking for a robot that might eventually do many things. Many want a robot that can at least do one thing really well, over and over again. “Most successes in robotics require 99.99% uptime,” @samanfarid, CEO of Formic, told me. “Most people underestimate how hard that bar is to hit.” Not to mention, real deployments are also incredibly complex.

📐💿 Design Conductor: An agent autonomously builds a 1.5 GHz Linux-capable RISC-V CPU

Design Conductor (DC) is an autonomous agent which applies the capabilities of frontier models to build semiconductors end-to-end -- that is, from concept to verified, tape-out ready GDSII (layout CAD file). In 12 hours and fully autonomously, DC was able to build several micro-architecture variations of a complete RISC-V CPU (which we dub VerCore) that meet timing at 1.48 GHz (rv32i-zmmul; using the ASAP7 PDK), starting from a 219-word requirements document. The VerCore achieves a CoreMark score of 3261. For historical context, this is roughly equivalent to an Intel Celeron SU2300 from mid-2011 (which ran at 1.2 GHz). To our knowledge, this is the first time an autonomous agent has built a complete, working CPU from spec to GDSII. This report is organized as follows. We first review DC’s design and its key components. We then describe the methodology that DC followed to build VerCore -- including RTL implementation, testbench implementation, frontend debugging, optimization to achieve timing closure, and interacting with backend tools. We review the key characteristics of the resulting VerCore. Finally, we highlight how frontier models could improve to better enable this application, and our lessons learned as to how chips will be built in the future enabled by the capabilities of systems like DC.

New Product Introduction

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

🦾🧠 NVIDIA and Global Robotics Leaders Take Physical AI to the Real World

NVIDIA is partnering with the global robotics ecosystem — including leading robot brain developers, industrial robot giants and humanoid pioneers — to power production-scale physical AI. NVIDIA also unveiled new NVIDIA Isaac™ simulation frameworks and new NVIDIA Cosmos™ and NVIDIA Isaac GR00T open models for the industry to develop, train and deploy the next generation of intelligent robots.

In addition, during his GTC keynote, Huang previewed GR00T N2, a next-generation robot foundation model based on DreamZero research. Built on a new world action model architecture, the model helps robots succeed at new tasks in new environments more than twice as often as leading vision language action models. Slated to be available by the end of the year, GR00T N2 currently ranks No. 1 on MolmoSpaces and RoboArena for generalist robot policies.

Business Transactions

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

💰 Partech’s €300M Impact Fund targets Europe’s next generation of industrial and climate tech leaders /Tech.eu/

🇳🇿🐄 Halter AI Cow Collar Startup reaches $2 Billion Valuation

Billionaire Peter Thiel’s venture capital firm, Founders Fund, is set to lead the financing, said the people, who asked not to be identified discussing private information. The talks are ongoing and details could change.
Halter’s technology is designed to create a virtual fence for cattle and enable farmers to monitor the animals’ locations and health indicators through an app. Its collars, which are solar-powered, connect to farmers’ phones to allow them to manage pastures remotely — for example, a rancher can herd their cows using vibrations and audio cues from the collars.

🇬🇧 Cocoon Secures $15M Series A to Fix A Critical Supply-Demand Gap in the Concrete Industry

Cocoon Carbon, a company unlocking a new, scalable supply of key materials used to make concrete, announced the closing of a $15 million Series A round. The investment was co-led by 2150 and Brick & Mortar Ventures, investors in the built environment and construction sectors. The round included participation from TVC (The Venture Collective) and continued support from existing investors Wireframe Ventures, Celsius Industries, Gigascale Capital, and SOSV.

Cocoon unlocks a new source of SCMs by converting an underutilized and robust supply of steel slag, a byproduct of electric arc furnaces (EAFs), into a low-cost, high-performance cement replacement. EAFs re-melt scrap using electricity, compared to coal powered blast furnaces that turn iron ore into pig iron. With tens of millions of tons of steel slag produced annually in the U.S. and Europe, and EAF steelmaking projected to double by 2050, Cocoon expands the domestic supply base concrete producers rely on to keep costs stable. Cocoon’s new product matches the performance of traditional SCMs while reducing the embodied CO2 of concrete by up to 40%.

Read more at Business Wire

🇺🇸 Rubi Raises $7.5M and Secures Over $60M in Offtake Term Sheets, Advancing Commercialization of Its Breakthrough CO2-to-Materials Platform /PR Newswire/
🇩🇪 Level Nine raises €4M to unlock local feedstocks for chemicals /Tech.eu/ by developing advanced catalysts to enable sustainable chemical production, converting biomass and waste into renewable materials while improving efficiency and supporting industrial-scale adoption.
🇺🇸 V-Glass Secures $3M Investment to Initiate Move from Lab Scale Production into a Pilot Plant /Business Wire/. V-Glass has developed next generation platform technology enabling the low-cost production of vacuum insulated glass (VIG) having 2-3x the thermal performance of ENERGY STAR® windows, lasting twice as long, and costing no more to manufacture.

🇺🇸 Tenkara Raises $7M led by True Ventures to Build Ops Agents for US Manufacturers

Tenkara, the company building ops agents for US manufacturers, announced $7 million in funding led by True Ventures. The round includes participation from HF0, WndrCo, Articulate Capital, Night Capital, SF1, Transpose, early employees at Flexport, and others.

Tenkara is building the next-generation tooling for supply chains. The company’s agents take on the back-office burden so that lean teams can operate like organizations 10 times their size. In its first 18 months, Tenkara signed multiple seven-figure contracts with U.S. manufacturers.

Read more at PR Newswire

🇩🇪 Fibionic secures €3 million seed funding for bionic fiber placement

✍️ Author: Grace Stubbins

Fibionic (Götzens, Austria), a deep-tech startup founded in 2021, has announced the successful closing of a €3 million seed financing round led by co-lead investors Redstone with Euregio+, Caesar and Leap435, and supported by various angel investors. This financing will enable the lightweight engineering company to further industrialize its nature-inspired technology for precise fiber placement and drive market entry into new industries.
Fibionic addresses material and automation inefficiencies via fibionic fiber placement (FFP). The patented, sustainable process uses bionic principles to align fibers specifically along actual load paths, inspired by structures found in nature, such as the wings of a dragonfly. FFP achieves cycle times of up to 1 minute per component, offering optimization potential for composites manufacturing — high-performance, stable components with minimal material use.

[Overcapacity] Catalyna Wine Mixture

David Rogers — Sun, 15 Mar 2026 16:02:58 GMT

Thank you for being a paid subscriber! This week’s bonus board is available until 2026-04-12.

Editor’s note: Overcapacity will be sent at noon Eastern US time each Sunday moving forward.

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This week’s digest:

Catalyna Wine Mixture

David Rogers — Sun, 15 Mar 2026 13:02:43 GMT

Shop Talk

Capturing this week’s zeitgeist

The era of the AI assistant has replaced by a paradigm where “Everything is ~~Computer~~ Code”, a shift led by tools like Claude Code (Coding) and Genie Code (Data Work) that move us from simply writing syntax to delegating entire autonomous lifecycles.

Who will make “Foundry Code”?

This product will autonomously refactor assembly workflows and optimize thermal cycles in real-time, treating a physical production floor with the same agility and version control we currently apply to coding and data work. Some features could include:

Software-Defined Hardware: Acts as a real-time compiler that translates high-level operational goals into optimized machine instructions for PLCs and CNCs.
The “Edit Button” for Reality: Synchronizes digital twins with physical lines to autonomously refactor and deploy updated G-code paths without stopping production.
Agentic Maintenance: Proactive background agents diagnose mechanical anomalies, source parts via ERP, and schedule repairs before failures occur.
Batch-of-One Orchestration: Dynamically rewrites machine recipes for every individual unit to compensate for raw material variances in real-time.

Quote of the Week

Software and automation are becoming increasingly central as machine capabilities improve. Chen outlined three areas where artificial intelligence is being applied across Creality’s platforms: model creation and visualisation, fault detection during printing, and optimisation of print parameters such as supports and toolpaths. “AI can help us to do better 3D modeling,” he said, adding that it is also used for “AI-based detection of faults, of failures”.
Jack Chen, Founder and CEO, Creality /3DPI/

EOS CEO Marie Langer on Next Frontier for Industrial 3D Printing /3DPI/

Last week’s answer: Appetite to Touch Grass and Build Donuts