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AI & Machine Learning Safety

AI & Machine Learning Safety

Engineering Services

Making machine learning defensible in safety-critical systems — education and practice from Critical Systems Analysis

About us

Machine learning breaks the assumptions functional safety was built on. There is no complete specification to verify against, behavior is learned from data rather than designed, and correctness is statistical rather than demonstrated. Making an ML component defensible inside a safety-critical system is its own engineering discipline. Not a bolt-on to the software chapter of an existing standard. Critical Systems Analysis works at exactly that seam: deriving safety requirements for AI under ISO/PAS 8800 for road vehicles and VDE-AR-E 2842-61 for autonomous systems more broadly, connecting them to ISO 26262 and IEC 61508 architectures respectively, and building the dataset requirements, model assurance arguments, and verification evidence that an assessor will actually accept. This page shares practical education from the CSA team: AI and ML definitions and concepts, statistical learning and what training really guarantees, trust and trustworthiness as engineering properties, the interaction between machine learning and cybersecurity, the emerging standards and legal landscape, and the basic notions of neural networks every safety engineer now needs. Critical Systems Analysis provides functional safety assessment, safety and cybersecurity analysis (FTA, FMEA, FMEDA, HARA, TARA), certification support, and training across automotive, machinery, robotics, semiconductor and industrial automation. Independent, standards-grounded, and engineering-first. Learn more at www.criticalsystemsanalysis.com — or reach out to talk through the ML safety argument you need to make.

Website
https://www.criticalsystemsanalysis.com/
Industry
Engineering Services
Company size
2-10 employees
Type
Privately Held
Specialties
AI safety, machine learning safety, ISO/PAS 8800, ISO 26262, IEC 61508, VDE-AR-E 2842-61, dataset safety, model assurance, verification and validation, safety requirements for AI

Updates

  • BionicHIVE’s SqUID explored a new approach to warehouse automation by climbing existing storage racks to pick and replenish boxes. Read more in our latest article:https://lnkd.in/gNxE76_m

    𝗠𝗲𝗲𝘁 𝗦𝗾𝘂𝗶𝗱, 𝘁𝗵𝗲 𝗴𝗮𝗺𝗲-𝗰𝗵𝗮𝗻𝗴𝗲𝗿 𝗶𝗻 𝘄𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 🏪 Imagine a robotic fleet that doesn’t just sit around waiting for instructions. Squid climbs racks from floor to ceiling, sorting and putting away items with remarkable efficiency. Here’s why this matters for you : → Efficiency Boost    ↳ Squid streamlines sorting and put-away tasks, reducing time spent on manual labor. → Safety First   ↳ With built-in cameras and sensors, these robots navigate around people and obstacles, ensuring a safer working environment. → Seamless Integration   ↳ No need for a complete overhaul, Squid adapts to your existing warehouse operations effortlessly. This isn’t just tech for tech’s sake, It’s about transforming your warehouse into a faster, safer, and more efficient space. 𝗔𝗿𝗲 𝘆𝗼𝘂 𝗿𝗲𝗮𝗱𝘆 𝘁𝗼 𝗲𝗺𝗯𝗿𝗮𝗰𝗲 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝘄𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 ❓ 𝗦𝗵𝗮𝗿𝗲 𝘆𝗼𝘂𝗿 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝘀.  #robotics #technology #engineering #warehouse #logistics #supplychain ♻️ If you found this insightful, don’t forget to share it with your network.

  • DeepDrive is bringing its Dual Rotor motor technology into robotic joint modules with the launch of DeepDrive Robotics. Read more in our latest article:https://lnkd.in/g6hHncEu

    Today, we are taking the next big step for DeepDrive: the official launch of DeepDrive Robotics. We are finally able to talk about what we've worked on in the background over the last year: applying the DeepDrive Dual Rotor technology to robotic joint modules - the most torque-dense and energy-efficient actuator at high volume and low cost. This is the consistent next step for us: We live in the age of electrification - electrifying everything from cars, drones to human(oid)s. All these applications need electric motors. And moving away from today's state-of-the-art technology, we developed "motor 2.0": Highest efficiency and torque density at lowest cost in all mobile applications. We cracked the automotive market and are scaling high volume production in the hundreds of thousands of units. Our automotive DNA drives our quality, cost and manufacturing standards - while staying a highly innovative and flexible scale-up. Now we apply this same mindset, discipline and groundbreaking tech to the next field. We've started working with some of the most prominent robotics players in the world and are overwhelmed by the feedback. I am incredibly excited for this next stage of DeepDrive. CC: Vincent Felix Stefan Alexander Peter Jens Andreas Marcus Benjamin Peter Jörg Markus

  • SK GODELIUS is applying robotic technology to underground inspections, combining tracked mobility with adaptable sensing for challenging industrial environments. Read more in our latest article: https://lnkd.in/gQw3MtN4

    View organization page for SK GODELIUS

    10,830 followers

    What if the first set of eyes on your equipment didn’t have to be human? SK Godelius uses robotic inspection technology to bring visibility into areas where traditional inspections can be difficult, repetitive or potentially hazardous. Equipped with cameras and inspection technology, robotic platforms can move through industrial environments while operators monitor conditions remotely and collect valuable information about critical assets. The result? Better visibility into your operation while reducing unnecessary personnel exposure. Inspect remotely. Identify issues earlier. Put people where their expertise matters most.

  • Rivian and Redwood Materials are expanding their partnership to give EV batteries a longer life through stationary energy storage and critical-material recovery. Read more in our latest article: https://lnkd.in/gmcydPQ5

    View organization page for Rivian

    795,361 followers

    A massive energy unlock.  We’re expanding our partnership with Redwood Materials to collaborate across the full lifecycle of Rivian battery packs. A battery pack that’s no longer right for a high-performance EV doesn’t have to be done. It can be repurposed into stationary energy storage to support grid reliability and store clean energy. And when it truly reaches the end of the road, it can be recycled. Battery scrap and end-of-life packs go back through the process, recovering over 95% of critical minerals—including lithium, nickel, cobalt, and copper—for a domestic supply chain. Building on our initial energy storage deployment at our manufacturing plant in Normal, Illinois, we’re proving how a fully circular battery ecosystem can power a cleaner, more resilient future. Read more on how retired EV batteries can make the energy grid more reliable while lowering costs for everyone: rivn.co/Battery-Lifecycle #Rivian #AdventurousForever

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  • John Deere’s autonomous tillage technology shows why reliable perception—not just automated steering—is essential for machines working in unpredictable field conditions. Read more in our latest article: https://lnkd.in/gTdkGYqa

    Deere is selling autonomous tillage as an extra pair of hands! 🚜 Field autonomy never struggled with driving a straight line. AutoTrac solved that years ago. It actuallt struggled with trusting what the cameras saw, on a machine that vibrates all day, flexes under draft load and swings tens of degrees between a cold morning and a dusty afternoon. John Deere says that exact trio, vibration, mechanical tolerance and temperature variation, is what capped the first-generation system. A camera that has drifted reports the wrong depth, and the tractor either stops for nothing or fails to stop for something. The second-generation perception system goes at that directly: → 16 cameras, 360° around the tractor and the tillage tool → coverage deliberately overlapped so cameras cross-check each other and recalibrate in real time, in the field → NVIDIA Orin GPUs running inference onboard → detection range up from 16 m to 24 m, which Deere says buys 40% more speed and implements twice as wide Calibration confidence converts into ground speed. Why? Because it sees further, trusts it, and drives faster. This ships as a retrofit. You can see it also in the video with phantom driver! ~~  ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com

  • What does it take to automate a sandwich? Bizerba, FANUC Europe, KILIVATIONS, Schmalz, and ViscoTec combine robotics, flexible gripping, precision dosing, and slicing technology to demonstrate a connected approach to fresh-food preparation. Read more in our latest article:https://lnkd.in/g4vj7XbK

    A robot making fresh sandwiches at the checkout counter. In a supermarket. Right in front of you. Bizerba and FANUC Europe built this. Slicing, spreading sauces, assembling, packaging. All without human hands touching the food. The business case is simple: fresh food counters are one of the hardest areas to staff and one of the most hygiene-sensitive. Labor-intensive, low margin, high turnover. This doesn't just automate the task, it improves it. The technical challenge here is real: soft, deformable ingredients, precise portion control, contact-free handling, all in an open retail environment. This is not a warehouse. This is a supermarket checkout. And it works. Physical AI is automating everything we thought needed human hands.

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