Gidsen
Technisch
Ollama and Strix Halo: Local AI Setup and Evaluation
A documentation-based guide to local setup, AMD acceleration, runtime choices and the evidence needed before an industrial rollout. No measured hardware results are claimed.
Beslisinstrumenten voor Physical AI
Bronnenbibliotheek
Veldnotities, evaluatiekaders en directiesjablonen om industriële AI-pilots om te zetten in producten die inzetbaar, beheerbaar en betrouwbaar zijn.
Start with your decision
Choose the question in front of you. Each path starts with three useful references; expand it for the full reading list.
Who will buy, and why?
Define the user, buyer, job and category before committing to a product direction or delivery model.
More in this path (2)
Which product and investment make sense?
Set the product boundary, platform choices and lifecycle economics before a technology commitment becomes hard to reverse.
- 01Hyperion Physical AI Product System
- 02Operated Product Decision Graph · HC-OPDG-001 v0.1.0 released
- 03Strategy Gate: Opportunity, Buyer & Economics
More in this path (8)
- 04Build vs Buy: Total Cost of Ownership
- 05Lifecycle Economics Stress Test
- 06Intralogistics Procurement Evidence
- 07Edge AI Vendor Evaluation Matrix
- 08Ollama and Strix Halo: Local AI Evaluation
- 09Deploying Mistral On-Prem for Manufacturing
- 10Mistral vs OpenAI vs Anthropic for Industrial AI
- 11Digital Twin ROI Playbook
What would make this ready to launch?
Build the evidence chain from a promising prototype through acceptance, release, recovery and field operation.
- 01Worked Product System Evidence Pack
- 02Worked Industrial AI Acceptance Pack
- 03Prototype-to-Product Decision Gate
More in this path (7)
Who will lead the portfolio and product team?
Clarify decision rights, portfolio cadence, leadership mode and the evidence needed for an accountable transition.
Brongebaseerde analyse
EU AI Act voor Physical AI
De toepasselijke datum hangt af van de classificatie van het systeem. Lees de actuele analyse en breng daarna het beoogde gebruik, de systeemgrenzen en verplichtingen in kaart voordat u een datum als deadline hanteert.
Alle Bronnen
22
Sjablonen
Strategie
Worked Product System Evidence Pack
Inspect a fictional cobot decision, evidence gaps and linked Product System exports. Modeled inputs and accountable roles remain distinct from recorded human approval.
Sjablonen
Strategie
Worked Industrial AI Acceptance Pack
Fictional worked example of an Industrial AI acceptance pack: unplanned-stop triage on one packaging line, with measures, costs and the decision.
Sjablonen
Strategie
Worked Commercial Product Decision
Fictional worked example of a commercial product decision: segment, price logic and channel for an AMR fleet, with its stop conditions.
Sjablonen
Strategie
Physical AI Lifecycle Economics Stress Test
Compare a fictional baseline with five declared stresses using the existing simulator. Inspect capital, support, recovery and payback assumptions; these are modeled scenarios, not forecasts.
Checklists
Strategie
Intralogistics Procurement Evidence Checklist
Sixteen evidence requests before a fleet commitment, with accountable roles, acceptance questions and hold conditions. Every request starts unassessed; no supplier score or approval is implied.
Gidsen
Strategie
Physical AI Product Management 2027: Research Protocol
The proposed study question, exploratory design, sample targets, consent boundaries and pre-launch gates. Recruitment has not started and no findings exist.
Gidsen
Technisch
Deploying Mistral On-Prem for Manufacturing — Sovereign, Air-Gapped AI
How manufacturers deploy Mistral AI on-premise and in air-gapped environments. Covers the Sovereign Model Ladder, Mistral Forge/Studio/Compute stack, use cases across aerospace, automotive, semiconductors, and energy, and EU AI Act compliance.
Gidsen
Technisch
Mistral vs OpenAI vs Anthropic for Industrial & Sovereign AI
Honest side-by-side comparison of Mistral, OpenAI GPT, and Anthropic Claude for industrial and sovereign AI workloads. Covers data residency, on-prem deployment, fine-tunability, cost at scale, capability ceiling, vendor lock-in, and EU AI Act fit — plus when frontier models genuinely win.
Gidsen
Technisch
Predictive Maintenance AI for Industrial Equipment: Condition Monitoring, RUL & ROI
How to build predictive maintenance for production equipment: the data foundation (vibration, thermal, and motor-current signatures over OPC-UA and time-series), modeling approaches (anomaly detection, remaining-useful-life, survival models), edge vs cloud inference, CMMS/SCADA integration, and how to quantify ROI (downtime avoided, MTBF). Framed against ISO 13374 condition monitoring and IEC 62443 OT security. Ties to the live CSV-maintenance demo on this site.
Gidsen
Normen
AI Visual Quality Inspection for Manufacturing: Computer-Vision Defect Detection
How to deploy computer vision quality inspection on the production line: surface defects, assembly/completeness, and weld inspection — sensor and lighting setup, dataset and annotation strategy, and edge deployment. Includes the honesty boundary: a vision model surfaces candidate indications mapped to a vocabulary like ISO 5817 weld imperfections — it does not assign a certified grade (that needs metrology and your WPS). Ties to the live plant-audit and defect demos on this site.
Gidsen
Technisch
Sim-to-Real for Industrial Robotics: Evidence Before Release
A product-decision guide to simulation assumptions, transfer tests, target hardware, policy authority, independent checks, recovery and field evidence. Compares simulator and policy choices without treating simulation performance as release proof.
Gidsen
Veiligheid
Edge AI Under Functional Safety: Deploying AI in ISO 26262 & IEC 62443 Systems
Deploying AI in safety-critical embedded systems: ISO 26262 ASIL levels, SOTIF (ISO 21448), IEC 61508 SIL, IEC 62443 OT cybersecurity, runtime assurance monitors, operational design domains, and the edge inference toolchain (ONNX/TensorRT).
Gidsen
Technisch
Digital Twin ROI Playbook: From OPC-UA to a Production Twin
A practical ROI framework for industrial digital-twin programmes: the data foundation (PLC → OPC-UA → time-series → twin), the five-rung maturity ladder, where AI enters (anomaly detection, predictive maintenance, process optimization), how to quantify ROI, and build-vs-buy guidance for manufacturing leaders.
Gidsen
Normen
AI for Aerospace & Defence-Adjacent Manufacturing: A Civil-First, Dual-Use Primer
How MRO operators, avionics suppliers, and UAV makers deploy AI for predictive maintenance, automated NDT, and documentation copilots — with a clear-eyed view of DO-178C / DO-254 / ARP4754A certification, EASA's learning-assurance roadmap, and the sovereign on-prem case. Civil-first; no defence contracts or clearances.
Gidsen
Normen
Auralink: A Physical AI Research Reference Architecture
A Hyperion-authored Physical AI research reference for EV-charging infrastructure, evaluated in simulation and bounded environments—not a live deployment or client-outcome claim.
Gidsen
Strategie
Physical AI Product Teardowns
Three shipped physical-AI product families read for the decisions behind them — EV charging reliability, Android Automotive inside a homologated vehicle, and video platforms at 100M+ scale. Public observation, not client case studies.
Gidsen
Strategie
The Prototype-to-Product Decision Gate
Five decisions that determine whether a Physical AI prototype becomes a product — degraded-mode ownership, variant count, field survival, the scale delta, and who signs the compliance case. Each gate carries the test that answers it and the failure it prevents.
Gidsen
Strategie
Physical AI Product Management: The Complete Guide
The operating reference for AI products that perceive, decide and act: strategy, discovery, productization, evidence, operating envelopes, safety, platforms, launch, field operations, metrics and scale.
Gidsen
Strategie
Physical AI Product Manager: Role Charter & Hiring Scorecard
A practical role definition for Physical AI product leaders: decision accountabilities, specialist boundaries, seniority ladder, hiring scorecard, interview loop, first-90-days plan and copyable role brief.
- Gratis met email
Sjablonen
Veiligheid
Safety-Case Evidence Template (ISO 26262 / DO-178C / IEC 61508)
A practitioner template for structuring an AI safety case: the Claims–Arguments–Evidence skeleton, a HARA input sheet, ASIL/DAL/SIL decomposition placeholders, and a V&V traceability matrix — mapped to ISO 26262, DO-178C and IEC 61508. It is a template and checklist; a notified/certification body assigns the actual rating, we engineer the evidence.
- Gratis met email
Sjablonen
Normen
Edge AI Vendor Evaluation Matrix
A vendor-neutral scoring matrix for evaluating edge-AI inference hardware and vendors: TOPS/W, P99 latency, ONNX/TensorRT-class format support, on-prem/sovereign deployment, toolchain maturity, functional-safety support, power/thermal envelope, and long-term support — with a weighted 1–5 rubric. Criteria and a scoring method, not a ranked vendor list.
Waar de bron stopt, begint de beslissing.
Vertel wat u wilt bereiken, wat de voortgang blokkeert en wanneer u hulp nodig hebt. Een paar zinnen volstaan.