Edge AI shifts from slide-deck fantasy to tactical reality. Rifle companies now carry 1,800 TOPS of computing power in two Pelican cases, enabling sense-decide-act cycles in 300 milliseconds even when every communication link is jammed or burning. Dell's new Pro Max systems with GB10 Grace-Blackwell accelerators fundamentally rewrite the tactical playbook. A 15-kilogram package now delivers what previously required containerized server farms, running 120-billion parameter models on vehicle power or 8-hour batteries without throttling. The operational specifications that matter include 1 petaFLOP of AI performance at 250W total system draw, and 128 GB of coherent unified LPDDR5x memory, keeping multiple models resident. NVIDIA Confidential Computing with FIPS 140-3 options for TS/SCI weights, while liquid-metal and vapor-chamber cooling enable 60°C ambient operation. This translates to AI firepower that survives Iraqi summers in a JLTV. Ukraine validates these capabilities daily. Pro Max Mini systems control 80 drones from a single Pelican case, using 120B coordination models that retask swarms, handle attrition, and adapt to jamming in real time. Marine Littoral Regiments are running models four times larger than 2024 systems at half the power consumption. The impact on engagement timelines is dramatic. Mast cameras stream 8K video at 120–180+ fps on 4K/8K feeds for instant threat detection. The system generates threat pop-up boxes, weapon slew commands, and shoot/don't shoot recommendations at 95% confidence levels. Human reaction time averages 4-6 seconds. AI-assisted response collapses to 400 milliseconds. Three fundamental shifts emerge from this edge computing revolution. Speed beats latency; 300ms local processing outperforms 3-second satellite round-trips. Resilience beats connectivity; systems function when everything else is offline. Integration beats isolation. One system handles every AI mission. For contractors: edge AI has moved from PowerPoint promises to operational reality. The question isn't whether to integrate AI at the tactical edge, but how fast you can deliver it. #DellProMax #EdgeAI #Defense
Edge Computing Applications
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AR / XR / Spatial Computing • Professor • Behavioral Science & Technology Management
15,554 followers[🚨] XR Marketing – only for fancy B2C brands? Not at all! New Paper on XR in B2B Excited to share that our paper "ð™°ðšžðšðš–ðšŽðš—ðšðšŽðš ðšŠðš—ðš ðš…ðš’ðš›ðšðšžðšŠðš• ðšðšŽðšŠðš•ðš’ðšðš¢ ðš’ðš— ð™¼ðšŠðš—ðšŠðšðš’ðš—ðš ð™±ðŸ¸ð™± ð™²ðšžðšœðšðš˜ðš–ðšŽðš› ð™´ðš¡ðš™ðšŽðš›ðš’ðšŽðš—ðšŒðšŽðšœ" has been accepted & appeared in "Industrial Marketing Management". Surprising: Although the B2B sectors has been using XR in marketing related activities for years, academics have widely ignored it. We took the chance, spoke with industry professionals and organized current practices. Download the article (open access / for free) here: https://lnkd.in/dtrRzhwJ ...find some key findings here: Â ðŸ› ï¸ HOW DO B2B BRANDS USE XR? FOUR CENTRAL USE CASES Product/Project Visualization Event-Based Engagement Remote Support Employee Training  💡 XR'S ROLE IN CUSTOMER EXPERIENCES enhancing their core offers (e.g., product visualization) building related experiences (e.g. previews or simulations) adding diverted experiences (e.g. by offering engaging content, such as branded VR Games)  🚀 WHAT BENEFITS DO B2B-BRANDS WANT TO ACHIEVE? Branding (e.g., creating an innovative brand image) Building better relationships Transactions (e.g., in sales) Cost Savings (e.g., by reducing expensive prototypes) Sustainability (e.g., by reducing travel)  ♾ï¸SIMPLY A FACNY SALES TOOL? NOT AT ALL Our study shows AR/VR's potential to add value throughout the entire B2B customer journey AR and VR are often managed by the same people (which makes sense) but should be clearly separated in how they are used   --- #AR #VR #B2BMarketing #SpatialComputing #CustomerExperience  Reference: Désirée Wieland, Prof. Dr. Bjoern Ivens, Elizaveta R. Kutschma & Philipp A. Rauschnabel (2024): Augmented and Virtual Reality in Managing B2B Customer Experiences, Industrial Marketing Management, forthcoming Some people we cited or who might like it: Peter Verhoef, Ko De Ruyter, Dr. Eric Boyd, Bernadett Koles, Thorsten Hennig-Thurau, Carlos Flavian, Sergio Barta Arroyos, Carlos Orus Sanclemente, Tim Hilken, Dominik Mahr, Maik Hammerschmidt, Sebastian Hohenberg, Jonas Heller, Robin-Christopher Ruhnau, Nilusha Aliman, Dr. Harish Kumar, VAHIDEH ARGHASHI. Have a great weekend!
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Applied AI Trailblazer | Defense Tech Disruptor | AI Computing SME | MBA | Ex-IBM, Ex-NVIDIA, Ex-MITRE, Ex-US Government, Ex-Octo
7,610 followersI'm proud of the work our Octo-oLabs edge AI team has been putting in quietly building Semantic Edge, our LLM solution tailored to the needs of users in denied, degraded, intermittent, or limited comms environments. No high-speed connectivity. No cloud infrastructure. No GPU cluster. No problem. United States Department of Defense, U.S. Department of Homeland Security, Headquarters, US Special Operations Command Semantic Edge Features 1. Stateless and Persistent Search History: Facilitates rapid familiarization with indexes and in-depth topic investigation through easy history navigation. 2. Speed: Achieves sub-100ms search responses, extending to hundreds of millions of passages, crucial for maintaining focus and performance. 3. Search Quality: Utilizes advanced, research-backed token-level indexing, with flexibility for future feature integration. 4. Multiple-Indexing: Allows for quick creation of multiple indexes, enhancing document management efficiency. 5. Multi-Turn Chat with History: Ensures data privacy with fully on-device operations, supports comprehensive problem-solving, and facilitates contextual understanding across different indexes. 6. Editable Chat History and Templating: Offers user-driven message editing for correcting or guiding chatbot interactions, enhancing task-specific performance. 7. Search & Answer: Adopts a results-first approach, prioritizing immediate display of search results while enhancing chatbot interactions to avoid misinterpretations. 8. Extractive Question Answering: Supports efficient query processing with instant answers, integrates with Search & Answer for enhanced accuracy, and offers API access for broader application. 9. Programmatic Search via API: Enables sophisticated document analysis and dataset generation for specialized tasks, with support for batch processing for increased throughput. So what’s next on our roadmap? We’ve got dozens of features planned, including Watsonx.governance integration for LLMOps CXEdge CIP/COP Integration Multimodal model Integration Compiling custom workflows Model finetuning Zachariah Marrero PhD | Josh Fowler | John Burrows | Ted Hallum | Joseph Amato | Aden O'Donoghue | Cesar Tavares | Derek Schwenkmeyer | Andrew Tran | IBM Consulting | Octo, an IBM Company
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The European Blockchain Association e.V. has formally submitted our reply to the European Data Protection Board’s public consultation on blockchain and GDPR. Together with my colleague Eugenio Reggianini, we provided a granular and context specific approach, using the EVM environment as a reference, given both its size, network development, community-based engagement and protocol evolution. 🧬 From monolithic to modular Public permissionless blockchains are no longer just modular. Raw personal data is being pushed to the edges where users and providers can maintain control. This is shifting architecture development towards modularity at varying levels of the stack. Combined with off-chain storage and metadata erasure, embedding #ZKPs, encrypted execution (FHE/TEEs), and shard-based data availability sampling (PeerDAS) into the #protocol, its possible to ensure that only a well-defined set of actors ever ‘control’ personal data. Within modular frameworks, the rest of the network (including #validators relays, archival nodes essentially) becomes a neutral verifier of encrypted or anonymous commitments. ✅ Execution layer → encrypted, ZK-proof, or pseudonymous #transaction processing ✅ Consensus layer → blind verification of proofs, not raw #data; ✅ Data availability layer → fragmented, anonymized data #custody with strict time-bound retention. Such design is fully aligned with #GDPR principles of data minimization and privacy by design. Importantly, it provides a pathway where GDPR obligations remain actionable and users can enforce data erasure off-chain (supported by metadata erasure patterns), controllers can prove #compliance, and the chain preserves #decentralization and integrity without propagating personal data unnecessarily. 🔎 Our Policy recommendations at a glance 🔹 Formalize roles in modular networks for block builders, proposers, attestors etc. 🔹 Adopt metadata erasure standards to enable functional erasure even in immutable systems. 🔹 Implement privacy-enhancing tech as default. zk-SNARK-based execution, encrypted rollups, and PeerDAS sampling should be core architecture. 🔹 Encourage off-chain governance via industry codes of conduct and community standards to supplement protocol-level guarantees. 🔹 Empower users at the edges. Application and wallet developers should be equipped with tools for consent management, erasure signaling, and selective disclosure, putting GDPR rights directly in users’ hands. Dr. Michael Gebert Dr. Clara Guerra Michael Reuter Rebecca Lynn Johnson Robert Kopitsch Tommaso Astazi Adriana Torres Vergara Marina Markezic Vyara Savova, LL.M., Ph.D.—to—be Mark Foster Arno Laeven Roman Beck Dr. Hagen Weiss Maha Al-Saadi
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Partner, IBM Consulting | Driving Defence & National Security Digital Transformation | AI • Hybrid Cloud • Cybersecurity
10,108 followers AI at the Tactical Edge—Smarter Logistics in Disconnected, Contested Environments In future conflicts, logistics will no longer be a rear-echelon function. Modern battlefields demand real-time logistics intelligence, even in disconnected, high-threat environments. That’s where #AI at the tactical #edge comes in—bringing intelligent decision-making tools directly to the frontline. Tactical edge AI refers to deploying models and analytics on lightweight, portable systems like rugged tablets, vehicles, or drones—without relying on constant connectivity to cloud infrastructure. This enables units to make logistics decisions in the field, in real time. Take Finland, which has integrated edge AI into mobile command units during Arctic training exercises. These systems track fuel consumption, ammunition usage, and environmental wear on vehicles—alerting commanders before supply issues arise, even in extreme weather and without network access. In India, the Armed Forces Medical Services are exploring edge-AI-based triage and supply tracking systems for use in forward medical posts during high-altitude deployments. The goal? Better sustainment planning for medevac and re-supply, with minimal human input. Even NATO’s Federated Mission Networking initiative includes edge AI tools to ensure logistics information can be shared across multinational forces operating in bandwidth-constrained zones. The tactical edge is often where logistics becomes the most fragile—and where AI can have the greatest operational impact. Key Takeaways: 1. Edge AI empowers frontline units with predictive logistics tools, even when cut off from central command or cloud access. 2. Militaries are applying tactical AI to enhance battlefield logistics in extreme and remote environments. 3. Edge-deployed AI increases resilience, speed, and autonomy, enabling smarter sustainment under fire. #defence #defense #logistics #AI Aneeta Bains Adam McCann Dale Kehler Steve Harding Ian Gallaway Chris MacIntosh Melanie Gilbert Hille Viita Chris Chabassol David Prior Caitlin Mouland
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Engineering consent infrastructure that operates at microsecond precision while maintaining global compliance requires advanced technical architecture. For many of our clients at Ethyca, the technical requirements they asked us to solve seemed extreme: Process 300 million consent decisions per hour ↓ With sub-15-millisecond response times ↓ With complete end-to-end user preference enforcement ↓ And zero impact on business-critical revenue systems The standard approaches couldn't scale, because they introduced unacceptable latency, batch synchronization lost real-time accuracy and manual configurations could never adapt to traffic patterns. Our technical solution used distributed architecture carefully orchestrated for speed: • Edge-deployed consent verification eliminates round-trip latency by processing decisions closest to users. • Server-side component rendering to reduce latency for UI components that require display for the user. • In-memory preference caching with intelligent invalidation ensures instant access to current user choices without database dependencies. • Asynchronous preference propagation maintains consistency across downstream and distributed systems (including third-party vendors) without interrupting primary workflows. • Real-time monitoring and auto-scaling maintains performance during traffic spikes while optimizing resource utilization. The architecture maintains legal compliance while operating at internet-scale performance standards. User preferences propagate through the complex data ecosystems so central to large-scale enterprise, without introducing system dependencies or performance degradation. Engineering teams can implement comprehensive privacy controls without compromising the technical performance their business depends on. How does your current consent architecture handle peak traffic while maintaining compliance accuracy?
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Innovation Leader | Business Development & Sales Strategist | Driving Growth with High-Tech Solutions (AI, XR, Digital Transformation)
8,095 followers🱠ð—¨ð˜€ð—² ð—–ð—®ð˜€ð—²ð˜€ ð˜„ð—¶ð˜ð—µ ð—œð—ºð—ºð—²ð—¿ð˜€ð—¶ð˜ƒð—² ð—§ð—²ð—°ð—µ ð˜„ð—¶ð˜ð—µ ð—½ð—¿ð—¼ð˜ƒð—²ð—» ð˜€ð—µð—¼ð—¿ð˜ ð˜ð—²ð—¿ð—º ð—¥ð—¢ð—œ ð—³ð—¼ð—¿ ð—œð—»ð—±ð˜‚ð˜€ð˜ð—¿ð˜† --  ð—¨ð˜€ð—¶ð—»ð—´ ð—©ð—¥/ð—”ð—¥ ð—³ð—¼ð—¿ ð—¿ð—²ð—ºð—¼ð˜ð—² ð—®ð˜€ð˜€ð—¶ð˜€ð˜ð—®ð—»ð—°ð—² -- A factory is like one single machine with many interconnected parts. When machinery breaks down, there’s no time to lose. This is why VR and AR are being used for remote assistance. Using extended reality, a service engineer can instantly ‘pay a visit’, guiding on-site crew through troubleshooting and easy fixes. --  ð—¨ð˜€ð—¶ð—»ð—´ ð—±ð—¶ð—´ð—¶ð˜ð—®ð—¹ ð˜ð˜„ð—¶ð—»ð˜€ ð—®ð—»ð—± ð—½ð—¿ð—¼ð—¼ð—³-ð—¼ð—³-ð—°ð—¼ð—»ð—°ð—²ð—½ð˜ ð˜ƒð—¶ð—¿ð˜ð˜‚ð—®ð—¹ ð—½ð—¿ð—¼ð˜ð—¼ð˜ð˜†ð—½ð—¶ð—»ð—´  -- Product development can be a long and costly process. The optimization phase often takes many iterations and adjustments before a fully tested design can be deployed. By using AR and VR, virtual prototypes can be created and tested using a virtual digital twin. --  ð—§ð—¿ð—®ð—¶ð—»ð—¶ð—»ð—´ ð—»ð—²ð˜„ ð—²ð—ºð—½ð—¹ð—¼ð˜†ð—²ð—²ð˜€ ð—³ð—®ð˜€ð˜ð—²ð—¿, ð˜„ð—¶ð˜ð—µ ð˜€ð˜ð—®ð—»ð—±ð—®ð—¿ð—±ð—¶ð˜‡ð—²ð—± ð˜ƒð—¶ð—¿ð˜ð˜‚ð—®ð—¹ ð˜ð—¿ð—®ð—¶ð—»ð—¶ð—»ð—´ -- Whether training on safety, or instructing engineers on practical skills, VR and AR are fantastic tools for rapid immersive learning. Manufacturers are using extended reality to accelerate the training of employees, without putting real equipment or people at risk. It also frees training programs from the limitations of physical resources. Employees can be given thorough safety training that highlights hazards in the factory, or more in-depth training on specific skills. --  ð—”ð—°ð—°ð—²ð—¹ð—²ð—¿ð—®ð˜ð—² ð˜€ð˜‚ð—°ð—°ð—²ð˜€ð˜€ ð˜„ð—¶ð˜ð—µ ð˜ƒð—¶ð—¿ð˜ð˜‚ð—®ð—¹ ð—½ð—¿ð—¼ð—±ð˜‚ð—°ð˜ ð—±ð—²ð˜ƒð—²ð—¹ð—¼ð—½ð—ºð—²ð—»ð˜ ð—®ð—»ð—± ð—°ð—¼ð—¹ð—¹ð—®ð—¯ð—¼ð—¿ð—®ð˜ð—¶ð—¼ð—»  -- Working with different stakeholders to define design parameters can be an arduous process, especially for the finer points like finishes and detailing. Are you all on the same page? With extended reality, manufacturers can collaborate easily with stakeholders and cross-functional teams around the world. Everyone can agree faster, because they can all see the different design options right in front of them in VR or AR. This makes your business more customer-centric, and reduces the material cost liability for OEM variations. Specifications are agreed much earlier, with less hesitation. It’s a win-win. --  ð—©ð—¶ð˜€ð˜‚ð—®ð—¹ð—¶ð˜‡ð—¶ð—»ð—´ ð—µð—²ð—®ð˜ƒð˜† ð—ºð—®ð—°ð—µð—¶ð—»ð—²ð—¿ð˜† ð—¶ð—» ð˜ð—µð—² ð˜€ð—²ð˜ð˜ð—¶ð—»ð—´ -- Upgrading your factory floor? With AR, a person can stand in the workspace and see exactly how the new machinery will fit in. You can easily rearrange elements and reorganize how the layout works. This makes it easier to optimize your factory floor, and you can improve safety too. Potential pinch points and other hazards can be identified long before the machinery is installed. As a bonus, before the new machinery arrives, your staff can immediately start training in VR or AR, using a virtual version of the new machinery, accompanied by a Holopresenter who explains how to operate it safely. Contact Fectar for more info
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Agentic AI | Healthcare | Emerging Technologies | Strategic Advisor & Innovator & Patent Attorney
22,420 followers🧠FDA Augmented Reality & Virtual Reality Medical Devices – Q2 2025 Trends 📊 The FDA’s Q2 2025 data on cleared Augmented Reality (AR) and Virtual Reality (VR) medical devices reveals accelerating clinical adoption across multiple specialties. Our analysis uncovers three key trends: 🔹 Orthopedic and Spine Navigation Leads the Pack AR/VR systems are being integrated into surgical workflows to guide alignment, placement, and anatomical targeting—particularly in joint replacement, spine correction, and trauma fixation procedures. 🔹 Surgical Planning + 3D Visualization on the Rise From cranial navigation to pre-operative simulation, AR/VR platforms are helping surgeons "see before they cut." Clinical domains like ENT, neurology, and orthopedics are especially active. 🔹 Rehabilitation & Behavioral Health Gaining Ground VR-powered rehab tools are being adopted for post-stroke motor recovery, gait training, and pain distraction. Emerging behavioral health applications include exposure therapy and cognitive conditioning. 🧩 Use Case Breakdown Highlights: 🦴 Orthopedic / Arthroplasty 🧠Neurology / Neurosurgery ðŸ‘ï¸ Ophthalmology Visualization 🩺 Radiology Interpretation 🚶 Rehab / PT / Gait Training ðŸ—£ï¸ Speech & Cognitive Therapy 🔠Most AR/VR devices follow the 510(k) pathway, reflecting evolutionary innovation and expanding real-world use across surgical, diagnostic, and therapeutic domains. list of companies with FDA-approved Augmented Reality (AR) or Virtual Reality (VR) medical devices as of Q2 2025: Abys by OneOrtho apoQlar medical AppliedVR Augmedics Augmedit B.V. Avatar Medical Barron Associates, Inc. Brainlab AG Ceevra, Inc. Clarus Viewer Corporation Clear Guide Medical CognifiSense, Inc. Comerge AG EchoPixel, Inc. Hoth Intelligence Inc. Intradys ImmersiveTouch, Inc. Insight Medical Systems Inc. Intuitive Surgical Devices Luminopia, Inc. Materialise NV MedApp S.A. Medacta International S.A. MediView XR, Inc. Medical Templates AG Medivis, Inc. MindMaze SA Novarad OculoMotor Technologies OnPoint Surgical, Inc. Penumbra, Inc. Pixee Medical PolarisAR Inc. PrecisionOS Technology Inc. sentiar, Inc. Sira Medical, Inc. Smileyscope Holding Inc. Specto Medical AG Surglasses - Taiwan Main Orthopaedic Biotechnology Co., Ltd. Xironetic, LLC 📎 Source:https://lnkd.in/dBY_a4u3 #DigitalHealth #AR #VR #XR #MedTech #FDA #DigitalTherapeutics #XRinHealthcare #Compliance
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Founder & CEO @ SimplAI | ex-CTO Pickrr| ex-CTPO Emiza | Technology Enthusiast | Angel Investor | Young CTO Of the Year (30-40) I ex-OYO | ex-Lenskart | ex-Cisco | CTO of the Year 2023 - Indian Achiver's Award
20,275 followersMost “AI†systems still phone the cloud for answers—and by the time the response comes back, the conveyor belt has already moved on. Edge-native agents keep the brains right beside the data, so action happens instantly and privately. Here’s why that matters (and how I’m seeing it play out on the ground). Why the move to the edge? 1. Speed you can feel Industrial lines need sub-10 ms reactions to avoid faults; dragging every frame to a data center rarely beats 100 ms. Camera modules running trimmed-down models are already hitting that bar on-device. 2. Safer shop floors A chemical manufacturer cut near-miss incidents by 48 % after plugging vision agents directly into existing CCTV. No new hardware—just smarter eyes on the line. 3. Compliance by design When inference stays on-site, GDPR headaches melt away because sensitive data never leaves the premises. 4. Operators become conductors Edge orchestration tools let frontline staff deploy, watch, and roll back models without writing a line of code—turning “machine operators†into “AI coordinators.†5. A new control-plane layer Analysts now talk about Model/Agent Control Planes to manage fleets of tiny brains scattered across sites—permissions, updates, drift detection, the works. 6. Strategy, not theory McKinsey calls autonomous systems (physical robots + digital agents) one of 2025’s top tech shifts, moving from pilots to production. AMD’s CTO echoes it: by 2030 most inference will happen on phones, laptops, and factory PLCs—not the cloud. My takeaway: If a decision can’t be made locally, it’s already late. Question for you: If latency disappeared and data stayed on-site, what’s the first task you’d hand to an edge agent? Drop a thought below—I’m collecting real-world ideas.