Ajay Arora

Roksan quietly made a big move with these new Caspian 4G separates. For anyone who’s outgrown an integrated amp but doesn’t want to abandon modern streaming, this combo makes a lot of sense. BluOS, proper phono support, fully balanced architecture, and a power amp that can scale all the way to serious monoblock output. It’s refreshing to see a brand focus on doing the fundamentals right instead of chasing spec-sheet gimmicks. Definitely worth paying attention to if you’re building a long-term system. #Audiophile #HiFi #Roksan #TwoChannel #HighEndAudio

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🔹 Insight 1: Mission-Critical Video ≠ Entertainment Video 🔍 Mission-critical video isn’t about cinematic quality — it’s about enabling decisions when seconds and kilobits count. In entertainment, success is defined by high resolution, smooth playback, and visual richness. But for mission-critical tasks like search and rescue, surveillance, or remote inspection, the goal is clarity of purpose — not pixel perfection. What matters is: Did the right person see the right thing in time to act? 📡 These operations are often conducted under extreme constraints: Limited bandwidth (especially over satellite or long-range radio) Harsh and unpredictable network conditions Edge devices like CCTV cameras or drones that may not be actively operated or zoomed 📈 Over the years, some or many of us have worked with L-band satellite systems, where links offered only a few hundred kilobits per second. Now, with Ka-band LEO constellations, the available bandwidth is increasing. But so are the demands. Camera resolutions have jumped from 480p, or 720p to Full HD, 4K, or even 8K. So while the pipe is growing, the payload is perhaps growing even faster. Without control and prioritization, higher rates and higher resolution simply means higher cost — and more risk of missing the mission-critical detail. 🧠 This is why blind adaptivity isn’t enough. You don’t want an algorithm deciding what matters — you want a person or a system that understands the mission to be in control: Adjust the bitrate and frame rate manually or by logic — not by passive feedback Define Regions of Interest (ROI) where action is likely to occur, especially when the edge device can’t zoom or refocus Focus bandwidth and computation on the relevant content — and ignore the rest 🎛️ Our approach emphasizes precision over abundance. Starting from a constrained environment helps force better design: Don’t stream everything and trim later — stream only what matters, the first time. ⚠️ Even the camera interface and transfer path can introduce latency. How the camera is configured and how it interfaces with the encoder or computer can have a real impact on delay — especially in systems not designed with real-time streaming in mind. 🛰️ ASMIRA enables video streaming at 50–200 kbps with region-focused precision. 📷 ASIGN allows users to interactively pull what they need — controlling what is sent, when, and how much. 🎯 Takeaway: Mission-critical video should be lean, focused, and purposeful. Technology has evolved, but so has video complexity. The future isn’t just higher bitrates — it’s smarter decisions about what to send. #MissionCriticalVideo #BandwidthEfficiency #VisualIntelligence #AnsuR #ASMIRA #ASIGN #Satcom #ISR #KaBand #LBand #LEO #EdgeVideo #SituationalAwareness #ControlledStreaming #EmergencyTech #VideoCompression #4KVideo #8KVideo #SmartStreaming

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Another disguised AI miss “Broadcom’s Earnings: Singing ‘Deck the Halls’ While The Data Sings 'Not Like AI Boom At All' “…Broadcom is now one of the most systemically important companies in global markets. And beneath the festive cheer of the AI narrative, the valuations tell a much colder story….. It’s the financial equivalent of watching customers flood into a store, fill their carts, walk up to the checkout counter… and then leave without paying. The aisles look busy, the shelves look empty, the activity looks real—until you open the register and realize it barely moved. That’s Broadcom this quarter. Revenue is rising, receivables are ballooning, and cash flow is falling behind both—clear evidence that the company is booking demand, not monetizing it. This isn’t what the start of an AI supercycle looks like. It’s what the end of one often feels like: noise, motion, and excitement… with very little money actually coming in….” Coastal Journal https://lnkd.in/ehYwHSHe

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As the D2D market heats up, GEO incumbents are leveraging spectrum, scale, and sovereign trust to carve out a unique role as infrastructure providers. This model may prove more resilient, more investable, and ultimately more scalable than the high-burn, vertically integrated paths of their LEO challengers. The Direct-to-Device (D2D) race is rapidly evolving from a technical ambition to a strategic battleground. LEO entrants such as Starlink Direct-to-Cell, AST SpaceMobile, Lynk Global and Skylo are investing aggressively to seize first-mover advantage. Yet amid this momentum, the incumbent GEO operators (Viasat and Space42) are charting a more deliberate, infrastructure-grade strategy that may ultimately prove more defensible. Through the launch of #Equatys, these operators are transforming decades of operational expertise and regulatory capital into a differentiated D2D platform. With over 100 MHz of harmonized MSS spectrum spanning 160+ jurisdictions, Equatys is positioned to bypass one of the largest barriers facing new entrants: global spectrum access. Moreover, by anchoring their model in 3GPP NTN standards and a neutral-host architecture, Viasat and Space42 are not just competing for market share — they are redefining how D2D capacity can be monetized at scale.  This “space tower company” approach unlocks three critical advantages: 1. Regulatory alignment and sovereignty compliance — appealing to governments and regulators. 2. Capital efficiency — shared infrastructure reduces duplication and burn. 3. Ecosystem integration — enabling MNOs and OEMs to participate without surrendering control to vertically integrated disruptors. GEO incumbents are leveraging spectrum, scale, and sovereign trust to carve out a unique role as infrastructure providers. This model may prove more resilient, more investable, and ultimately more scalable than the high-burn, vertically integrated paths of their LEO challengers. The D2D revolution is just beginning—who will define the future of global connectivity? Exciting times ahead as the race between LEO disruptors and GEO incumbents unfolds. 🚀📶 #space42 #equatys #viasat

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One of our robot characters, Aria, spent 12 days in NYC. During that time she: ✔️ Worked as a product specialist for Ericsson at Verizon’s head office. ✔️ Acted as a store host for the opening of a new store in Times Square. ✔️ Autonomously interacted with pedestrians in Times Square in several languages. ✔️ Conducted a solo interview with CNN. ✔️ Met with investors at GF Capital’s office. Our robots don’t breakdance or fold laundry. They have superior use cases and real-world customer service applications that unscripted. Our #AI #robots think and act autonomously. Realbotix (TSXV: XBOT | OTCQB: XBOTF | FSE: 76M0.F)

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Jensen Huang’s hotly anticipated CES 2026 keynote was less about faster chips and more a declaration that AI is moving from "chatting" to "acting." While the headline grabber is the new Vera Rubin platform from NVIDIA, a six-chip beast boasting a 5x performance leap over Blackwell, the real strategic pivot lies in Alpamayo. NVIDIA is seeking to solve the "long tail" problem in autonomous driving not by driving more miles, but by using chain-of-thought reasoning. So, what do the key announcements signal for the industry? 1. The Hardware: "Vera Rubin" is a Full-Stack play Huang unveiled the Vera Rubin platform, confirming it is in full production and shipping later this year. The Specs: It’s not just a GPU. It’s a six-chip supercomputer system that includes the Vera CPU (with 88 custom Olympus cores), the Rubin GPU (with HBM4 memory), and advanced networking silicon such as the NVLink 6 switch. To achieve its claimed 10x efficiency boost in generating AI "tokens," the chips utilise a proprietary data format known as NVFP4. This is a classic NVIDIA moat-building move: adoption of it’s hardware incentivises adoption of it’s specific data standards. 2. The Software: Alpamayo and "Reasoning" AVs Current self-driving tech is largely reactive. Alpamayo aims to be cognitive. Chain-of-thought: Instead of just detecting a pedestrian, the 10-billion-parameter model is designed to "reason" through the scenario (e.g., "The pedestrian is looking at their phone and might step out"). Explainability: Crucially, it is claimed that the system can explain its decision-making, a holy grail for regulators and safety certifiers. 3. The Deployment: Mercedes-Benz CLA.  Significantly, the technology is hitting the road in the Mercedes-Benz CLA. Launching in the US in Q1 2026, followed by Europe in Q2 and Asia later in the year. While officially a "Level 2+" system, Mercedes-Benz AG CEO Ola Kaellenius described the driving experience as feeling like the car is "on rails," handling point-to-point navigation through complex San Francisco traffic. NVIDIA appears to be aggressively moving to own the entire "Physical AI" stack. By combining the raw grunt of Rubin (to train the models) with the cognitive architecture of Alpamayo (to run the robots), it is positioning itself to be as dominant in robotics and AVs as it is in LLMs. Its competition isn't just about chip sales anymore; it's about the fundamental architecture of how machines move through the world. #CES2026 #AI #NVIDIA #JensenHuang #VeraRubin #MercedesBenz #AgenticAI

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Thank Dani Cherkassky Great piece on the architecture shift voice AI needs. The core thesis: cloud-centric voice systems fail in real-world conditions because they are too slow, too expensive to keep always-on, and deaf to spatial context. The solution is a hybrid architecture—fast, always-on edge processing (Spatial Hearing AI and Cognition AI) handling 80% of interactions locally, with cloud LLMs reserved for complex reasoning. But the Kahneman thesis runs deeper than the article suggests. System 1 and System 2 are not just useful metaphors—they reflect an actual biological sequence. Fast, intuitive processing (System 1) evolved first; slow, deliberate reasoning (System 2) was layered on top. The brain's architecture reflects this: spatial-acoustic processing happens in milliseconds at the brainstem and primary auditory cortex, long before language centers engage. Kardome is not just borrowing Kahneman as marketing. Their architecture is neurologically correct—it replicates the hierarchical, parallel, spatially-aware processing that makes human auditory cognition so robust. Here is the deeper point: hearing preceded language in human evolution, and spatial hearing preceded both. The mammalian auditory system evolved to detect predators and locate prey—survival functions that required sub-second latency and continuous environmental awareness. Language processing was layered on top of this infrastructure. Current voice AI inverts this evolutionary logic: it starts with language models and treats spatial audio as an afterthought. Kardome restores the natural hierarchy. 🙌 Danny Shapiro, Rory Sutherland

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🚀 * The Next Frontier in Live Streaming * Sub-5 second latency is no longer just a technical milestone - it’s now achievable even with one-to-one personalized ad insertion. For leaders in streaming, CDN, and video tech, this signals a shift: * Viewer experience: seamless live events * Monetization: personalized ads at scale * Infrastructure: tighter integration between ad logic and edge delivery * Caching at the edge: leveraging solutions like Varnish Enterprise can help maintain low latency and high throughput for repeated content, while still supporting dynamic, personalized streams. My take: Low latency alone isn’t enough. The future belongs to platforms that can deliver real-time, personalized, and monetized streaming experiences at scale, powered by smart edge caching and infrastructure intelligence. ❓❓❓Which part of this stack is hardest to optimize in real-time, personalized streams—ad decisioning, edge delivery, or caching strategies? Read more: https://lnkd.in/dk3gDNjX #Streaming #CDN #VideoTech #AI #Broadcast #Leadership #EdgeCaching

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From startups to enterprise-scale builders, the AI House community is shaping the next wave of breakthroughs in the Pacific Northwest. Their teams rely on fast, scalable, secure connectivity to train models, host live events, and support AI‑driven workloads. That’s where Lumen Technologies comes in.   With ultra‑low latency, on‑demand bandwidth, and security built in, Lumen is helping AI House and Seattle’s growing AI ecosystem push past traditional limits and build what’s next.⚡   📖 Read the full story to see how this partnership is unlocking new possibilities for innovators across the region: https://bit.ly/4jP7y6h   #PartnerProgram #SolvedWithLumen #TrustedNetwork

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