Kalluri Siva Kumar Reddy

Dharmasthala Files: Can Technology Offer a Faster, More Efficient Solution Than Excavation? The alleged tragedy of 400-500 deaths is deeply unsettling. If true, it shakes our trust in safety—making us question how we travel and protect our loved ones. While the SIT’s excavation efforts are commendable, the process is painstakingly slow and may not cover all areas thoroughly. There’s a better way. Ground-Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) are proven geophysical methods used in archaeology, forensics, and utility detection. These technologies can: ✔ Scan large areas non-invasively ✔ Detect skeletal remains even 6-8 feet underground ✔ Generate high-resolution subsurface imaging for targeted excavation Why rely solely on manual digging when science can guide efforts more efficiently? Authorities should integrate these tools to accelerate investigations. What do you think? Should forensic tech play a bigger role in such cases? #DharmasthalaFiles #GPR

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Quantization in Large Language Models (LLMs) As LLMs scale, intelligence is no longer the bottleneck — memory, latency, and cost are. Quantization turns out to be one of the most powerful (and misunderstood) techniques enabling real-world deployment of large models. In this blog, I break down: • Why LLMs are surprisingly quantization-friendly • INT8 vs INT4 vs NF4 — what actually works in practice • How modern architectures absorb low-bit noise • Where quantization fails and how to design around it Quantization is no longer an optimization step — it’s foundational infrastructure for production LLM systems. Link: https://lnkd.in/gqGje75G #LLMs #AIEngineering #Quantization #MachineLearning #GenAI #MLOps

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🧩 How do these black-and-white squares make payments, open websites, or connect to Wi-Fi? We see QR codes everywhere, from scanning menus 🍽️ to paying bills 💸 to logging into Wi-Fi 📶. The little we are concerned about is how these tiny squares actually carry and store information. Because behind those random-looking boxes lies a brilliant mix of image processing, encoding algorithms, and error correction, all happening in milliseconds⚡ 🔍 What’s really inside a QR code? A QR (Quick Response) Code isn’t just an image; it’s a data matrix. Each small black or white square (called a module) represents a bit - 0 or 1; arranged in a pattern that encodes real information. That data can be: ✅ Text ✅ URLs ✅ Payment IDs ✅ Wi-Fi credentials ✅ Even small binary data or images Depending on its version, a single QR code can hold up to 4,296 alphanumeric characters! ⚙️ How it actually stores information 1️⃣ Encoding The original data (like a UPI link or website URL) is converted into binary using one of several encoding schemes — numeric, alphanumeric, byte, or Kanji (for Japanese text). 2️⃣ Error Correction (Reed–Solomon) QR codes use Reed–Solomon error correction, a mathematical algorithm that allows up to 30% of the code to be damaged (folds, scratches, glare) and still be readable. 3️⃣ Module Mapping The binary and error-correction bits are arranged in precise positions inside the grid, surrounded by key structures: ➡️ Finder patterns (those 3 large corner boxes — used for orientation) ➡️Alignment patterns (to correct distortion) ➡️Timing patterns (to identify rows/columns) 📱 What happens when you scan it? When your phone camera or Google Lens scans a QR code: 1️⃣ The app detects the finder patterns. 2️⃣ It adjusts for angle, rotation, and lighting using computer vision. 3️⃣ It samples each tiny module (black = 1, white = 0). 4️⃣ The Reed–Solomon algorithm fixes any corrupted data. 5️⃣ Finally, it decodes the binary data into a readable action, like opening a URL, triggering a payment, or connecting to Wi-Fi. …and remember, barcodes were developed much earlier and dominated retail and logistics. So how did QR codes evolve to outperform them and become the modern standard? 🔍 Why QR codes beat barcodes Traditional barcodes store data in one dimension, horizontally, using black-and-white lines. They require laser scanners that detect reflected light as the beam sweeps across. QR codes, on the other hand, are two-dimensional. They store data both horizontally and vertically, allowing hundreds of times more information and no need for lasers. Your smartphone camera (or any image sensor) captures the entire pattern at once. Then, built-in image processing algorithms decode the data instantly, making QR codes faster, cheaper, and far more versatile. #Technology #Engineering #Innovation #EmbeddedSystems #TechExplained #EngineeringDesign #TechFacts #DidYouKnow

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🏀 Masterstroke of Creating Chaos - Do H1B hurts Indians? 🏀 OPINION DIFFERS Recent reports indicate that a new U.S. presidential proclamation has significantly altered the H-1B visa landscape, particularly impacting Indian professionals who are the largest group of beneficiaries. Here's a summary of the key "threats" and the current situation: 🌀 The New H-1B Visa Fee The most significant change is the introduction of a steep, one-time fee of $100,000 for new H-1B visa petitions. This is a massive increase from the previous fees, which typically ranged from $2,000 to $5,000. 🌀 Who it affects: This fee applies to new H-1B applications, including those submitted in the next lottery round. It does not apply to current H-1B visa holders or visa renewals. 🌀 Who pays: The fee is to be paid by the sponsoring company, not the individual applicant. 🌀 Purpose: The stated goal of this policy is to limit the program to "very highly skilled" professionals and to prevent companies from using the visa to bring in lower-paid, entry-level workers who could be replaced by American citizens. 🌀 Immediate and Potential Impacts on Indians Reduced opportunities for new applicants: The exorbitant fee makes it economically unfeasible for many companies, especially smaller firms and startups, to hire new H-1B workers. This could drastically reduce the number of new visas issued and limit the career opportunities for Indian professionals seeking to work in the U.S. 🌀 Disruption and uncertainty: The sudden announcement of the policy caused panic and confusion among Indian H-1B visa holders who were outside the U.S. at the time. Despite clarifications that the fee does not apply to existing visa holders, many rushed to return to the U.S. to avoid any potential issues, leading to chaos at airports and a surge in flight ticket prices. 🌀 Impact on Indian IT companies: Indian IT firms are major users of the H-1B visa program. The new fee is expected to significantly increase their operational costs and may force them to rethink their business models, potentially leading to a shift toward more offshore projects. 🌀 Concerns for families: The change can cause significant disruption for families. Spouses and children on H-4 visas are tied to the H-1B visa holder's status, and the uncertainty surrounding the new rules has created a great deal of anxiety. 🌀 India's Response and Potential "Silver Linings" Some experts in India see a potential silver lining in the new policy, suggesting it could lead to a "reverse brain drain." The argument is that if skilled Indian professionals cannot easily go to the U.S., they will return to India, which could boost the domestic economy and accelerate the growth of Global Capability Centers (GCCs) and the Indian technology sector as a whole. Stephen D J A #h1b #visa #visaimpact #Wednesdaytopic

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🌍 Scaling AI Isn’t About GPUs Alone — Lessons from OCP Global Summit 2025 Day 1 of OCP made one point crystal clear: AI infrastructure scale is no longer a chip problem — it’s a system problem. Every keynote from hyperscalers and GPU vendors converged on the same idea: to sustain AI growth, we must co-architect power, cooling, and networking as a single open system. Some hard signals from the field 👇 ⚡ Power → HVDC shift Traditional AC distribution is breaking down. Operators are rolling out ±400–800 V DC designs (Google/Microsoft’s Mt. Diablo, Nvidia’s Kyber rack). These aren’t just about efficiency gains — they integrate ML-driven predictive telemetry to absorb transient spikes. The data center is evolving from a passive consumer to an active participant in the grid. 💧 Cooling → First-class subsystem Liquid cooling is no longer an afterthought. Rack-level liquid distribution with standardized interfaces is becoming the baseline design point. Cooling now scales in lockstep with compute + power lifecycles. 🌐 Networking → Spectrum-X pushes into scale-out + scale-across Nvidia is positioning Spectrum-X beyond intra-cluster fabrics — even into DCI (scale-across), a space long dominated by Broadcom. The technical intrigue: Nvidia suggests using distance-based load balancing instead of traditional deep-buffer switches for congestion absorption. If successful, this would mark a shift from buffer-heavy hardware → telemetry + algorithm-driven congestion control. 🤝 AMD joins ESUN AMD’s participation in Ethernet for Scale-Up Networking (ESUN) raises big questions. Can they support both UALink and ESUN simultaneously? Or will we see a dual-layer fabric: UALink inside GPU pods, ESUN between them? 🔑 My takeaway: Scaling AI now means re-architecting electrical, thermal, and network fabrics together. The winners won’t just have the fastest silicon — they’ll master system-level co-design across the stack. #OCP2025 #AIInfrastructure #DataCenters #HPC #LiquidCooling #HVDC #Ethernet #Networking #SpectrumX #ESUN #Broadcom #Nvidia #AMD #OpenCompute #AIInfrastructureDesign #ScaleOutAI

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Snowflake’s Snowpipe Streaming just got a major upgrade, and we’ve broken it all down for you. From blazing-fast ingestion speeds to seamless SDK integration and in-flight transformations, this is a game-changer for modern data pipelines. 🔍 Learn how your organization can move beyond batch processing and embrace true real-time analytics in this blog post by Chris Schneider here: https://lnkd.in/gpFFqY7f #DataEngineering #Snowflake #RealTimeAnalytics #evolvConsulting #SnowpipeStreaming

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Extending India’s Digital Horizon Nelco is joining forces with Eutelsat OneWeb to deliver Low Earth Orbit (LEO) satellite connectivity across the nation. This collaboration will unlock secure, high-speed, and low-latency communication—connecting people and enterprises on land, at sea, and in the air. From the heart of India’s cities to its most remote frontiers, from territorial waters to international skies, we are enabling seamless coverage beyond boundaries. The partnership marks a significant step in bolstering India’s digital backbone and enhancing strategic communication capabilities for government, defense, maritime, aviation, and enterprise sectors. Guided by our commitment to innovation and nation-building, Nelco continues to pioneer multi-orbit satellite solutions that make inclusive connectivity a reality for all. Read more on: Financial Express (India) https://lnkd.in/dbS7YJw7 #SatelliteConnectivity #LEO #DigitalIndia #TataGroup #EutelsatOneWeb #NationBuilding #InnovationInAction

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🚀 Ready to elevate your AI/ML strategy? CData's Jerod Johnson joins industry experts to explore how data engineering can unlock the full power of intelligent applications. Learn how to reduce latency, scale pipelines, and enable real-time decision-making. 🎥 Watch the on-demand webinar hosted by Database Trends & Applications now: https://bit.ly/4esNOTg #DataEngineering #AI #ML #Analytics #RealTimeData #DataOps #CData #DBTA

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Everyone is racing to make data ready for AI. Far fewer are asking the harder question. Is AI ready for the business? We have become obsessed with cleaning data, structuring data, labeling data, connecting systems, and building pipelines so models can consume enterprise information. Such effort matters. But it is only half the job. Enterprise value is not created when AI understands the data. It is created when AI delivers the right output to the right role, at the right moment, in the right form for action. The same underlying signal does not serve everyone the same way. An operator may need an alert. A manager may need a recommendation. An executive may need a decision summary. A compliance team may need an audit trail. A government analyst may need assessed context. A defense operator may need a fast, confidence-tagged cue for action. Same data. Different role. Different mission. Different risk. Different action. This is where many AI strategies quietly break. They are designed around what the model can process, not around what the business or mission must decide. Enterprise AI is not just a data readiness problem. It is a decision delivery problem. If your AI can interpret the data but cannot adapt to the person or system expected to act on it, you have solved the technical problem and missed the business one.

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👉 “RAG isn’t one thing—it’s evolving…. into 8 powerful architectures that shape how LLMs interact with knowledge.” Here’s the lineup: 1️⃣ Naive RAG – Embed query → retrieve from vector DB → generate. 2️⃣ Multimodal RAG – Expands to text + images + other data sources. 3️⃣ HyDE (Hypothetical Document Embeddings) – Generate a pseudo-answer → embed → retrieve. 4️⃣ Corrective RAG – Cross-checks retrieval, fact-checks via web/external sources. 5️⃣ Graph RAG – Uses structured graph DBs alongside embeddings. 6️⃣ Hybrid RAG – Merges graph DB + vector DB contexts for richer context. 7️⃣ Adaptive RAG – Multi-step reasoning chains that refine queries. 8️⃣ Agentic RAG – Agents with memory, planning, and tool orchestration. Of what i am seeing in the industry, I see organizations moving step-by-step from Naive → Adaptive → Agentic RAG as their systems mature. The big shift? Moving from “retrieving documents” to “reasoning and acting” across data ecosystems. 💬 Which of these RAG architectures do you think will become the enterprise default in the next 12–18 months? #GenerativeAI #RAG #AIArchitecture #LLM #Innovation

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Unlock AI’s real value for your business. Curious how machine learning actually drives outcomes? Today, we break down what neural networks are—and why they matter in real-world decisions. See how smarter data leads to better results. Want to explore how AI can solve your toughest challenges? Let’s connect. 🤝

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While most of us in Software world believe that GenAI would lead to AGI or large tech companies like #MAANG will come with a different architecture for the same, we cannot ignore the fact that real AGI could come from a #BioTech company. #AGI #GenAI #Technology #FoodForThought

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