#chetanpatil – Chetan Arvind Patil
Nano Banana Strategic Context AI SoC development is now a board-level strategic choice, not just a technical decision. The question is no longer if AI acceleration is needed, but who should own the silicon. As AI workloads grow and diversify, companies must decide whether to build custom
Nano Banana Data Center Networking Became A Silicon Problem Data center networking has moved from a background enabler to a key driver of performance. In cloud and AI environments, network speed and reliability directly affect application latency, accelerator usage, storage throughput, and cost per workload. As clusters
Nano Banana Compute Infrastructure For New-Age Applications Modern workloads are AI-heavy, data-intensive, latency-sensitive, and increasingly distributed. These characteristics are reshaping the compute infrastructure. Traditional enterprise applications relied mainly on CPU-centric execution with moderate memory and networking. In contrast, new-age workloads demand sustained high throughput. They also require
Nano Banana The Changing Shape Of AI Workloads AI workloads have rapidly evolved. They have shifted from lengthy, compute-intensive training runs to an ongoing cycle. This cycle includes training, deployment, inference, and refinement. AI systems today are expected to respond in real time, operate at scale, and
Nano Banana Two Worlds Of AI Compute Are Finally Colliding For more than a decade, AI silicon has evolved along two independent trajectories. On one side sat throughput-optimized architectures built to train massive models across thousands of accelerators. These prioritize raw FLOPS, memory bandwidth, and scaling efficiency.
Nano Banana What Is Silicon Test Analytics Silicon test analytics refers to the systematic analysis of data generated during semiconductor testing to improve yield, product quality, and manufacturing efficiency. It operates across wafer sort, final test, and system-level test, using test results to understand how silicon behaves
Nano Banana What Computer Architecture Is And Why It Matters Computer architecture defines a computing system’s structure, component interaction, and trade-offs for performance, efficiency, cost, and reliability at scale. Architecture balances instruction sets, microarchitecture, memory hierarchies, and system-level design to meet workload requirements. Instruction encoding, pipeline depth,
Nano Banana Yield As The Hidden Profit Engine In the economics of semiconductor products, few variables exert as much influence as yield, yet few receive as little attention outside manufacturing circles. Yield quietly governs how much value can be extracted from every wafer, shaping product cost structures,
Nano Banana Reliance Of AI And Data Workloads On Computer Architecture AI and modern data workloads have transformed how we think about computing systems. Traditional processors were designed for sequential tasks and moderate data movement. Today’s AI models work with enormous datasets and large numbers of parameters
Nano Banana The Shifting Foundations Of Semiconductor Productivity Productivity in semiconductors was once anchored in a predictable formula in which each new node delivered higher transistor density, better performance per watt, and stable cost per transistor. That engine is weakening. Design complexity has surged, stretching development cycles
Hi, I am Chetan Arvind Patil (chay-tun – how to pronounce), a semiconductor professional whose job is turning data into products for the semiconductor industry that powers billions of devices around the world. And while I like what I do, I also enjoy biking, working on few ideas, apart from writing, and talking about interesting developments in hardware, software, semiconductor and technology.
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Opinions expressed here are my own and may not reflect those of others. Unless I am quoting someone, they are just my own views.
Nano Banana Strategic Context AI SoC development is now a board-level strategic choice, not just a technical decision. The
Nano Banana Data Center Networking Became A Silicon Problem Data center networking has moved from a background enabler to
Nano Banana Compute Infrastructure For New-Age Applications Modern workloads are AI-heavy, data-intensive, latency-sensitive, and increasingly distributed. These characteristics are
Nano Banana The Changing Shape Of AI Workloads AI workloads have rapidly evolved. They have shifted from lengthy, compute-intensive
Nano Banana Two Worlds Of AI Compute Are Finally Colliding For more than a decade, AI silicon has evolved
