Gate and Kernel (@insidecomput) header
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Explaining how computers really work—from logic gates, CPUs, memory, C Language, and Linux to RISC-V, ARM, x86, AI, and large language models.

La Canada Flintridge, CA
Joined June 2018
Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)Photo by Gate and Kernel (@insidecomput)
Gate and Kernel retweeted
AND, OR, XOR Gates
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Dennis Ritchie wasn't trying to create one of the world's most important programming languages. he was trying to build a better language for Unix. Ken Thompson's B was too limited for the new PDP-11, so Ritchie started adding types and building a real compiler. That became C. the first version was built on a machine with just 24 KB of memory. Decades later, C is still running the world.
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Gate and Kernel retweeted
Replying to @insidecomput
hey, that's so cool! sounds like a simple yet important part of circuits. 💅
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Why is every tech giant hoarding GPUs right now? 🤖💡 It comes down to one core architectural difference: 1️⃣ CPUs prioritize low latency (running sequential logic as fast as possible). 2️⃣ GPUs prioritize high throughput (running thousands of parallel threads at once). Turns out, rendering 3D pixels in video games requires the exact same math as training LLMs. Once you understand the hardware-software boundary, the entire AI stack finally makes sense.
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Replying to @insidecomput
AI safety and proper controls are becoming more important than ever as autonomous agents continue to evolve.
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LLMs Don’t Need GPUs Anymore? 17,000 Tokens Per Second! youtu.be/mCkVBm8m9mQ
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Replying to @insidecomput
DRAM needs refresh, while NAND traps charge.
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Replying to @insidecomput @Dell
Plus it keeps laptops like the @Dell XPS 13 thin, light, cool, and efficient!
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How Linux Works youtu.be/9PkIYK9tdAI?si=NU-E… A simple ls command travels through: User ↓ Shell ↓ fork() ↓ execve() ↓ Kernel ↓ VFS ↓ Page Cache ↓ Filesystem ↓ Terminal before you see the result. Most users never realize how much happens behind a single command.
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How Linux Architecture Works ? youtu.be/KNw5b8emVpU A simple Linux workflow looks like this: User enters a command in the shell The shell interprets the command System libraries translate requests into system calls The kernel processes the request Device drivers communicate with hardware Results return back to the user application
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Replying to @insidecomput
Pipeline ≠ Parallelism Pipeline: Same work, overlapped Parallelism: Different work, simultaneous One improves flow. The other increases capacity. #CPU #Hardware
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Replying to @insidecomput
Clear distinction, real outcomes matter. Latency and determinism are big wins for FPGA in AI inference and networking, curious about toolchains
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Google just dropped a quantum bomb 💥 Their new chip Willow solved a problem in <5 minutes That would take a supercomputer 10 septillion years Now people are asking: Are quantum computers tapping into parallel universes? Reality: No proof of that. But something big is happening. ⚡ #QuantumComputing #Google #AI #Tech
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They sent four human beings 252,756 miles away from Earth, guided them around the Moon, and brought them back safely—landing at a precise location on Earth. No GPS. No modern computers. Just math, physics, and human brilliance.
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Replying to @insidecomput
The future of computing isn’t one technology. It’s a WAR of paradigms: | Hardware | Strength | Weakness | | GPU | Massive parallel AI | Power hungry | FPGA | Ultra-low latency | Hard to program | Quantum | Exponential scaling | Not practica
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The future is not one chip. It’s a stack: CPU + GPU + FPGA + Quantum
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Sequential Processing is why your code feels slow. But most engineers never question it. Let’s break it down 👇
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ARM + FPGA = System DO you Agree ?
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Most FPGA designs fail here 👇
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Real systems don’t choose. They combine.
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