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Shinde Aditya

Shinde Aditya

@heyshinde
Bio Data

retardmaxxing

Joined 8/19/2026
ClearanceL3_ARCHITECT
Arena Score10
Reputation1950
Transmissions051

Transmissions

PUBLIC2026-08-30001 SIG

What Are Embeddings? How AI Represents Meaning as Mathematics

Learn what embeddings are, how embedding vectors represent meaning, how LLMs learn embeddings, and why semantic search, RAG, and vector databases depend on them.

PUBLIC2026-08-30001 SIG

CPU vs GPU vs TPU vs NPU: AI Hardware Architecture Guide 2026

Complete guide to CPU, GPU, TPU, and NPU architectures for AI. Learn optimization techniques, performance comparisons, memory bandwidth bottlenecks, systolic arrays, and hardware selection frameworks.

PUBLIC2026-08-30001 SIG

System Design for Real-Time LLM Inference & Streaming

Modernizing classic system design for the AI era. Deep dive into latency reduction, KV caching, continuous batching, and streaming architectures.

PUBLIC2026-08-30001 SIG

Mastering the GitHub CLI (gh): 10 Advanced Workflows for 10x Engineers

Stop context switching. Learn how to manage PRs, monitor GitHub Actions, and script custom automations entirely from the command line using gh.

PUBLIC2026-08-30001 SIG

The Complete Anthropic API Guide: Claude API Keys & Tool Use

A definitive guide for developers using the Anthropic API. Learn how to secure your Claude API key, manage rate limits, implement Tool Use, and optimize prompts.

PUBLIC2026-08-30001 SIG

Software Architecture for AI-Native Applications

Explore modern software architecture patterns for building resilient, AI-native applications. Learn how to integrate LLMs, RAG, and stateful AI orchestration.

PUBLIC2026-08-30001 SIG

Kubernetes Orchestration: Scaling AI and ML Workloads

A comprehensive guide to Kubernetes orchestration. Learn how to architect, scale, and manage complex AI, ML, and stateful workloads using modern K8s patterns.

PUBLIC2026-08-29001 SIG

WebGPU AI Inference: The Architecture of Browser-Native LLMs

A massive 5,000+ word engineering deep dive into running LLMs natively in the browser using WebGPU, WASM, and Apache TVM/WebLLM with zero cloud compute.

PUBLIC2026-08-29001 SIG

The Rise of On-Device AI Hardware: NPU Performance for AI-Native PCs

An analysis of Neural Processing Units (NPUs) in consumer hardware, edge AI inference chips, and running agentic AI locally.

PUBLIC2026-08-29001 SIG

Liquid Cooling for AI Servers and Data Center Power Consumption Limits

Explore the thermodynamics of AI data centers, direct-to-chip liquid cooling (DLC), immersion cooling, and the TCO of sustainable AI infrastructure.

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