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@faun shared a link, 3 weeks, 3 days ago

Writing Load Balancer From Scratch In 250 Line of Code

A developer rolled out a fully working **Go load balancer** with a clean **Round Robin** setup—and hooks for dropping in smarter strategies like **Least Connection** or **IP Hash**. Backend servers live in a custom server pool. Swapping balancing logic? Just plug into the interface...

Writing Load Balancer From Scratch In 250 Line of Code
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@faun shared a link, 3 weeks, 3 days ago

Privacy for subdomains: the solution

A two-container setup using **acme.sh** gets Let's Encrypt certs running on a Synology NAS—thanks, Docker. No built-in Certbot support? No problem. Cloudflare DNS API token handles auth. Scheduled tasks handle renewal...

Privacy for subdomains: the solution
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@faun shared a link, 3 weeks, 3 days ago

Uncommon Uses of Common Python Standard Library Functions

A fresh guide gives old Python friends a second look—turns out, tools like **itertools.groupby**, **zip**, **bisect**, and **heapq** aren’t just standard; they’re slick solutions to real problems. Think run-length encoding, matrix transposes, or fast, sorted inserts without bringing in another depen..

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@faun shared a link, 3 weeks, 3 days ago

Authentication Explained: When to Use Basic, Bearer, OAuth2, JWT & SSO

Modern apps don’t just check passwords—they rely on **API tokens**, **OAuth**, and **Single Sign-On (SSO)** to know who’s knocking before they open the door...

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@faun shared a link, 3 weeks, 3 days ago

Becoming a Research Engineer at a Big LLM Lab - 18 Months of Strategic Career Development

To land a big career role like Mistral, mix efficient **tactical** moves (like LeetCode practice) with **strategic** ups, like building a powerful portfolio and a solid network. Balance is key; aim to impress and prepare well without overlooking the power of strategy in shaping a successful career...

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@faun shared a link, 3 weeks, 3 days ago

Jupyter Agents: training LLMs to reason with notebooks

Hugging Face dropped an open pipeline and dataset for training small models—think **Qwen3-4B**—into sharp **Jupyter-native data science agents**. They pulled curated Kaggle notebooks, whipped up synthetic QA pairs, added lightweight **scaffolding**, and went full fine-tune. Net result? A **36% jump ..

Jupyter Agents: training LLMs to reason with notebooks
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@faun shared a link, 3 weeks, 3 days ago

Building a Natural Language Interface for Apache Pinot with LLM Agents

MiQ plugged **Google’s Agent Development Kit** into their stack to spin up **LLM agents** that turn plain English into clean, validated SQL. These agents speak directly to **Apache Pinot**, firing off real-time queries without the usual parsing pain. Behind the scenes, it’s a slick handoff: NL2SQL ..

Building a Natural Language Interface for Apache Pinot with LLM Agents
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@faun shared a link, 3 weeks, 3 days ago

The productivity paradox of AI coding assistants

A July 2025 METR trial dropped a twist: seasoned devs using Cursor with Claude 3.5/3.7 moved **19% slower** - while thinking they were **20% faster**. Chalk it up to AI-induced confidence inflation. Faros AI tracked over **10,000 developers**. More AI didn’t mean more done. It meant more juggling, ..

The productivity paradox of AI coding assistants
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@faun shared a link, 3 weeks, 3 days ago

Inside NVIDIA GPUs: Anatomy of high performance matmul kernels

NVIDIA Hopper packs serious architectural tricks. At the core: **Tensor Memory Accelerator (TMA)**, **tensor cores**, and **swizzling**—the trio behind async, cache-friendly matmul kernels that flirt with peak throughput. But folks aren't stopping at cuBLAS. They're stacking new tactics: **warp-gro..

Inside NVIDIA GPUs: Anatomy of high performance matmul kernels
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@faun shared a link, 3 weeks, 3 days ago

5 Free AI Courses from Hugging Face

Hugging Face just rolled out a sharp set of free AI courses. Real topics, real tools—think **AI agents, LLMs, diffusion models, deep RL**, and more. It’s hands-on from the jump, packed with frameworks like LangGraph, Diffusers, and Stable Baselines3. You don’t just read about models—you build ‘em i..

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