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@laura_garcia shared a post, 1 day, 13 hours ago
Software Developer, RELIANOID

🚀 RELIANOID is heading to Washington, DC!

From September 9–12, 2025, we’ll be at the 16th Billington CyberSecurity Summit — the premier government cybersecurity event gathering 2,500+ leaders and innovators to shape the future of AI, Zero Trust, cloud security, and critical infrastructure protection. Meet our team and discover how RELIANOID..

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@idjuric660 shared a post, 1 day, 16 hours ago
Technical Content Writer, Mailtrap

Send emails with v0 and Mailtrap

Vercel Mailtrap.io

Learn how to integrate Mailtrap with your v0 application to send transactional emails and manage contacts without writing complex code.

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@faun shared a link, 1 day, 17 hours ago

How Salesforce Delivers Reliable, Low-Latency AI Inference

Salesforce’s AI Metadata Service (AIMS) just got a serious speed boost. They rolled out a multi-layer cache—L1 on the client, L2 on the server—and cut inference latency from 400ms to under 1ms. That’s over 98% faster. But it’s not just about speed anymore. L2 keeps responses flowing even when the b..

How Salesforce Delivers Reliable, Low-Latency AI Inference
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@faun shared a link, 1 day, 17 hours ago

We Needed Better Cloud Storage for Python so We Built Obstore

Obstoreis a new stateless object store that skips fsspec-style caching and keeps its API tight and predictable across S3, GCS, and Azure. Sync and async both work. Under the hood? Fast, zero-copy Rust–Python interop. And on small concurrent async GETs, it reportedly crushes S3FS with up to9x better ..

We Needed Better Cloud Storage for Python so We Built Obstore
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@faun shared a link, 1 day, 17 hours ago

Everything I know about good API design

This guide lays out the playbook for running tough, user-first APIs: no breaking changes, stick to familiar patterns, honor long-lived API keys, and make every write idempotent. It pushes cursor-based pagination for heavy data, rate limits that come with context, and optional fields to keep things ..

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@faun shared a link, 1 day, 17 hours ago

Open Source is one person

New data from ecosyste.ms drops a hard truth:almost 60% of 11.8M open source projects are solo acts. Even among NPM packages topping 1M monthly downloads, about half still rest on one pair of hands. The world runs on open source. But the scaffolding seems shakier than anyone wants to admit—millions..

Open Source is one person
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@faun shared a link, 1 day, 17 hours ago

The unexpected productivity boost of Rust

Lubeno's backend is100% Rust, providing strong safety guarantees for refactoring confidence. Rust's type checker catches async bugs, unlikeTypeScript. Rust excels in tracking lifetimes and borrowing rules.Zig, on the other hand, can be alarming with its compiler choices, such as overlooking typos in..

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@faun shared a link, 1 day, 17 hours ago

From Python to Go: Why We Rewrote Our Ingest Pipeline at Telemetry Harbor

Telemetry Harbor tossed out Python FastAPI and rebuilt its ingest pipeline inGo. The payoff?10x faster, no more CPU freakouts, and strongerdata integritythanks to strict typing. PostgreSQL is now the slowest link in the chain—not the app—which is the kind of bottleneck you actuallywant. Means the s..

From Python to Go: Why We Rewrote Our Ingest Pipeline at Telemetry Harbor
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@faun shared a link, 1 day, 17 hours ago

Go is still not good

Go’s been catching flak for years, and the hits keep coming: stiff variable scoping, no destructor patterns, clunky error handling, and brittle build directives. Critics point out how Go’s design often blocks best practices like RAII and makes devs contort logic just to clean up resources or manage ..

GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.