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@sanjayjoshi shared a post, 4 days, 14 hours ago

8+ Best Shadcn Collapsible Component Examples for React & Next.js

Shadcn Collapsible components offer a flexible, non-interruptive way to manage secondary content in React and Next.js projects. Unlike accordions or dialogs, they keep users in context while reducing UI clutter. Key variations include sidebar menus, API key managers, and file trees, all of which benefit from Tailwind CSS styling and full ARIA accessibility.

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@alihenryofficial started using tool SAP Commerce Cloud , 4 days, 14 hours ago.

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@alihenryofficial started using tool Google Publisher Tag , 4 days, 14 hours ago.

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@laura_garcia shared a post, 4 days, 15 hours ago

Software Developer, RELIANOID

𝗲𝗻𝗮𝗯𝗹𝗲 𝗦𝗲𝗰𝘂𝗿𝗲 𝗕𝗼𝗼𝘁 𝗶𝗻 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗘𝗱𝗶𝘁𝗶𝗼𝗻

𝗦𝗲𝗰𝘂𝗿𝗲 𝗕𝗼𝗼𝘁 + 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 = 𝘴𝘵𝘳𝘰𝘯𝘨𝘦𝘳 𝘵𝘳𝘶𝘴𝘵 from the very first instruction executed. Here's a practical guide on 𝗵𝗼𝘄 𝘁𝗼 𝗲𝗻𝗮𝗯𝗹𝗲 𝗦𝗲𝗰𝘂𝗿𝗲 𝗕𝗼𝗼𝘁 𝗶𝗻 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗘𝗱𝗶𝘁𝗶𝗼𝗻 using the standard shim + MOK approach. 🔐 What’s inside: - Why Secure Boot can’t be enabled on first install - Step-by-step MOK enr..

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@sanjayjoshi gave 🐾 to How To Make a Fast Dynamic Language Interpreter , 4 days, 17 hours ago.

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@sanjayjoshi gave 🐾 to A Couple Million Lines of Haskell: Production Engineering at Mercury , 4 days, 17 hours ago.

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@sanjayjoshi gave 🐾 to 𝗛𝗮𝗰𝗸 𝗦𝗽𝗮𝗰𝗲 𝗖𝗼𝗻 𝟮𝟬𝟮𝟲 , 4 days, 17 hours ago.

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@laura_garcia shared a post, 5 days, 14 hours ago

Software Developer, RELIANOID

𝗛𝗮𝗰𝗸 𝗦𝗽𝗮𝗰𝗲 𝗖𝗼𝗻 𝟮𝟬𝟮𝟲

🚀 𝗛𝗮𝗰𝗸 𝗦𝗽𝗮𝗰𝗲 𝗖𝗼𝗻 𝟮𝟬𝟮𝟲 📍 Kennedy Space Center 📅 May 6–9, 2026 𝙒𝙝𝙚𝙧𝙚 𝙘𝙮𝙗𝙚𝙧𝙨𝙚𝙘𝙪𝙧𝙞𝙩𝙮 𝙢𝙚𝙚𝙩𝙨 𝙨𝙥𝙖𝙘𝙚 𝙞𝙣𝙣𝙤𝙫𝙖𝙩𝙞𝙤𝙣. Hack Space Con is not your typical event — it’s where cybersecurity, aerospace, and advanced technologies converge to shape the future of security beyond Earth. 🔍 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗲𝘅𝗽𝗲𝗰𝘁: - Hands-on techn..

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@varbear shared a link, 5 days, 14 hours ago

FAUN.dev()

A Couple Million Lines of Haskell: Production Engineering at Mercury

Mercury runs ~2M lines ofHaskellin production. They choseTemporalto replace cron and DB-backed state machines. Durable workflows replace brittle coordination. They open-sourced aHaskellSDK forTemporal, wired inOpenTelemetryhooks, and pushed records-of-functions plus domain-error types... read more

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@varbear shared a link, 5 days, 14 hours ago

FAUN.dev()

How To Make a Fast Dynamic Language Interpreter

Zef's AST-walking interpreter posts a 16.6× speed-up. The gains come from surgical changes:64-bit tagged values,AST node & RMW specialization,symbol hash-consing,inline caches, and a shapedobject model. Developers built it onFil-C++and later ported it toYolo-C++. The Yolo build adds ~4x speed, at th.. read more

AIStor is an enterprise-grade, high-performance object storage platform built for modern data workloads such as AI, machine learning, analytics, and large-scale data lakes. It is designed to handle massive datasets with predictable performance, operational simplicity, and hyperscale efficiency, while remaining fully compatible with the Amazon S3 API. AIStor is offered under a commercial license as a subscription-based product.

At its core, AIStor is a software-defined, distributed object store that runs on commodity hardware or in containerized environments like Kubernetes. Rather than being limited to traditional file or block interfaces, it exposes object storage semantics that scale from petabytes to exabytes within a single namespace, enabling consistent, flat addressing of vast datasets. It is engineered to sustain very high throughput and concurrency, with examples of multi-TiB/s read performance on optimized clusters.

AIStor is optimized specifically for AI and data-intensive workloads, where throughput, low latency, and horizontal scalability are critical. It integrates broadly with modern AI and analytics tools, including frameworks such as TensorFlow, PyTorch, Spark, and Iceberg-style table engines, making it suitable as the foundational storage layer for pipelines that demand both performance and consistency.

Security and enterprise readiness are central to AIStor’s design. It includes capabilities like encryption, replication, erasure coding, identity and access controls, immutability, lifecycle management, and operational observability, which are important for mission-critical deployments that must meet compliance and data protection requirements.

AIStor is positioned as a platform that unifies diverse data workloads — from unstructured storage for application data to structured table storage for analytics, as well as AI training and inference datasets — within a consistent object-native architecture. It supports multi-tenant environments and can be deployed across on-premises, cloud, and hybrid infrastructure.