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Curated links from external sources — not 360Softy original articles.

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The Hacker News

Iranian Hackers Use Telegram-Controlled Malware to Spy on Dissidents and Journalists

Cybersecurity agencies in the United States, the United Kingdom, and the Netherlands have detailed a Windows malware that they say Iran's intelligence service uses to spy on dissidents, journalists, and activists around the world. The malware is controlled via the Telegram messaging app and can copy a target's emails and chat messages, take screenshots, and activate the microphone to record

The Hacker NewsRead original
ExternalDevOps
CNCF Blog

What I learned organizing KCD Lima 2026

On July 18, 2026, we held the third edition of Kubernetes Community Days Lima at UTEC in Barranco. By now, we have already sent the Transparency Report to the CNCF, thanked our sponsors, and processed the...

Blog
CNCF BlogRead original
ExternalAI
AWS Machine Learning Blog

Optimizing cost and latency with Amazon Bedrock prompt caching

Prompt caching in Amazon Bedrock can cut input token costs by up to 90% when you repeatedly send the same context to foundation models. This post walks through six practical prompt caching scenarios using the Converse API: message content, system prompt, tool definition, mixed TTL, tenant isolation, and LangChain integration.

Advanced (300)Amazon BedrockTechnical How-to
AWS Machine Learning BlogRead original
ExternalTechnology Trends
The Verge Tech

How The Oregon Trail became a generational icon

Whether you played it in the back of your classroom or on your computer at home, if you were a kid in the last 30 years you almost certainly grew up playing The Oregon Trail. On the season 5 premiere of Version History, our fearless wagon leader David Pierce is joined by gaming journalist Chris Grant and Philip Bouchard, the designer and team leader of the game's most iconic version. They talk about the academic origins of The Oregon Trail, the game's complicated legacy, and whether anyone ever

The Verge TechRead original
ExternalAI
AWS Machine Learning Blog

Build an AI-powered product tagging system with Amazon SageMaker serverless model customization

Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) on Amazon SageMaker serverless model customization, then deploy it for asynchronous inference to build a cost-efficient product tagging system.

Amazon SageMakerExpert (400)Technical How-to
AWS Machine Learning BlogRead original
ExternalAI
AWS Machine Learning Blog

Announcing instance preference lists for Amazon SageMaker AI training jobs

Amazon SageMaker AI now offers instance preference lists for training and processing jobs. Specify an ordered list of up to five instance types, and SageMaker AI automatically launches on the first type with available capacity, eliminating manual retry loops and capacity-watching scripts.

Amazon SageMaker AIAnnouncementsIntermediate (200)
AWS Machine Learning BlogRead original

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