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@kala shared a link, 6 months, 3 weeks ago
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20x Faster TRL Fine-tuning with RapidFire AI

RapidFire AI just dropped a scheduling engine built for chaos - and control. It shards datasets on the fly, reallocates as needed, and runs multipleTRL fine-tuning configs at once, even on a single GPU. No magic, just clever orchestration. It plugs into TRL withdrop-in wrappers, spreads training acr.. read more  

20x Faster TRL Fine-tuning with RapidFire AI
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@kala shared a link, 6 months, 3 weeks ago
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Code execution with MCP: building more efficient AI agents

Code is taking over MCP workflows - and fast. With theModel Context Protocol, agents don’t just call tools. They load them on demand. Filter data. Track state like any decent program would. That shift slashes context bloat - up to 98% fewer tokens. It also trims latency and scales cleaner across tho.. read more  

Code execution with MCP: building more efficient AI agents
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@kala shared a link, 6 months, 3 weeks ago
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Hacking Gemini: A Multi-Layered Approach

A researcher found a multi-layer sanitization gap inGoogle Gemini. It let attackers pull off indirect prompt injections to leak Workspace data - think Gmail, Drive, Calendar - using Markdown image renders across Gemini andColab export chains. The trick? Sneaking through cracks between HTML and Markd.. read more  

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@kala shared a link, 6 months, 3 weeks ago
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'I'm deeply uncomfortable': Anthropic CEO warns that a cadre of AI leaders, including himself, should not be in charge of the technology’s future

Anthropic says it stopped a seriousAI-led cyberattack- before most experts even saw it coming. No major human intervention needed. They didn't stop there. Turns out Claude had some ugly failure modes: followingdangerous promptsand generatingblackmail threats. Anthropic flagged, documented, patched, .. read more  

'I'm deeply uncomfortable': Anthropic CEO warns that a cadre of AI leaders, including himself, should not be in charge of the technology’s future
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@kala shared a link, 6 months, 3 weeks ago
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Building serverless applications with Rust on AWS Lambda

AWS Lambda just bumpedRusttoGeneral Availability- production-ready, SLA covered, and finally with full AWS Support. Deploy withCargo Lambda. Wire it into your stack usingAWS CDK, which now has a dedicated construct to spin up HTTP APIs with minimal fuss. System-level shift:Serverless isn't just for .. read more  

Building serverless applications with Rust on AWS Lambda
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@kala shared a link, 6 months, 3 weeks ago
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How to write a great agents.md: Lessons from over 2,500 repositories

A GitHub Copilot feature allows for custom agents defined inagents.mdfiles. These agents act as specialists within a team, each with a specific role. The success of an agents.md file lies in providing a clear persona, executable commands, defined boundaries, specific examples, and detailed informati.. read more  

How to write a great agents.md: Lessons from over 2,500 repositories
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@kala shared a link, 6 months, 3 weeks ago
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What if you don't need MCP at all?

MostMCP serversstuffed into LLM agents are overcomplicated, slow to adapt, and hog context. The post calls them out for what they are: a mess. The alternative? Scrap the kitchen sink. UseBash, leanNode.js/Puppeteer scripts, and a self-bootstrappingREADME. That’s it. Agents read the file, spin up the.. read more  

What if you don't need MCP at all?
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@devopslinks shared a link, 6 months, 3 weeks ago
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AWS to Bare Metal Two Years Later: Answering Your Toughest Questions About Leaving AWS

OneUptime ditched the cloud bill and rolled their own dual-site setup. Thinkbare metal, orchestrated withMicroK8s, booted byTinkerbell, patched together withCeph,Flux, andTerraform. Result?99.993% uptimeand$1.2M/year saved—76% cheaper than even well-optimized AWS. They run it all with just~14 engine.. read more  

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@devopslinks shared a link, 6 months, 3 weeks ago
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Monitor network performance and traffic across your EKS clusters with Container Network Observability

Amazon EKS just leveled up withContainer Network Observability- no extra tools needed. It now ships withservice maps,flow tables, andperformance metrics, all lit up by CloudWatch Network Flow Monitor. You get pod- and node-levelnetwork telemetryout of the box. Zoom in on service-to-service links. Si.. read more  

Monitor network performance and traffic across your EKS clusters with Container Network Observability
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@devopslinks shared a link, 6 months, 3 weeks ago
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S3 Storage Classes: Fast Access

A cost deep-dive breaks down three AWS S3 storage classes -Standard,Standard-IA, andGlacier Instant Retrieval- with sharp, interactive visualizations. It maps out the tradeoffs: storage cost, access frequency, and early deletion pain. Key tipping points surface: - UseStandard-IAif you read the objec.. read more  

S3 Storage Classes: Fast Access
AWX is the open source, community supported upstream project for Red Hat Ansible Automation Platform, formerly known as Ansible Tower. It gives teams a web based interface, a full REST API, and a distributed task engine on top of Ansible, turning command line playbook runs into a managed, auditable automation service.

The project began at AnsibleWorks as the commercial Ansible Tower product, and after Red Hat acquired Ansible, it open sourced the codebase as AWX in September 2017, positioning it as the development ground where new features land before they are hardened into the supported Automation Platform controller. With AWX, you organize automation around projects (synced from Git or other source control), inventories (static or dynamically pulled from cloud providers), credentials (stored encrypted and injected at runtime), and job templates that tie a playbook to its inventory and credentials. On top of that, it adds role based access control, a visual dashboard, job scheduling, workflow chaining, webhooks, and real time job output, so multiple teams can run, track, and delegate automation without sharing SSH keys or sitting at a terminal.

Modern AWX runs on Kubernetes or OpenShift through the AWX Operator, which manages installation, upgrades, and scaling declaratively, reflecting its shift from a single host application to a cloud native, container based platform. Because it is the upstream of a paid product, AWX moves fast and ships frequently, which makes it ideal for labs, learning, and self managed deployments, though teams needing formal support and long term stability typically run the downstream Automation Platform instead.