Tag: command line
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Cloud Blog: Automate app deployment and security analysis with new Gemini CLI extensions
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/automate-app-deployment-and-security-analysis-with-new-gemini-cli-extensions/ Source: Cloud Blog Title: Automate app deployment and security analysis with new Gemini CLI extensions Feedly Summary: Find and fix security vulnerabilities. Deploy your app to the cloud. All without leaving your command-line. Today, we’re closing the gap between your terminal and the cloud with a first look at the future of…
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Docker: Building AI Agents with Docker MCP Toolkit: A Developer’s Real-World Setup
Source URL: https://www.docker.com/blog/docker-mcp-ai-agent-developer-setup/ Source: Docker Title: Building AI Agents with Docker MCP Toolkit: A Developer’s Real-World Setup Feedly Summary: Building AI agents in the real world often involves more than just making model calls — it requires integrating with external tools, handling complex workflows, and ensuring the solution can scale in production. In this post,…
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Tomasz Tunguz: Hidden Technical Debt in AI
Source URL: https://www.tomtunguz.com/hidden-technical-debt-in-ai/ Source: Tomasz Tunguz Title: Hidden Technical Debt in AI Feedly Summary: That little black box in the middle is machine learning code. I remember reading Google’s 2015 Hidden Technical Debt in ML paper & thinking how little of a machine learning application was actual machine learning. The vast majority was infrastructure, data…
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Tomasz Tunguz: The Surprising Input-to-Output Ratio of AI Models
Source URL: https://www.tomtunguz.com/input-output-ratio/ Source: Tomasz Tunguz Title: The Surprising Input-to-Output Ratio of AI Models Feedly Summary: When you query an AI model, it gathers relevant information to generate an answer. For a while, I’ve wondered : how much information does the model need to answer a question? I thought the output would be larger, however…