Want faster AI? Join our live demo Wed, May 9. Train a chatbot intent classifier using sample chats and labeling functions. Grab your spot: https://
snorkel.ai/webinar/weekly
-demo-with-qa/
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Live Demo: Train AI Chatbot Intent Classifier May 9
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Cisco Outshift Boosts Productivity 10x with Agentic AI Engineer
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How Cisco Outshift 10x’d productivity with their Agentic AI Engineer @outshiftbycisco
, Cisco’s innovation engine, uses JARVIS, their AI Platform Engineer, to automate developer requests and eliminate operational bottlenecks. Built with LangGraph and LangSmith, JARVIS has allowed -
Paper2Code: Multi-Agent System Transforms ML Papers into Code
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Turn any ML paper into code repository! Paper2Code is a multi-agent LLM system that transforms a paper into a code repository. It follows a three-stage pipeline: planning, analysis, and code generation, each handled by specialized agents. 100% Open Source
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Open-Source AI Cookbook as a technical resource for builders
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The Open-Source AI Cookbook is a goldmine. Real notebooks from real builders not just theory.
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Cisco’s Foundation-Sec-8B Matches GPT-4o-mini on Security Tasks
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Cisco's Foundation AI released Foundation-Sec-8B on HF Built on Llama 3.1, the LLM matches Llama 3.1-70B & GPT-4o-mini on multiple security tasks It will help with use cases like threat detection, vulnerability assessment, security automation, and more
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Apple Partners with Anthropic for AI Vibe Coding Platform in Xcode
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Apple is said to be partnering with Anthropic for an AI 'vibe coding' platform The offering, powered by a Claude Sonnet model, will automate writing, editing, and testing code within Apple’s Xcode software Launch timeline still remains unclear!
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Cursor AI and Windsurf AI tools for development assistance
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Wouldn't @cursor_ai or @windsurf_ai help you?
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Vibe Coders Rise: Platform Responsibility Over User Skill
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First step is happening already where people want to hire vibe coders to work on startup ideas or whatever. And there’s levels to good vs bad ones, the best ones today know the implications of security, scalability etc I think those issues fall on the platforms not the users
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Engineers Have Superior AI Tool Experience Than Hours Spent
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And I assume engineers are better early users of these tools too – know how to prompt, what to ask for, how to debug. So their “experience” is actually more valuable. If hours spent = experience here its the wrong metric id suspect It’s how much can you get out of these tools