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52 Weeks of Cloud

52 Weeks of Cloud

By: Noah Gift
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 A weekly podcast on technical topics related to cloud computing including: MLOPs, LLMs, AWS, Azure, GCP, Multi-Cloud and Kubernetes.2021-2024 Pragmatic AI Labs Mathematics Science
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Episodes
  • DevOps Narrow AI Debunking Flowchart

    DevOps Narrow AI Debunking Flowchart
    May 16 2025
    Extensive Notes: The Truth About AI and Your Coding JobTypes of AI

    • Narrow AI

      • Not truly intelligent
      • Pattern matching and full text search
      • Examples: voice assistants, coding autocomplete
      • Useful but contains bugs
      • Multiple narrow AI solutions compound bugs
      • Get in, use it, get out quickly

    • AGI (Artificial General Intelligence)

      • No evidence we're close to achieving this
      • May not even be possible
      • Would require human-level intelligence
      • Needs consciousness to exist
      • Consciousness: ability to recognize what's happening in environment
      • No concept of this in narrow AI approaches
      • Pure fantasy and magical thinking

    • ASI (Artificial Super Intelligence)

      • Even more fantasy than AGI
      • No evidence at all it's possible
      • More science fiction than reality
    The DevOps Flowchart Test

    1. Can you explain what DevOps is?

      • If no → You're incompetent on this topic
      • If yes → Continue to next question

    2. Does your company use DevOps?

      • If no → You're inexperienced and a magical thinker
      • If yes → Continue to next question

    3. Why would you think narrow AI has any form of intelligence?

      • Anyone claiming AI will automate coding jobs while understanding DevOps is likely:
        • A magical thinker
        • Unaware of scientific process
        • A grifter
    Why DevOps Matters
    • Proven methodology similar to Toyota Way
    • Based on continuous improvement (Kaizen)
    • Look-and-see approach to reducing defects
    • Constantly improving build systems, testing, linting
    • No AI component other than basic statistical analysis
    • Feedback loop that makes systems better
    The Reality of Job Automation
    • People who do nothing might be eliminated
      • Not AI automating a job if they did nothing
    • Workers who create negative value
      • People who create bugs at 2AM
      • Their elimination isn't AI automation
    Measuring Software Quality
    • High churn files correlate with defects
    • Constant changes to same file indicate not knowing what you're doing
    • DevOps patterns help identify issues through:
      • Tracking file changes
      • Measuring complexity
      • Code coverage metrics
      • Deployment frequency
    Conclusion
    • Very early stages of combining narrow AI with DevOps
    • Narrow AI tools are useful but limited
    • Need to look beyond magical thinking
    • Opinions don't matter if you:
      • Don't understand DevOps
      • Don't use DevOps
      • Claim to understand DevOps but believe narrow AI will replace developers
    Raw Assessment
    • If you don't understand DevOps → Your opinion doesn't matter
    • If you understand DevOps but don't use it → Your opinion doesn't matter
    • If you understand and use DevOps but think AI will automate coding jobs → You're likely a magical thinker or grifter

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    11 mins
  • No Dummy, AI Isn't Replacing Developer Jobs

    No Dummy, AI Isn't Replacing Developer Jobs
    May 14 2025
    Extensive Notes: "No Dummy: AI Will Not Replace Coders"Introduction: The Critical Thinking ProblemAmerica faces a critical thinking deficit, especially evident in narratives about AI automating developers' jobsSpeaker advocates for examining the narrative with core critical thinking skillsSuggests substituting the dominant narrative with alternative explanationsAlternative Explanation 1: Non-Productive EmployeesOrganizations contain people who do "absolutely nothing"If you fire a person who does no work, there will be no impactThese non-productive roles exist in academics, management, and technical industriesReference to David Graeber's book "Bullshit Jobs" which categorizes meaningless jobs:Task mastersBox tickersGoonsWhen these jobs are eliminated, AI didn't replace them because "the job didn't need to exist"Alternative Explanation 2: Low-Skilled DevelopersSome developers have "very low or no skills, even negative skills"Firing someone who writes "buggy code" and replacing them with a more productive developer (even one using auto-completion tools) isn't AI replacing a jobThese developers have "negative value to an organization"Removing such developers would improve the company regardless of automationUsing better tools, CI/CD, or software engineering best practices to compensate for their removal isn't AI replacementAlternative Explanation 3: Basic Automation with Traditional ToolsSoftware engineers have been automating tasks for decades without AISpeaker's example: At Disney Future Animation (2003), replaced manual weekend maintenance with bash scripts"A bash script is not AI. It has no form of intelligence. It's a for loop with some conditions in it."Many companies have poor processes that can be easily automated with basic scriptsThis automation has "absolutely nothing to do with AI" and has "been happening for the history of software engineering"Alternative Explanation 4: Narrow vs. General IntelligenceUseful applications of machine learning exist:Linear regressionK-means clusteringAutocompletionTranscriptionThese are "narrow components" with "zero intelligence"Each component does a specific task, not general intelligence"When someone says you automated a job with a large language model, what are you talking about? It doesn't make sense."LLMs are not intelligent; they're task-based systemsAlternative Explanation 5: OutsourcingCompanies commonly outsource jobs to lower-cost regionsJobs claimed to be "taken by AI" may have been outsourced to India, Mexico, or ChinaThis practice is common in America despite questionable ethicsOrganizations may falsely claim AI automation when they've simply outsourced workAlternative Explanation 6: Routine Corporate LayoffsLarge companies routinely fire ~3% of their workforce (Apple, Amazon mentioned)Fear is used as a motivational tool in "toxic American corporations"The "AI is coming for your job" narrative creates fear and motivationMore likely explanations: non-productive employees, low-skilled workers, simple automation, etc.The Marketing and Sales DeceptionCEOs (specifically mentions Anthropic and OpenAI) make false claims about agent capabilities"The CEO of a company like Anthropic... is a liar who said that software engineering jobs will be automated with agents"Speaker claims to have used these tools and found "they have no concept of intelligence"Sam Altman (OpenAI) characterized as "a known liar" who "exaggerates about everything"Marketing people with no software engineering background make claims about coding automationCompanies like NVIDIA promote AI hype to sell GPUsConclusion: The Real Problem"AI" is a misnomer for large language modelsThese are "narrow intelligence" or "narrow machine learning" systemsThey "do one task like autocomplete" and chain these tasks togetherThere is "no concept of intelligence embedded inside"The speaker sees a bigger issue: lack of critical thinking in AmericaWarns that LLMs are "dumb as a bag of rocks" but powerful toolsLeft in inexperienced hands, these tools could create "catastrophic software"Rejects the narrative that "AI will replace software engineers" as having "absolutely zero evidence"Key Quotes"We have a real problem with critical thinking in America. And one of the places that is very evident is this false narrative that's been spread about AI automating developers jobs.""If you fire a person that does no work, there will be no impact.""I have been automating people's jobs my entire life... That's what I've been doing with basic scripts. A bash script is not AI.""Large language models are not intelligent. How could they possibly be this mystical thing that's automating things?""By saying that AI is going to come for your job soon, it's a great false narrative to spread fear where people worry about all the AI is coming.""Much more likely the story of AI is that it is a very powerful tool that is dumb as a bag of rocks and left into the hands of the inexperienced and the naive and the fools could create ...
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    15 mins
  • The Narrow Truth: Dismantling IntelligenceTheater in Agent Architecture

    The Narrow Truth: Dismantling IntelligenceTheater in Agent Architecture
    May 14 2025

    how Gen.AI companies combine narrow ML components behind conversational interfaces to simulate intelligence. Each agent component (text generation, context management, tool integration) has direct non-ML equivalents. API access bypasses the deceptive UI layer, providing better determinism and utility. Optimal usage requires abandoning open-ended interactions for narrow, targeted prompting focused on pattern recognition tasks where these systems actually deliver value.

    🔥 Hot Course Offers:
    • 🤖 Master GenAI Engineering - Build Production AI Systems
    • 🦀 Learn Professional Rust - Industry-Grade Development
    • 📊 AWS AI & Analytics - Scale Your ML in Cloud
    • ⚡ Production GenAI on AWS - Deploy at Enterprise Scale
    • 🛠️ Rust DevOps Mastery - Automate Everything
    🚀 Level Up Your Career:
    • 💼 Production ML Program - Complete MLOps & Cloud Mastery
    • 🎯 Start Learning Now - Fast-Track Your ML Career
    • 🏢 Trusted by Fortune 500 Teams

    Learn end-to-end ML engineering from industry veterans at PAIML.COM
    Show More Show Less
    11 mins

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