• What the Boeing 737 MAX’s crashes can teach us about production business – the effects of commoditisation

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    newrepublic.com/article/154944/boeing-737-max-investigation-indonesia-lion-air-ethiopian-airlines-managerial-revolution

     

     

    Airplane manufacturing is no different from mortgage lending or insulin distribution or make-believe blood analyzing software (or VFX?) —another cash cow for the one percent, bound inexorably for the slaughterhouse.

     

    The beginning of the end was “Boeing’s 1997 acquisition of McDonnell Douglas, a dysfunctional firm with a dilapidated aircraft plant in Long Beach and a CEO (Harry Stonecipher) who liked to use what he called the “Hollywood model” for dealing with engineers: Hire them for a few months when project deadlines are nigh, fire them when you need to make numbers.” And all that came with it. “Stonecipher’s team had driven the last nail in the coffin of McDonnell’s flailing commercial jet business by trying to outsource everything but design, final assembly, and flight testing and sales.”

     

    It is understood, now more than ever, that capitalism does half-assed things like that, especially in concert with computer software and oblivious regulators.

     

    There was something unsettlingly familiar when the world first learned of MCAS in November, about two weeks after the system’s unthinkable stupidity drove the two-month-old plane and all 189 people on it to a horrific death. It smacked of the sort of screwup a 23-year-old intern might have made—and indeed, much of the software on the MAX had been engineered by recent grads of Indian software-coding academies making as little as $9 an hour, part of Boeing management’s endless war on the unions that once represented more than half its employees.

     

    Down in South Carolina, a nonunion Boeing assembly line that opened in 2011 had for years churned out scores of whistle-blower complaints and wrongful termination lawsuits packed with scenes wherein quality-control documents were regularly forged, employees who enforced standards were sabotaged, and planes were routinely delivered to airlines with loose screws, scratched windows, and random debris everywhere.

     

    Shockingly, another piece of the quality failure is Boeing securing investments from all airliners, starting with SouthWest above all, to guarantee Boeing’s production lines support in exchange for fair market prices and favorite treatments. Basically giving Boeing financial stability independently on the quality of their product. “Those partnerships were but one numbers-smoothing mechanism in a diversified tool kit Boeing had assembled over the previous generation for making its complex and volatile business more palatable to Wall Street.”

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  • Types of AI Explained in a few Minutes – AI Glossary

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    1️⃣ 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗔𝗜) – The broadest category, covering automation, reasoning, and decision-making. Early AI was rule-based, but today, it’s mainly data-driven.
    2️⃣ 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟) – AI that learns patterns from data without explicit programming. Includes decision trees, clustering, and regression models.
    3️⃣ 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 (𝗡𝗡) – A subset of ML, inspired by the human brain, designed for pattern recognition and feature extraction.
    4️⃣ 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗗𝗟) – Multi-layered neural networks that drives a lot of modern AI advancements, for example enabling image recognition, speech processing, and more.
    5️⃣ 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 – A revolutionary deep learning architecture introduced by Google in 2017 that allows models to understand and generate language efficiently.
    6️⃣ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 (𝗚𝗲𝗻𝗔𝗜) – AI that doesn’t just analyze data—it creates. From text and images to music and code, this layer powers today’s most advanced AI models.
    7️⃣ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗣𝗿𝗲-𝗧𝗿𝗮𝗶𝗻𝗲𝗱 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 (𝗚𝗣𝗧) – A specific subset of Generative AI that uses transformers for text generation.
    8️⃣ 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠) – Massive AI models trained on extensive datasets to understand and generate human-like language.
    9️⃣ 𝗚𝗣𝗧-4 – One of the most advanced LLMs, built on transformer architecture, trained on vast datasets to generate human-like responses.
    🔟 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 – A specific application of GPT-4, optimized for conversational AI and interactive use.

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