Does LLMs Really Makes Us Dumb

The tech industry's version of David vs. Goliath just got real. On one side, we've got trillion-dollar titans like Google, NVIDIA, OpenAI, and Meta throwing endless resources at the GPU and AI arms race. On the other? Just DeepSeek and their single open-source repo taking them all on. It's that classic moment when some scrappy engineer in their pajamas pushes code that makes corporate execs choke on their $12 lattes. Ten years of VC funding and board meetings outperformed by someone who probably debugs with print statements. The beautiful chaos of open source – where sometimes the simplest solution from the smallest player completely disrupts the market that giants spent billions trying to corner. Welcome to tech, where your market cap means nothing when someone's weekend project goes viral.

Ah, the classic LinkedIn resume time-travel paradox! This CS grad with a 4.3 GPA from Columbia somehow managed to intern at NASA, OpenAI, and Google before graduating, then immediately pivoted to their dream career... flipping burgers at McDonald's in May 2025 (which hasn't even happened yet). The chronological whiplash is giving me serious temporal complexity issues. It's like they implemented a reverse-sorted linked list of career achievements where Big O notation stands for "Order of fries, please." This resume perfectly captures that special moment when your algorithm for career progression throws an unexpected exception.

That moment when your AI model is just a hammer repeatedly hitting itself until it gets a reward. Basically how most machine learning projects go in production - smack things randomly until something works, then call it "intelligence." The neural network doesn't understand the problem, it just knows that hitting the nail sometimes makes the treats appear.

Formal Bugs Bunny just murdered an entire generation of developers who can't code without their AI bestie. HTTP 429 is the digital equivalent of "sorry, you've asked for too much help today." The irony of wishing "vibe coders" a rate limit error is pure evil genius – like watching someone's IDE crash right before a demo. Those who actually know how to solve problems without pasting entire error messages into ChatGPT are sitting back with popcorn, watching the chaos unfold.

The tech industry's unofficial dictionary just dropped! Someone's taking a satirical jab at outsourcing with these "alternative" definitions. Instead of Artificial Intelligence, APIs, and GPT, we get the Mumbai edition. Gotta love how GPT went from "Generative Pre-trained Transformer" to "Gujarati Professional Typist." Next time your manager brags about implementing AI solutions, just ask "Which part of India are they from?" The outsourcing jokes never get old... unlike the legacy code we're all maintaining.

Ah, the irony of modern tech! Here's a vintage book teaching "Artificial Intelligence in BASIC" from what looks like the 80s, sitting right next to "EXPERT SYSTEMS" on the bookshelf. Fast forward to 2023, and we're all losing our minds over ChatGPT and friends—billion-dollar AI systems built on Python, a language that would make your CPU cry if you asked it to calculate 2+2 in less than half a second. The cosmic joke is that we've gone from programming AI in languages designed to be "Beginner's All-purpose" to building world-changing models with a language where indentation errors can crash your entire system. Somewhere, this book's author is either laughing hysterically or weeping uncontrollably.