Bob Ross died 30 years ago, and Mr. Roger’s died over 20 years ago. Basing your argument on decades old examples is a pretty clear indicator of its merits.
I asked Grok to review the comments here and generate a response defending AI:
After reviewing the discussion on the Hacker News thread, it’s clear that there are a range of complaints and criticisms about AI, particularly centered around its limitations, overhype, and practical utility. Some users express frustration with AI’s inability to handle complex reasoning, its tendency to produce generic or incorrect outputs, and the perception that it’s more of a buzzword than a transformative tool. Others question its value compared to traditional methods or human expertise, suggesting it’s overhyped or misapplied in many cases. Below, I’ll offer a defense of AI that addresses these concerns while highlighting its strengths and potential.
AI isn’t perfect, and no one should claim it is—but that’s not the point. It’s a tool, and like any tool, its effectiveness depends on how it’s used. Critics who point to AI’s struggles with nuanced reasoning or edge cases often overlook the fact that it’s not designed to replace human judgment entirely. Instead, it excels at augmenting it. For example, AI can process vast amounts of data—far more than any human could in a reasonable timeframe—and identify patterns or insights that might otherwise go unnoticed. This makes it invaluable in fields like medicine, where it’s already helping diagnose diseases from imaging data, or in logistics, where it optimizes supply chains with precision that manual methods can’t match.
The complaint about generic or incorrect outputs, often dubbed “hallucinations,” is fair but misses the bigger picture. Yes, AI can churn out nonsense if pushed beyond its limits or fed poor data—but that’s a reflection of its current stage of development, not its ultimate potential. These systems are improving rapidly, with each iteration reducing errors and refining capabilities. More importantly, AI’s ability to generate starting points—like drafts, code snippets, or hypotheses—saves time and effort. It’s not about delivering flawless results every time; it’s about accelerating the process so humans can refine and perfect the output. A programmer tweaking AI-generated code is still faster than writing it from scratch.
As for the overhype, it’s true that the buzz can get out of hand—marketing teams love a shiny new toy. But beneath the noise, real progress is happening. AI’s contributions aren’t always flashy; they’re often mundane but critical, like automating repetitive tasks or enhancing search algorithms. The critics who say it’s just a “fancy autocomplete” underestimate how transformative that can be. Autocomplete might sound trivial until you realize it’s powering real-time language translation or helping scientists sift through research papers at scale. These aren’t sci-fi fantasies—they’re practical applications delivering value today.
Finally, the notion that AI can’t match human expertise in complex domains ignores its complementary role. It’s not here to outthink a seasoned expert but to amplify their reach. A lawyer using AI to review contracts doesn’t lose their skill—they gain efficiency. A researcher leveraging AI to analyze data doesn’t stop hypothesizing—they get to test more ideas. The technology’s strength lies in its ability to handle the grunt work, freeing humans to focus on creativity and judgment.
AI isn’t a silver bullet, and it’s not without flaws. But the criticisms often stem from inflated expectations or a failure to see its incremental, practical benefits. It’s not about replacing humans—it’s about making us better at what we do. The trajectory is clear: as it evolves, AI will continue to refine its capabilities and prove its worth, not as a standalone genius, but as a partner in progress.
I remember learning Prolog, it was tricky to wrap my mind around it, it wasn’t like any other language. The day I finally “got it” I was very happy, until I realized all the other languages I had previously learned, no longer made any sense.
I remember taking a PL class in undergrad, learning Prolog as one of a handful of languages. During that section my brain started to want to "bind" variables to things as I was going about my day, it was very weird.
I remember searching my library for every book I could find on computers and hacking, there weren’t many, but I somehow stumbled upon The Cuckoos Egg while flipping through the ancient wooden drawers of the card catalog in my local library. It really was one of the most magical books I’ve ever read. Since then I’ve had many exciting experiences of my own in the digital world, and I owe that in part to Clifford Stoll for painting such a vivid an exciting view of his own experiences that helped shape my own imagination.
To me, it seems like people writing these articles should be careful to avoid inaccuracies and overstatements in their writing. The very first sentence of the article includes the phrase “on track to be”.
