惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Apple Machine Learning Research
Apple Machine Learning Research
博客园_首页
G
Google Developers Blog
aimingoo的专栏
aimingoo的专栏
罗磊的独立博客
博客园 - 【当耐特】
M
MIT News - Artificial intelligence
D
Docker
博客园 - 三生石上(FineUI控件)
博客园 - 司徒正美
人人都是产品经理
人人都是产品经理
博客园 - 叶小钗
月光博客
月光博客
S
SegmentFault 最新的问题
Jina AI
Jina AI
Blog — PlanetScale
Blog — PlanetScale
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - Franky
L
LangChain Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Microsoft Azure Blog
Microsoft Azure Blog
阮一峰的网络日志
阮一峰的网络日志
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Last Week in AI
Last Week in AI

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
Re: If AI Existed in 2011, Would We Still Have the Modern...
TyIsI · 2026-04-24 · via DEV Community

TyIsI

Below is a comment I left on @sylwia-lask's post If AI Existed in 2011, Would We Still Have the Modern Web?, which I thought warranted its own post.

Disclaimer on this post: I'm a general cynic with very strong decolonial tendencies. As such, I'm very cynical about "ai" in general, and especially how humanity and conversely capitalism will use it. Please keep that in mind as you read the rest of this post below.


Disclaimer: I'm not a fan of "ai" because of a lot of reasons, but most of all because it's essentially really advanced T9/Markov chains on steroids and because a lot of people who drink the koolaid seem to forgo critical thinking. So if there's disdain in my tone, you're absolutely right. However, this disclaimer is relevant and I am going to respond in-depth.

You touch on exactly the core of "ai".

Because the inconvenient truth is that "ai" has a knowledge horizon problem, and much like how the human brain works, its inherent internal statistical model and inference models merely improve on statistical connections between the internal vectors.

In human terms and as you already mentioned, "ai" favours the most common/valued paths.
Consequently, when an "ai" engine does not have a common path, it will try to extrapolate a solution, which leads to modelling outputs that resemble existing acceptable paths/patterns.
I.e. "ai" hallucinates!

One of the other challenges here is that the way we've trained "ai" implementations/models, has always been focused around externally controlled input. Or in other words, we pre-chewed the input for the machine. We gave it baby food. And because of that, to my best understanding at least, "ai" does not have a fundamental understanding of the more relationships between different concepts.

"ai" knows how to express a mathematical function and "ai" can (re)produce functions but does not have a more fundamental understanding of what E=MC2 than you or I do beyond that it statistically has to do with the speed of light.

Now... With all of that said...

I think the "ai" companies let the "genie" out of the box too soon. Because money needed to be made. I don't think humanity was ready for "ai".

I think that if current day "ai" was transported to 2010 or even 2000, it would've stifled progress. Because like you and others said... It just optimizes what exists and without money driving the need to progress and innovate, I don't believe that creativity would have come to this point.

Maybe some hackers would... But that lands me to the point of my disclaimer...
The magic thinking machines that is "ai" also seems to inhibit critical thinking.

If "ai" was more mature, then maybe. But looking at how management is already wooed by current "ai" and looking at the current state of "civilization", I have a really hard time seeing how "ai" would make a positive change at any point in the past.

Because after all, doesn't programming distill to a lot of below but repeated ad-nauseum?

result = do_thing

if result == condition 
  do_that_thing
else if result == condition
  do_other_thing
else
  do_some_thing

Enter fullscreen mode Exit fullscreen mode

Which drives home that "ai" as really advanced T9 is great at repeating things.
But "ai" can't synthesize that.

So we need to create content for "ai" to ingest, but if it can't synthesize and distill the underlying fundamentals, progress will always be restricted by our dependency on "ai".

And colonialism/capitalism says that progress isn't as important as making money.

So I have a hard time believing that we'd do better 10 or 20 years before than we do currently.
There's just more content "ai" could be trained on right now.

Just my 2 cents.