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

爱范儿
爱范儿
P
Palo Alto Networks Blog
月光博客
月光博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More
I
InfoQ
aimingoo的专栏
aimingoo的专栏
腾讯CDC
T
Threatpost
D
DataBreaches.Net
Vercel News
Vercel News
F
Fortinet All Blogs
Engineering at Meta
Engineering at Meta
C
Cybersecurity and Infrastructure Security Agency CISA
Forbes - Security
Forbes - Security
U
Unit 42
C
Check Point Blog
Blog — PlanetScale
Blog — PlanetScale
O
OpenAI News
量子位
TaoSecurity Blog
TaoSecurity Blog
Microsoft Azure Blog
Microsoft Azure Blog
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
V
Visual Studio Blog
Recorded Future
Recorded Future
云风的 BLOG
云风的 BLOG
Security Archives - TechRepublic
Security Archives - TechRepublic
The Last Watchdog
The Last Watchdog
S
Security Affairs
Attack and Defense Labs
Attack and Defense Labs
罗磊的独立博客
Stack Overflow Blog
Stack Overflow Blog
Microsoft Security Blog
Microsoft Security Blog
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
V
V2EX
小众软件
小众软件
S
SegmentFault 最新的问题
www.infosecurity-magazine.com
www.infosecurity-magazine.com
W
WeLiveSecurity
AI
AI
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
博客园 - 聂微东
I
Intezer
Know Your Adversary
Know Your Adversary
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
P
Proofpoint News Feed
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
The Cloudflare Blog
博客园_首页
NISL@THU
NISL@THU
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. Adam/papers/emergent_values_whitepaper.md at master · strangeadvancedmarketing/Adam Ask HN: How do you stop playing 20 questions with your AI coding tools How far can automation and AI support psychotherapy? - @theU GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits A Mac Studio for Local AI — 6 Months Later A History of the Early Years of AI at the University of Edinburgh Why AI Coding Tools Still Feel Stuck on Localhost MSN AI Datacenters Are Becoming Strategic Targets twitter.com Penn Researchers Use AI to Surface Unreported GLP-1 Side Effects in Reddit Posts Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 AI models are terrible at betting on soccer—especially xAI Grok GitHub - xialeistudio/echoic GitHub - HimashaHerath/github-dev-wrapped: AI-powered weekly GitHub activity reports deployed to GitHub Pages GitHub - alejandrobalderas/claude-code-from-source: Architecture, patterns & internals of Anthropic's AI coding agent — reverse-engineered from source maps AI and Tech brief: Ireland ascendant GitHub - Titovilal/context0: Context0 - Never Surrender Training for a Marathon with an AI Coach: What Worked and What Didn't Cyber Pulse: Agentic Intel - Apps on Google Play I Built an AI PR Reviewer That Catches Bugs by Not Looking for Bugs Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout | Fortune How AI Is Reimagining the Game of Golf–For Both Players and Courses GitHub - nattergabriel/reseed: A CLI tool for managing and distributing agent skills across projects Is SVG the final frontier? My AI workflow evolved from prompts to a near-autonomous workflow MLSharp Help - 3DGS Viewer & Generator I put my cognitive field based AI's runtime on GitHub Is Numble the first AI-proof game? A3: Kubernetes for autonomous AI agent fleets | Emergent Principles Deepali Vyas ("The Elite Recruiter") GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Unionized ProPublica staff are on strike over AI, layoffs, and wages Unleashing the Advantage of Quantum AI We're heading for an AI-fueled 'dementia crisis,' brain scientist warns The AI-Assisted Breach of Mexico's Government Infrastructure [pdf] GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. How to Build a Secure AI PR Reviewer with Claude, GitHub Actions, and JavaScript This Startup Wants You to Pay Up to Talk With AI Versions of Human Experts Intel Arc Pro B70 Brings 32GB VRAM to Local AI for $949 WordPress 7.0: The Good, the AI, and the Still Missing AI on the couch: Anthropic gives Claude 20 hours of psychiatry IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures AI Agents Know About Supabase. They Don't Always Use It Right. The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
History Rhymes
Gokul Kannan · 2026-06-25 · via Hacker News - Newest: "AI"

My six-year-old is at that stage of his life where he tries to find words which rhyme. As I was thinking about this post, I blurted out, “History rhymes”.

He asked, “Rhymes with what?”

I said “It rhymes with history.”

He said, unimpressed, “Dad. That’s the same word.”

I leant back on my chair, took a deep breath and sighed, “Son, that is the travesty of it”.

Irked, he replied “Tra-ves-ty? That does not rhyme either!”

It is May 24, 1844. Alfred Vail taps out a message and sends it sixty miles down copper wire. Samuel Morse receives it and taps the same words back: “What hath God wrought”. Prior to this, the invention of telegraph, the fastest a message could travel was the speed of a horse.

Western Union strung telegraph wire across an entire continent. Its valuation grew from $385,000 in 1858 to $41 million by 1876. To put that in perspective: when the U.S. government bought the entire territory of Alaska from Russia in 1867, it cost $7.2 million. Within a decade, Western Union was worth nearly six Alaskas. The press crowned it the inevitable master of the age.

Western Union Telegraph Office | History In Living Color

And yet. For every $1 of value created by Western Union, the businesses that used those telegraph wires created roughly $50. Railroads coordinated schedules across thousands of miles. Brokers routed orders to the NYSE. The Associated Press was born to fill those wires with words and sell them to a news-hungry nation.

Western Union built the miracle. Everyone else cashed in on it.

But the very railroads that made Western Union rich were about to play the same subordinate role for someone else.

Railroad stocks and bonds totaled $2.5 billion in 1871. By the early 1900s, $20 billion. The press crowned railroads the inevitable masters of the age.

Then a former bookkeeper from Cleveland looked at the tracks and saw something different.

John D. Rockefeller was not interested in laying iron rail; he was interested in the leverage of what moved along it. He negotiated railroad shipping rates so aggressively, that his competitors could not match his prices even if their refineries were inherently more efficient. By 1890, Standard Oil’s assets exceeded $100 million. By 1912, it became the first company in history valued at over $1 billion, when the entire stock market was worth $16 billion.

The telegraph was infrastructure; the railroad exploited it. The railroad was infrastructure; Standard Oil exploited it. History doesn’t repeat. But God, does it rhyme.

But the chain didn’t stop at Standard Oil. It seldom does.

Standard Oil built the massive distribution network of refineries, pipelines, and storage tanks. That fuel distribution network became the infrastructure that allowed the automobile industry to scale. Ford and GM became the giants of the next era. The highways built to move those cars became the infrastructure for an entirely new economy: McDonald’s at every exit ramp, Walmart in every mid-size town, FedEx connecting it all overnight. None of them built the highways. They just understood them better than anyone else.

Many winners eventually became the next era’s infrastructure, often without realizing it. And at each turn, the press was busy crowning the current winner the inevitable master of the age.

AOL reached $222 billion in 1999, the 4th largest company in the United States, behind only Microsoft, GE, and Cisco. The AOL-Time Warner merger closed at $350 billion, the largest deal in history at that point. Whoever owns the pipe owns the century, they said. The pipe became a commodity. Google is worth $4 trillion. Amazon approaches $3 trillion. AT&T, Verizon, and Comcast combined: $400 billion. Less than a tenth of what was built on top of their pipes.

This time, the infrastructure builders seemed to have read the history. Google, Microsoft and Amazon climbed the stack deliberately, capturing enormous value not just as pipe-layers but as application builders. AWS, Azure, and Google Cloud together generate over a quarter-trillion dollars a year, growing at 18-30% annually. It looked like they had finally cracked it, infrastructure that also captured the application layer.

And yet. Google had DeepMind. It had the best AI researchers in the world. Google researchers published the Transformer architecture in 2017. All the ingredients were there.

Instead, two hyper-focused startups moved fastest. As of mid-2026, Anthropic’s annualized revenue run rate has crossed $47 billion, and OpenAI’s stands at roughly $33 billion. Both numbers are moving so fast that they may already be out of date by the time you read this. They are barely five years old, growing faster than the cloud ever did.

The model makers also seem to be learning from history and climbing up the stack. But like we saw with the cloud providers, even when you know the history and act deliberately, surprises still emerge. Time and again, infrastructure builders have enabled others to create enormous value on top of their platforms.

The innovator’s dilemma may be less a law of business than a recurring temptation.

Today, the press is crowning the model makers the inevitable masters of this age. The question everyone is asking: who will win AI? This is probably the wrong question. It assumes the chain stops here. But history suggests it never has.

The right question probably is: what is AI enabling that we cannot yet see? Who is going to use OpenAI and Anthropic the way they used AWS and Azure’s compute? What company is sitting quietly right now, seeing these models the way Rockefeller saw the railroad, not as the prize, but as the lever? We don’t know yet. What we do know is that OpenAI, Anthropic, and Google are aware of the history. They are building models, and cautiously extending into applications. But their primary bet is still on the model layer. History suggests the biggest winner may not be any of them. It will be whoever picks up these models and does to an industry what Rockefeller did to oil. But rarely have the incumbents been this aware of the trap or this well armed to escape it.

The jury is still out.

My son recently pointed out that mystery rhymes with history. He’s right. It does. I’ll let him figure out what rhymes with future.

Maybe you can help.

Inspirations/References:
  1. Americana by Bhu Srinivasan

  2. Chris Davis interviewed by Barry Ritholz

  3. Story of Google by Acquired

  4. Alchemy by Rory Sutherland

  5. Rockefeller by David Senra

Discussion about this post

Ready for more?