A Hitchhiker's Guide to the AI Bubble
SMRTR summary
The hum of a coffee machine and the tap of a keyboard. A veteran programmer, dormant for over a decade, suddenly builds complex systems in unfamiliar languages within weeks. This quiet resurrection is happening across the tech landscape as artificial intelligence becomes what one developer calls "boring infrastructure."
"The old timers who built the early web are coding with AI like it's 1995," notes Stanford lecturer Christina Wodtke. "When developers who've seen every tech cycle since Gopher start acting like excited newbies, that tells you something."
While headlines scream about an "AGI arms race" and governments pour billions into computational supremacy, the real revolution is occurring at ground level. AI capabilities that once required PhD teams and custom hardware now come as standardized APIs costing pennies.
Prices tell the story: GPT-3 cost $60 per million tokens in 2020. Today, GPT-3.5 costs just 7 cents for the same processing.
The transformation extends beyond coding. Non-English speakers across Asia communicate professionally at native levels. Students integrate AI naturally into learning. Everyday tasks from cooking to analysis become expertise-on-demand.
The bubble of artificial general intelligence may eventually pop, but the infrastructure will remain – just as the internet survived the dot-com crash, leaving behind a foundation that changed everything.
SMRTR provides this summary for quick context. The original article belongs to Hacker News.
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