무슨 발표인가
- FLOPS(초당 부동소수점 연산)로 컴퓨트 성능 측정
- Muse Spark 기반 Meta AI가 음성 질의에 응답
- 음성→텍스트 변환 후 서버 라우팅 과정
원문 (영어)
Imagine you’re visiting a new city and want to find a restaurant that impresses your vegan in-laws. Using voice conversations on the Meta AI app, you ask, “Hey Meta, what are the best vegan options around?” Within seconds, Meta AI — powered by Muse Spark — responds with a list of local vegan restaurants, a short description of each restaurant’s vibe, and a map showing you exactly where the restaurants are.
It’s a quick and seamless interaction that feels effortless, but behind that brief exchange are layers of calculations enabled by compute power. What Is Compute Power? Simply put, compute power is the measure of how much work a computer chip can do and how fast it can do it — like horsepower in a car engine.
Compute power is measured in FLOPS: floating-point operations per second, or the number of calculations that a chip can perform in one second. FLOPS measure the speed of compute and gigawatts measure the scale of it, or how many chips you can keep running at once.
When you ask Meta AI to find a vegan restaurant, it runs billions of calculations in just a few seconds. Your voice is captured, converted from sound waves into text, and routed to computers or servers inside a data center . From there, a large language model (LLM), and the result is delivered right to your ear.
Even simple actions, searching for a local barbershop on Instagram, require layers of computation: understanding language, processing your query, scanning an index, generating results, and delivering it back to you, all before your thumb leaves the screen.
All of this processing power is made possible by processing chips inside the servers inside our data centers. So why does the future of AI depend on compute? Here’s a closer look.
원문: Meta Newsroom — "What Is Compute Power? Meta's AI Infrastructure Explained" (2026-06-16) 공식 원문: https://about.fb.com/news/2026/06/what-is-compute-power-meta-ai-infrastructure/
