Andrej Karpathy on AI efficiency
From Andrej Karpathy on Future Of AI, LLM OS, and Building Ecosystems · · Perfology Clips
“I think there's still like a massive gap in just the energetic efficiency of running all this stuff. So my brain is 20 watts roughly. Jensen was just talking at GTC about you know the massive supercomputers that they're going to be building. Now these are the numbers are in mega megawws right and so maybe you don't need all that to run like a brain. I don't know how much you need exactly, but I think it's safe to say we're probably off by a factor of a thousand to like a million somewhere there in terms of like the efficiency of running these these models.”
On , Andrej Karpathy, Independent AI Researcher and Former Director of AI at Tesla/Independent, spoke about AI efficiency during Andrej Karpathy on Future Of AI, LLM OS, and Building Ecosystems on Perfology Clips.
About Andrej Karpathy
Andrej Karpathy has continued to speak publicly about the evolution of software development in the age of large language models. In a June 2025 keynote at the AI Startup School, he described a shift he calls "Software 3.0," where natural language prompts function as programs that direct LLMs, and he argued that LLMs have "flipped the direction of technology diffusion" by making advanced tools available to consumers before corporations or governments. He cautioned that "2025 is the year of agents" was an overstatement, saying "this is the decade of agents" and stressing that "we need humans in the loop." In 2026 appearances, Karpathy revisited the term "vibe coding," which he coined in 2025, and contrasted it with what he now calls "agentic engineering." He said vibe coding is about "raising the floor for everyone" to create software, while agentic engineering is about "preserving the quality bar" of professional software and avoiding vulnerabilities. He stated that he has "never felt more behind as a programmer" despite using agentic tools, and described LLMs as "statistical simulation circuits" rather than animal intelligence, adding that "if you'll yell at them, they're not going to work better." He also suggested that hiring for AI-era roles should involve evaluating candidates on large, real-world projects rather than traditional interviews.