There is an old Silicon Valley warning that the AI industry should probably take more seriously: โ๐๐ณ ๐๐ผ๐ ๐ฎ๐ฟ๐ฒ ๐ผ๐ป ๐๐ต๐ฒ ๐๐ฟ๐ผ๐ป๐ด ๐ฝ๐ฎ๐๐ต ๐๐ผ ๐๐๐, ๐ด๐ฒ๐ ๐ผ๐ณ๐ณ ๐ฎ๐ ๐๐ผ๐ผ๐ป ๐ฎ๐ ๐๐ผ๐ ๐ฐ๐ฎ๐ป. ๐ง๐ต๐ฒ ๐น๐ผ๐ป๐ด๐ฒ๐ฟ ๐๐ผ๐ ๐ฏ๐ฒ๐น๐ถ๐ฒ๐๐ฒ ๐๐ต๐ฎ๐ ๐๐ฐ๐ฎ๐น๐ถ๐ป๐ด ๐น๐ฎ๐ฟ๐ด๐ฒ ๐น๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐บ๐ผ๐ฑ๐ฒ๐น๐ ๐๐ถ๐น๐น ๐ด๐ฒ๐ ๐๐ผ๐ ๐๐ต๐ฒ๐ฟ๐ฒ, ๐๐ต๐ฒ ๐ณ๐๐ฟ๐๐ต๐ฒ๐ฟ ๐๐ผ๐ ๐ฑ๐ฟ๐ถ๐ณ๐ ๐ณ๐ฟ๐ผ๐บ ๐๐๐, ๐ฎ๐ป๐ฑ ๐๐ต๐ฒ ๐บ๐ผ๐ฟ๐ฒ ๐ฒ๐ ๐ฝ๐ฒ๐ป๐๐ถ๐๐ฒ ๐๐ต๐ฒ ๐ฐ๐ผ๐๐ฟ๐๐ฒ ๐ฐ๐ผ๐ฟ๐ฟ๐ฒ๐ฐ๐๐ถ๐ผ๐ป ๐๐ถ๐น๐น ๐ฏ๐ฒ.โ And that may be the bigger point. Not just whether LLM scaling reaches AGI. But whether the worldโs smartest companies are becoming incredibly efficient at going faster in the wrong direction. #technology #ai #workplace Image credit: Ralph
โ View original post on X โ @pascal_bornet, 2026-03-30 09:00 UTC
