v: AI Psychosis + the Great New Hope
AI fatigue is real—recent model releases were enough to discourage even senior devs and luminaries in the space. But once the dust settles, a case emerges that AI progress looks more like a sigmoid than an exponential, and that there are too many incentives for AI companies to appear more successful than they really are. We explore those theories.
We are all a bit fatigued by AI, and the latest models were enough to get some senior devs and luminaries in the space discouraged on X the other day. But once that subsides, a different picture comes into focus: there are many theories that make this look like a sigmoid rather than exponential growth. There are too many reasons for AI companies to seem more successful than they really are—and we explore those today.
Topics Covered
- Why AI fatigue set in, and what the recent model releases actually delivered
- The case for sigmoid (S-curve) growth over runaway exponential progress
- The incentives that push AI companies to appear more successful than they are
- Where the “great new hope” might actually come from—human-first, technology-second
Links & Resources
- Ossa — a local-first, Google Photos alternative
- Erikk Shupp on X
- Erikk Shupp on Medium
- Humans Only (Podcast)
- Thoughtful App Co
This is Humans Only. I’m Erikk Shupp.