Reflecting on ML's Rise and the Shift in Open Source Culture
_onionesque · x · 2026-07-20
The author reviews the development history of the machine learning field, noting that AI's takeoff around 2011-2013 was largely attributed to the highly open and easily reproducible academic culture at the time.
However, from 2018 to 2021, a massive "scramble" for resources and technologies emerged in the industry, leading to today's controversies over closed-source AI. Furthermore, the scaling potential demonstrated by GPUs in early feedforward models, along with post-financial-crisis stimulus funds, were also key factors driving AI's accelerated development.
Related event: Open Models Act as Accelerators, Not Decelerators(9 posts)→
More from AGI Musings
- Microsoft's reported 60,000 voluntary exits spark essay asking who AI is really for — _jaydeepkarale · 2026-10-27
- PHP2Shell exploits confirmed in the wild, attackers may use agentic AI for post-exploitation — AravSrinivas · 2026-10-27
- LukeW: Technology Limits Are Temporary — and AI Skeptics Are Already Feeling It — LukeW · 2026-10-27
- GiveDirectly pilots an optional AI chatbot alongside cash aid in Rwanda — NathanpmYoung · 2026-10-27
- Ex-Anthropic employee essay: the org optimizes for power 'constrained by being seen as the good guys' — RichardMCNgo · 2026-10-27
- Investor: model version numbers are a mirage, only datacenter margins are real — StewartalsopIII · 2026-10-27