- The Oxford-based Future of Humanity Institute (FHI) has permanently closed; participants attribute the shutdown to a 2020 hiring freeze, non-renewed contracts, and reputational damage to Effective Altruism after the SBF fraud scandal, with some arguing the group’s “doomerism” stance ultimately worked against humanity’s future.  
- FHI’s self-published “Final Report” was criticized for its extremely brief “Where we failed” section, which focused on internal academic politics (poor communication, lack of cross-department influence, insufficient paper output) rather than substantive reflection on the institute’s intellectual direction.  
- Participants debated whether academia’s “publish or perish” culture is inherently hostile to long-term, high-risk research, while acknowledging that institutes on university funding must still play the incremental-publication game.  
- A collection of recent articles and blog posts were shared to advance the case for biological enhancement and intelligence amplification:  
  – “The Case for Biological Enhancement” (Ad Profectum Substack)  
  – “A Model of Intelligence” (ThinkingComplete, 2018)  
  – “The Biosingularity Is Near” (Nooceleration)  
- Technical papers on evolutionary and developmental approaches to strong amplification of natural selection and innate ability encoding were highlighted:  
  – “Construction of arbitrarily strong amplifiers of natural selection using evolutionary graph theory” (Nature Communications, 2018)  
  – “Complex computation from developmental priors” (bioRxiv, 2021)  
  – “Encoding innate ability through a genomic bottleneck” (bioRxiv, 2021)  
- Revisiting a 2014 DIY wiki page on “human-like cognitive abilities,” participants noted that the requirement to run on “commodity computing hardware” was ultimately vindicated when ImageNet-level performance became affordable on sub-$2,000 GPUs.  
- The “bitter lesson” was invoked to argue that large-scale pre-training, not hand-crafted design, is the dominant path to AI capability gains, challenging earlier assumptions about avoiding “impossibly huge” compute.