The hottest Prediction Substack posts right now

And their main takeaways
Top Technology Topics
Astral Codex Ten β€’ 8534 implied HN points β€’ 05 Mar 24
  1. The Annual Forecasting Contest on involves participants making predictions about various questions, helping to determine if one identifiable genius or aggregated mathematical predictions work best for foreseeing the future.
  2. The winners of the contest were both amateurs and seasoned forecasting veterans, showcasing a mix of skill and luck in predicting outcomes.
  3. Metaculus outperformed prediction markets, superforecasters, and the wisdom of crowds in the contest, suggesting that consistent high performance might be rare but achievable with specific methods like those used by superforecaster Ezra Karger.
Meaningness β€’ 79 implied HN points β€’ 31 Mar 24
  1. Opinions about AI future are often based on feelings rather than evidence or rational reasoning.
  2. Predicting AI future using Bayesian probability can be unreliable due to the initial framing of the problem and personal biases.
  3. Understanding the risks and opportunities of AI requires acknowledging uncertainty and taking pragmatic measures while considering the impact on culture and society.
Hardcore Software β€’ 569 implied HN points β€’ 06 Jun 23
  1. Most new products in the market tend to fail, so predicting failure can be a way to gain social status.
  2. Predicting failure of new products has always been popular and attention-grabbing throughout different eras.
  3. Success in launching a new product heavily depends on navigating risks and uncertainties, making predicting success challenging.
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Axial β€’ 7 implied HN points β€’ 17 Feb 24
  1. Natural products and drugs have similarities but drugs are a balance between complexity and accessibility for optimization.
  2. Molecular complexity in drugs is increasing to improve IP coverage, binding affinity, and effectiveness for chronic diseases.
  3. Embracing enabling methods, computational modeling, and deep exploration of complex chemical space can revolutionize natural product synthesis for therapeutic goals.
Never Met a Science β€’ 38 implied HN points β€’ 02 Oct 23
  1. Scientific knowledge of social media platforms needs constant updating due to their fast-changing nature.
  2. The traditional scientific method may not be sufficient for studying rapidly evolving subjects like social media platforms.
  3. There is a need for meta-scientific improvements in how we approach research and knowledge synthesis.
The End of Reckoning β€’ 58 implied HN points β€’ 18 Jul 23
  1. There is still no reliable way to detect lies in large language models.
  2. Probing the beliefs of language models is challenging due to limited behavioral evidence and an opaque internal structure.
  3. The debate on whether language models have beliefs is still ongoing, with contrasting views on the necessity of beliefs for these models.
Notices to three friends β€’ 1 implied HN point β€’ 01 Dec 23
  1. The halting problem in computer science cannot be solved because of the limitations of predicting a program's behavior.
  2. Prophecy and prediction face conceptual limitations due to the inability to fully control or predict the future.
  3. The connection between the halting problem and prophecy reveals insights about self-understanding, unpredictability, and the quest for knowledge.
Joshua Gans' Newsletter β€’ 0 implied HN points β€’ 15 Mar 24
  1. Quality jump in AI prediction is essential for driving system change. This improvement can happen in traditional prediction areas.
  2. AI transformation can be sparked by innovative startups like BeforePay. Such examples demonstrate the potential for AI to bring about significant changes.
  3. Global discussions and publications, like a bimonthly column in The Korean Herald, can shed light on the impact of AI on various systems worldwide.