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Articole: 34
  1. Inventing Transformers

    A branching tech tree of the Transformer: the path of innovations from 2012 to 2017 - AlexNet, Word2vec, Attention, ResNet and more - drawn as glowing nodes on a skill-tree diagram, each one unlocking the next on the way to the architecture behind modern…

  2. The Myth of Deterministic Software

    How I've come to terms with LLM non-determinism in software and abandoned the comforting lies we've been telling ourselves about traditional software.

  3. More Thoughts on Falling Surplus

    The feeling of poverty amidst wealth stems from less opportunity to realize surplus.

  4. Rationalism's Lamprey

    How Steve Sailer wormed his way into Silicon Valley's hivemind through Slate Star Codex.

  5. How Claude Changes My Code

    Claude writes all my code now, but the bigger shift is in *what* code I produce.

  6. What's Next for Prompt Injection

    Prompt injection requires training LLMs with robust "untrusted content" primitives, viewing it as a solvable cybersecurity problem distinct from jailbreaking.

  7. Don't Compensate with Equity

    It is in startups' interest to pay employees cash and save their equity to sell to VCs.

  8. Boldness Alone is no Virtue

    Silicon Valley backs Trump for "bold action," because America's problems require it.

  9. Why Everyone Feels Poor

    Why do rich Americans feel poor?

  10. I built a new prompt injection benchmark for AI agents because the existing ones are not great.

  11. USENIX Security '25 Round-up

    USENIX Security '25 roundup on LLM security topics: prompt injection, data leaks, CAPTCHA bypasses, and model misbehavior.

  12. Searle's Sleight-of-Hand

    The Chinese Room argument is flawed because it ignores the practical speed and scale of computation, misguiding our intuition about AI intelligence.

  13. Prompt injection, where untrusted input overrides LLM system instructions, is a hard problem with no reliable defenses yet.

  14. LLMs display "generalized intelligence," yet research lacks a theoretical explanation for their capabilities, how they work, or their inherent limitations, and there is no clear path to fixing this.

  15. AI and the Future Economy

    AI's economic future is debated.

  16. Understanding Transformers

    Writing stuff down about the Transformer architecture and training methods to solidify my own understanding.

  17. Democrats Lost, What's Next?

    Democrats lost due to inflation & immigration.

  18. Israel/Palestine

    Israel holds nearly all power in the conflict.

  19. Satoshi's Mistake

    Satoshi's Bitcoin, intended for freedom, has failed to realize Finney's ambitions and instead empowered global crime, scams, and human trafficking.

  20. AI and the Future of Work

    AI will transform work, replacing some jobs & enhancing others, but its crucial impact lies in the "signaling problem," where AI-generated content devalues human competence.

  21. A Machine for Burning Cities

    "Nuclear" bombs aren't all equal.

  22. How to project SaaS user growth?

  23. In Blockchain We Trust

    Blockchains promise "trustless" transactions, but they actually require new forms of trust in value and network security, making them vulnerable to major attacks.

  24. Electronic Health Records (EHRs) harm patient care & raise costs due to bad design, lack of interoperability, and government mandates.

  25. A Front-End Debugging Adventure

    Debugging a front-end Firefox bug: A double-click race condition caused `mousedown` to overwrite an element's reference before `mouseup` could remove it.

  26. What Mathematics has Lost

    Mathematicians often fail to share the human intuitions behind their work, leading to a profound loss of understanding, exemplified by Mirzakhani's death.

  27. Please Lie

    Fight back against pervasive surveillance & exploitative algorithms: lie about your data to disrupt models that stereotype, entrench poverty, and reinforce corporate power.

  28. The Cult of Averages

    We often think in terms of the mean even when this is ill-defined.

  29. Lessons from Milo

    Violent protests against Milo Yiannopoulos ironically did his work for him.

  30. Against AI Risk

    Grey goo scenarios obscure the more imminent and likely risks: military AI, inequality-fueling tech, and other powerful tools society already struggles to control.

  31. Analyzing the Effects of Voting

    An individual vote has never tipped an important election, so why vote?

  32. You Are Probably Misusing Opacity

    Designers often misuse opacity for text, leading to unreadable stacking effects and CSS bugs like new stacking contexts.

  33. Towards Universal HTTPS Adoption

    Why is HTTPS adoption so slow?

  34. Django is Dangerous

    This post argues Django is dangerous due to fundamental flaws in data integrity and dynamic templating that worsen as projects scale.