Top all-time · #5856
Neil Lawrence
Personal blog · inverseprobability.comaidata
Neil Lawrence's personal blog at inverseprobability.com covers ai and data. Since 2015, 14 different Hacker News readers have linked it 16 times, most often “Future of AI VI. Discussion of 'Superintelligence: Paths, Dangers, Strategies'”. It is still writing: the last post was on 2026-07-21, and you can follow it by feed.
Too few sampled comments (4) to say how often HN recommends it.?
Why HN links it
HN readers link Neil Lawrence's blog for a critique of Bostrom's book on AI risk. Other comments discuss ML peer review and publishing but do not assess his posts.
Summarised by Claude from a sample of 4 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
My webpage
Most-linked posts?
- Future of AI VI. Discussion of 'Superintelligence: Paths, Dangers, Strategies'3 people · 3 mentions · first linked 2016-05-09
What Hacker News says?
As a grad student (ML) close to finishing I can say exactly what I want. I want to read math books, program, and publish slowly (papers + blogs) with meaningful and substantial work. I do not want to be chasing benchmarks or worrying about how to play the politics of paper publishing to get through the provably random[0][1][2] noise that is the review process. But no one is going to pay me for this, including academ…
Comment linking /talks/notes/the-neurips-experiment-snsf.html
on “Graduate students question career options”Submitted ML Futures (Bostrom refutation) as a story · 4 points
HN discussionHere is a very good critique of Bostrom's book: http://inverseprobability.com/2016/05/09/machine-learning-fu...
Comment linking /2016/05/09/machine-learning-futures-6
on “What’s Next for Artificial Intelligence”Submitted Future of AI VI. Discussion of 'Superintelligence: Paths, Dangers, Strategies' as a story · 4 points
HN discussion> paper reviewers are usually not supposed to look at the actual source code of the papers Wait what? I haven't reviewed for ACL but most conferences don't say "don't look at the source code." They will say that reviewers are not required to look at it (as well as the appendix). But generally it just isn't uploaded. I do always look at the main method when it is there but talking to my peers and advisor, this is ver…
Comment linking /talks/notes/the-neurips-experiment-snsf.html
on “Bad numbers in the “gzip beats BERT” paper?”Submitted Discussion of Nick Bostrom's Superintelligence: Paths, Dangers, Strategies as a story · 3 points
HN discussionHonestly, these complaints (other than 4) apply to the vast majority of papers. #4 is just false. It has already been viewed by other lab members (peers) and open publication is peer reviewing. The "peer review system" (publishing to conferences/journals) is relatively new and I think ML demonstrates all the problems with the system (yay hype). Novelty is especially a joke. ViTs are "just" NLP encoding transformers.…
Comment linking /talks/notes/the-neurips-experiment-snsf.html
on “Unlimiformer: Long-Range Transformers with Unlimited Length Input”Submitted This House Believes an Artificial Intelligence Will Benefit Society as a story · 3 points
HN discussionSubmitted AI and ML Futures 3: The Trojan Wars of Machine Learning as a story · 3 points
HN discussionSubmitted The Trojan Wars of Machine Learning as a story · 2 points
HN discussionSubmitted Post NIPS Reflections as a story · 2 points
HN discussionSubmitted Data Readiness Levels as a story · 1 points
HN discussionSubmitted Don't Panic: Deep Learning Will Be Mostly Harmless as a story · 1 points
HN discussionSubmitted New directions in kernels and gaussian processes as a story · 1 points
HN discussionSubmitted Deep Learning, Pachinko, and James Watt: Efficiency Is the Driver of Uncertainty as a story · 1 points
HN discussionSubmitted Neil Lawrence: Baidu and the Imagenet Challenge as a story · 1 points
HN discussion
