Top all-time · #2551
Shane Legg
Personal blog · vetta.orgaiscience
Shane Legg writes vetta project, a personal blog at vetta.org about ai and science. Since 2007, 33 different Hacker News readers have linked it 41 times, most often “Shane Legg: Machine Super Intelligence (2008) [pdf]”. The last post was in 2012, but the archive is still widely read.
Most-linked posts?
- Shane Legg: Machine Super Intelligence (2008) [pdf]5 people · 5 mentions · first linked 2024-05-09
- /2009/09/monte-carlo-aixi/3 people · 4 mentions · first linked 2010-09-06
- Machine Superintelligence – Dissertation by the founder of Deepmind [pdf]3 people · 3 mentions · first linked 2014-02-03
- Scipy - the embarrassing way to code3 people · 3 mentions · first linked 2008-05-06
- /2011/12/goodbye-2011-hello-2012/2 people · 2 mentions · first linked 2022-02-06
- /publications/2 people · 2 mentions · first linked 2014-01-27
- As many definitions of intelligence as there were experts asked to define it2 people · 2 mentions · first linked 2008-12-18
- /2011/11/aiq/2 people · 2 mentions · first linked 2011-11-27
- DeepMind CoFounder Shane Legg: Tick, tock, tick, tock Bing [2009]2 people · 2 mentions · first linked 2023-05-17
- /2011/12/goodbye-2011-hello-2012/2 people · 2 mentions · first linked 2014-01-28
What Hacker News says?
- nl · 2014-02-19
Shane Legg (one founder of DeepMind, purchased by Google) has written a number of good papers around the "measuring machine intelligence" problem. http://www.vetta.org/documents/Benelearn-UniversalIntelligen... is a pretty good place to start.
Comment linking /documents/Benelearn-UniversalIntelligence-Talk.pdf
on “AI” Submitted SciPy - the embarrassing way to code as a story · 92 points
HN discussionFYI, Shane Legg's theses was "Machine Super Intelligence". http://www.vetta.org/publications/
Comment linking /publications/
on “Google to Buy Artificial Intelligence Startup DeepMind for $400M”Submitted Scipy - the embarrassing way to code as a story · 66 points
HN discussiona backup just in case https://nlp.seas.harvard.edu/annotated-transformer/ https://scottaaronson.blog/?p=762 https://karpathy.github.io/2015/05/21/rnn-effectiveness/ https://colah.github.io/posts/2015-08-Understanding-LSTMs/ https://arxiv.org/pdf/1409.2329.pdf https://www.cs.toronto.edu/~hinton/absps/colt93.pdf https://arxiv.org/pdf/1506.03134.pdf https://proceedings.neurips.cc/paper_files/paper/2012/file/c... https:…
Comment linking /documents/Machine_Super_Intelligence.pdf
on “Ilya Sutskever: “If you learn all of these, you’ll know 90% of what matters””Submitted Shane Legg: Machine Super Intelligence (2008) [pdf] as a story · 60 points
HN discussionShane Legg is a cofounder of DeepMind and an AI researcher. He was pretty casual about predicting human level AGI in 2028. https://www.vetta.org/2011/12/goodbye-2011-hello-2012/ He doesn't say so publicly any more, but I think it is due to people's negative reaction. I don't think he changed his opinion about AGI.
Comment linking /2011/12/goodbye-2011-hello-2012/
on “AlphaCode as a dog speaking mediocre English”Submitted Tick, tock, tick, tock Bing (2009) as a story · 3 points
HN discussionhttp://www.vetta.org/2008/05/scipy-the-embarrassing-way-to-c... ;)
Comment linking /2008/05/scipy-the-embarrassing-way-to-code/
on “Why I Still Use Python for High Performance Scientific Computing”Submitted DeepMind CoFounder Shane Legg: Tick, tock, tick, tock Bing [2009] as a story · 2 points
HN discussionThe call for AI safety has existed since before we broke through the Turing test with LLMs. And I personally wouldn’t call things like code generation or content-generated learning experiences for advanced topics “basic”. Not to mention where we’re headed with multimodal integration. Many have argued for safety for decades. They’ve predicted and built the AI trajectory, they’ve been right, and we should listen. > If…
Comment linking /documents/Machine_Super_Intelligence.pdf
on “Sam and Greg's response to OpenAI Safety researcher claims”Submitted Publishing through lulu.com using LaTeX as a story · 2 points
HN discussionShane Legg (DeepMind cofounder) is public about predicting AGI at 2028. http://www.vetta.org/2011/12/goodbye-2011-hello-2012/ My impression is this is common among DeepMind folks and not an aberration. (See also dwiel's comment elsewhere.) It is super weird for me that Demis Hassabis says AGI is nowhere close. Is he lying? Or does he mean 10 years is not close?
Comment linking /2011/12/goodbye-2011-hello-2012/
on “Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality”Submitted Machine Superintelligence – Dissertation by the founder of Deepmind [pdf] as a story · 1 points
HN discussion> Shane Legg is known for being a co-founder of DeepMind, in a business role (as I understand) You are quite mistaken. He leads the applied AI team there, and has significant history in research. http://www.vetta.org/publications/
Comment linking /publications/
on “Machine intelligence, part 1”Submitted As many definitions of intelligence as there were experts asked to define it as a story · 1 points
HN discussionShane Legg isn't just a business guy - his career has been pretty much focused on AI research since uni - http://www.vetta.org/about-me/
Comment linking /about-me/
on “Machine intelligence, part 1”Submitted The Noughties as a story · 1 points
HN discussion"SciPy – the embarrassing way to code" http://www.vetta.org/2008/05/scipy-the-embarrassing-way-to-c...
Comment linking /2008/05/scipy-the-embarrassing-way-to-code/
on “A deep dive into APL”Submitted Serious, solemn or silly as a story · 1 points
HN discussionMy favorite application is Marcus Hutter's AIXI[1], a provably optimal theoretic intelligent agent for any environment, though uncomputable. And then Shane Legg's use of a Monte Carlo AIXI approximation to define a universal measure of intelligence[2]. [1] https://en.wikipedia.org/wiki/AIXI [2] http://www.vetta.org/documents/Machine_Super_Intelligence.pd...
Comment linking /documents/Machine_Super_Intelligence.pdf
on “Kolmogorov Complexity: Extensions and Applications”Submitted Beware of your intuition when reasoning about many dimensions as a story · 1 points
HN discussionMonte Carlo AIXI: http://www.vetta.org/2009/09/monte-carlo-aixi/ . It's an approximation of the optimal-but-uncomputable AIXI agent. Apparently it learned to play a Pacman variant without being told the rules in advance.
Comment linking /2009/09/monte-carlo-aixi/
on “Ask HN: So what's new in the world of A.I.?”There's a recent one that's supposed to have done respectably on Pac-Man: http://www.vetta.org/2009/09/monte-carlo-aixi/
Comment linking /2009/09/monte-carlo-aixi/
on “New Google AI Challenge: Planet Wars”> If easy instances are enough, what's the relevance of the provably ideal uncomputable problem, besides rhetoric? It shows that there's a path to AI that's gated on solving formal math problems instead of imitating wishy-washy emotional humans. This point may be obvious to you, but apparently it wasn't obvious to Stross. > If humans used easy instances, and they're the only example we know of that achieved I, how i…
Comment linking /2009/09/monte-carlo-aixi/
on “Three arguments against the singularity”- nl · 2014-01-28
It's difficult not to get caught up in the excitement around Deep Learning. The unsupervised nature of it at its best really does seem to approach human levels of learning (if not intelligence). Also, I thought this was hilarious: In a 2011 interview that predated DeepMind, co-founder Shane Legg said he gave only a 50 percent chance that human level-machine intelligence would exist by 2028. ONLY?!? By 2028? That is…
Comment linking /2011/12/goodbye-2011-hello-2012/
on “DeepMind to Work Directly With Google’s Search Team” Link without ssl (notice the http at the beginning): http://www.vetta.org/documents/Machine_Super_Intelligence.pd...
Comment linking /documents/Machine_Super_Intelligence.pdf
on “Shane Legg: Machine Super Intelligence (2008) [pdf]”The clearest description of what CS researchers talk about when they talk about "intelligence" (see http://www.vetta.org/definitions-of-intelligence/ ) is probably a production function from economics.
Comment linking /definitions-of-intelligence/
on “Common Lisp + Machine Learning Internship at Google (Mountain View, CA)”There's an algorithm developed by Marcus Hutter called AIXI, which makes provably optimal decisions. Unfortunately(?) it's also uncomputable, but computable approximations exist including a Monte Carlo variant: http://www.vetta.org/2009/09/monte-carlo-aixi/ . As the paper notes it scales extremely well; to get better results you just throw more computing power at it.
Comment linking /2009/09/monte-carlo-aixi/
on “Bill Joy: Why the future doesn't need us (2004)”Interestingly, he once called MIRI[1] (formerly SIAI) “the best hope that we have”[2]. [1] https://intelligence.org/ [2] http://www.vetta.org/2009/08/funding-safe-agi/
Comment linking /2009/08/funding-safe-agi/
on “Shane Legg: DeepMind's third cofounder”
