Can I get tips on bringing Alchemy's optimized Tuffy <http://i.stanford.edu/hazy/tuffy/> in Java to Julia while showing the best of Julia? I am going for the most correct way, even if it means coding Tuffy into C and Julia.
On Sunday, August 7, 2016 at 8:34:37 PM UTC-3, Kevin Liu wrote: > > I'll try to build it, compare it, and show it to you guys. I offered to do > this as work. I am waiting to see if they will accept it. > > On Sunday, August 7, 2016 at 6:15:50 PM UTC-3, Stefan Karpinski wrote: >> >> Kevin, as previously requested by Isaiah, please take this to some other >> forum or maybe start a blog. >> >> On Sat, Aug 6, 2016 at 10:53 PM, Kevin Liu <kvt...@gmail.com> wrote: >> >>> Symmetry-based learning, Domingos, 2014 >>> https://www.microsoft.com/en-us/research/video/symmetry-based-learning/ >>> >>> Approach 2: Deep symmetry networks generalize convolutional neural >>> networks by tying parameters and pooling over an arbitrary symmetry group, >>> not just the translation group. In preliminary experiments, they >>> outperformed convnets on a digit recognition task. >>> >>> On Friday, August 5, 2016 at 4:56:45 PM UTC-3, Kevin Liu wrote: >>>> >>>> Minsky died of a cerebral hemorrhage at the age of 88.[40] >>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-40> Ray Kurzweil >>>> <https://en.wikipedia.org/wiki/Ray_Kurzweil> says he was contacted by >>>> the cryonics organization Alcor Life Extension Foundation >>>> <https://en.wikipedia.org/wiki/Alcor_Life_Extension_Foundation> seeking >>>> Minsky's body.[41] >>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-Kurzweil-41> >>>> Kurzweil >>>> believes that Minsky was cryonically preserved by Alcor and will be >>>> revived >>>> by 2045.[41] >>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-Kurzweil-41> Minsky >>>> was a member of Alcor's Scientific Advisory Board >>>> <https://en.wikipedia.org/wiki/Advisory_Board>.[42] >>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-AlcorBoard-42> In >>>> keeping with their policy of protecting privacy, Alcor will neither >>>> confirm >>>> nor deny that Alcor has cryonically preserved Minsky.[43] >>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-43> >>>> >>>> We better do a good job. >>>> >>>> On Friday, August 5, 2016 at 4:45:42 PM UTC-3, Kevin Liu wrote: >>>>> >>>>> *So, I think in the next 20 years (2003), if we can get rid of all of >>>>> the traditional approaches to artificial intelligence, like neural nets >>>>> and >>>>> genetic algorithms and rule-based systems, and just turn our sights a >>>>> little bit higher to say, can we make a system that can use all those >>>>> things for the right kind of problem? Some problems are good for neural >>>>> nets; we know that others, neural nets are hopeless on them. Genetic >>>>> algorithms are great for certain things; I suspect I know what they're >>>>> bad >>>>> at, and I won't tell you. (Laughter)* - Minsky, founder of CSAIL MIT >>>>> >>>>> *Those programmers tried to find the single best way to represent >>>>> knowledge - Only Logic protects us from paradox.* - Minsky (see >>>>> attachment from his lecture) >>>>> >>>>> On Friday, August 5, 2016 at 8:12:03 AM UTC-3, Kevin Liu wrote: >>>>>> >>>>>> Markov Logic Network is being used for the continuous development of >>>>>> drugs to cure cancer at MIT's CanceRX <http://cancerx.mit.edu/>, on >>>>>> DARPA's largest AI project to date, Personalized Assistant that >>>>>> Learns (PAL) <https://pal.sri.com/>, progenitor of Siri. One of >>>>>> Alchemy's largest applications to date was to learn a semantic network >>>>>> (knowledge graph as Google calls it) from the web. >>>>>> >>>>>> Some on Probabilistic Inductive Logic Programming / Probabilistic >>>>>> Logic Programming / Statistical Relational Learning from CSAIL >>>>>> <http://people.csail.mit.edu/kersting/ecmlpkdd05_pilp/pilp_ida2005_tut.pdf> >>>>>> (my >>>>>> understanding is Alchemy does PILP from entailment, proofs, and >>>>>> interpretation) >>>>>> >>>>>> The MIT Probabilistic Computing Project (where there is Picture, an >>>>>> extension of Julia, for computer vision; Watch the video from Vikash) >>>>>> <http://probcomp.csail.mit.edu/index.html> >>>>>> >>>>>> Probabilistic programming could do for Bayesian ML what Theano has >>>>>> done for neural networks. >>>>>> <http://www.inference.vc/deep-learning-is-easy/> - Ferenc Huszár >>>>>> >>>>>> Picture doesn't appear to be open-source, even though its Paper is >>>>>> available. >>>>>> >>>>>> I'm in the process of comparing the Picture Paper and Alchemy code >>>>>> and would like to have an open-source PILP from Julia that combines the >>>>>> best of both. >>>>>> >>>>>> On Wednesday, August 3, 2016 at 5:01:02 PM UTC-3, Christof Stocker >>>>>> wrote: >>>>>>> >>>>>>> This sounds like it could be a great contribution. I shall keep a >>>>>>> curious eye on your progress >>>>>>> >>>>>>> Am Mittwoch, 3. August 2016 21:53:54 UTC+2 schrieb Kevin Liu: >>>>>>>> >>>>>>>> Thanks for the advice Cristof. I am only interested in people >>>>>>>> wanting to code it in Julia, from R by Domingos. The algo has been >>>>>>>> successfully applied in many areas, even though there are many other >>>>>>>> areas >>>>>>>> remaining. >>>>>>>> >>>>>>>> On Wed, Aug 3, 2016 at 4:45 PM, Christof Stocker < >>>>>>>> stocker....@gmail.com> wrote: >>>>>>>> >>>>>>>>> Hello Kevin, >>>>>>>>> >>>>>>>>> Enthusiasm is a good thing and you should hold on to that. But to >>>>>>>>> save yourself some headache or disappointment down the road I advice >>>>>>>>> a >>>>>>>>> level head. Nothing is really as bluntly obviously solved as it may >>>>>>>>> seems >>>>>>>>> at first glance after listening to brilliant people explain things. A >>>>>>>>> physics professor of mine once told me that one of the (he thinks) >>>>>>>>> most >>>>>>>>> malicious factors to his past students progress where overstated >>>>>>>>> results/conclusions by other researches (such as premature >>>>>>>>> announcements >>>>>>>>> from CERN). I am no mathematician, but as far as I can judge is the >>>>>>>>> no free >>>>>>>>> lunch theorem of pure mathematical nature and not something induced >>>>>>>>> empirically. These kind of results are not that easily to get rid of. >>>>>>>>> If >>>>>>>>> someone (especially an expert) states such a theorem will prove wrong >>>>>>>>> I >>>>>>>>> would be inclined to believe that he is not talking about literally, >>>>>>>>> but >>>>>>>>> instead is just trying to make a point about a more or less practical >>>>>>>>> implication. >>>>>>>>> >>>>>>>>> >>>>>>>>> Am Mittwoch, 3. August 2016 21:27:05 UTC+2 schrieb Kevin Liu: >>>>>>>>>> >>>>>>>>>> The Markov logic network represents a probability distribution >>>>>>>>>> over the states of a complex system (i.e. a cell), comprised of >>>>>>>>>> entities, >>>>>>>>>> where logic formulas encode the dependencies between them. >>>>>>>>>> >>>>>>>>>> On Wednesday, August 3, 2016 at 4:19:09 PM UTC-3, Kevin Liu wrote: >>>>>>>>>>> >>>>>>>>>>> Alchemy is like an inductive Turing machine, to be programmed to >>>>>>>>>>> learn broadly or restrictedly. >>>>>>>>>>> >>>>>>>>>>> The logic formulas from rules through which it represents can be >>>>>>>>>>> inconsistent, incomplete, or even incorrect-- the learning and >>>>>>>>>>> probabilistic reasoning will correct them. The key point is that >>>>>>>>>>> Alchemy >>>>>>>>>>> doesn't have to learn from scratch, proving Wolpert and Macready's >>>>>>>>>>> no free >>>>>>>>>>> lunch theorem wrong by performing well on a variety of classes of >>>>>>>>>>> problems, >>>>>>>>>>> not just some. >>>>>>>>>>> >>>>>>>>>>> On Wednesday, August 3, 2016 at 4:01:15 PM UTC-3, Kevin Liu >>>>>>>>>>> wrote: >>>>>>>>>>>> >>>>>>>>>>>> Hello Community, >>>>>>>>>>>> >>>>>>>>>>>> I'm in the last pages of Pedro Domingos' book, the Master Algo, >>>>>>>>>>>> one of two recommended by Bill Gates to learn about AI. >>>>>>>>>>>> >>>>>>>>>>>> From the book, I understand all learners have to represent, >>>>>>>>>>>> evaluate, and optimize. There are many types of learners that do >>>>>>>>>>>> this. What >>>>>>>>>>>> Domingos does is generalize these three parts, (1) using Markov >>>>>>>>>>>> Logic >>>>>>>>>>>> Network to represent, (2) posterior probability to evaluate, and >>>>>>>>>>>> (3) >>>>>>>>>>>> genetic search with gradient descent to optimize. The posterior >>>>>>>>>>>> can be >>>>>>>>>>>> replaced for another accuracy measure when it is easier, as >>>>>>>>>>>> genetic search >>>>>>>>>>>> replaced by hill climbing. Where there are 15 popular options for >>>>>>>>>>>> representing, evaluating, and optimizing, Domingos generalized >>>>>>>>>>>> them into >>>>>>>>>>>> three options. The idea is to have one unified learner for any >>>>>>>>>>>> application. >>>>>>>>>>>> >>>>>>>>>>>> There is code already done in R >>>>>>>>>>>> https://alchemy.cs.washington.edu/. My question: anybody in >>>>>>>>>>>> the community vested in coding it into Julia? >>>>>>>>>>>> >>>>>>>>>>>> Thanks. Kevin >>>>>>>>>>>> >>>>>>>>>>>> On Friday, June 3, 2016 at 3:44:09 PM UTC-3, Kevin Liu wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> https://github.com/tbreloff/OnlineAI.jl/issues/5 >>>>>>>>>>>>> >>>>>>>>>>>>> On Friday, June 3, 2016 at 11:17:28 AM UTC-3, Kevin Liu wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>> I plan to write Julia for the rest of me life... given it >>>>>>>>>>>>>> remains suitable. I am still reading all of Colah's material on >>>>>>>>>>>>>> nets. I ran >>>>>>>>>>>>>> Mocha.jl a couple weeks ago and was very happy to see it work. >>>>>>>>>>>>>> Thanks for >>>>>>>>>>>>>> jumping in and telling me about OnlineAI.jl, I will look into it >>>>>>>>>>>>>> once I am >>>>>>>>>>>>>> ready. From a quick look, perhaps I could help and learn by >>>>>>>>>>>>>> building a very >>>>>>>>>>>>>> clear documentation of it. Would really like to see Julia a leap >>>>>>>>>>>>>> ahead of >>>>>>>>>>>>>> other languages, and plan to contribute heavily to it, but at >>>>>>>>>>>>>> the moment am >>>>>>>>>>>>>> still getting introduced to CS, programming, and nets at the >>>>>>>>>>>>>> basic level. >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Friday, June 3, 2016 at 10:48:15 AM UTC-3, Tom Breloff >>>>>>>>>>>>>> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Kevin: computers that program themselves is a concept which >>>>>>>>>>>>>>> is much closer to reality than most would believe, but >>>>>>>>>>>>>>> julia-users isn't >>>>>>>>>>>>>>> really the best place for this speculation. If you're actually >>>>>>>>>>>>>>> interested >>>>>>>>>>>>>>> in writing code, I'm happy to discuss in OnlineAI.jl. I was >>>>>>>>>>>>>>> thinking about >>>>>>>>>>>>>>> how we might tackle code generation using a neural framework >>>>>>>>>>>>>>> I'm working >>>>>>>>>>>>>>> on. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Friday, June 3, 2016, Kevin Liu <kvt...@gmail.com> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> If Andrew Ng who cited Gates, and Gates who cited Domingos >>>>>>>>>>>>>>>> (who did not lecture at Google with a TensorFlow question in >>>>>>>>>>>>>>>> the end), were >>>>>>>>>>>>>>>> unsuccessful penny traders, Julia was a language for web >>>>>>>>>>>>>>>> design, and the >>>>>>>>>>>>>>>> tribes in the video didn't actually solve problems, perhaps >>>>>>>>>>>>>>>> this would be a >>>>>>>>>>>>>>>> wildly off-topic, speculative discussion. But these statements >>>>>>>>>>>>>>>> couldn't be >>>>>>>>>>>>>>>> farther from the truth. In fact, if I had known about this >>>>>>>>>>>>>>>> video some >>>>>>>>>>>>>>>> months ago I would've understood better on how to solve a >>>>>>>>>>>>>>>> problem I was >>>>>>>>>>>>>>>> working on. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> For the founders of Julia: I understand your tribe is >>>>>>>>>>>>>>>> mainly CS. This master algorithm, as you are aware, would >>>>>>>>>>>>>>>> require >>>>>>>>>>>>>>>> collaboration with other tribes. Just citing the obvious. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Friday, June 3, 2016 at 10:21:25 AM UTC-3, Kevin Liu >>>>>>>>>>>>>>>> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> There could be parts missing as Domingos mentions, but >>>>>>>>>>>>>>>>> induction, backpropagation, genetic programming, >>>>>>>>>>>>>>>>> probabilistic inference, >>>>>>>>>>>>>>>>> and SVMs working together-- what's speculative about the >>>>>>>>>>>>>>>>> improved versions >>>>>>>>>>>>>>>>> of these? >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Julia was made for AI. Isn't it time for a consolidated >>>>>>>>>>>>>>>>> view on how to reach it? >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Thursday, June 2, 2016 at 11:20:35 PM UTC-3, Isaiah >>>>>>>>>>>>>>>>> wrote: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> This is not a forum for wildly off-topic, speculative >>>>>>>>>>>>>>>>>> discussion. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Take this to Reddit, Hacker News, etc. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> On Thu, Jun 2, 2016 at 10:01 PM, Kevin Liu < >>>>>>>>>>>>>>>>>> kvt...@gmail.com> wrote: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> I am wondering how Julia fits in with the unified tribes >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> mashable.com/2016/06/01/bill-gates-ai-code-conference/#8VmBFjIiYOqJ >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> https://www.youtube.com/watch?v=B8J4uefCQMc >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>> >>
