I have no idea where to start and where to finish. Founders' help would be wonderful.
On Tuesday, August 9, 2016 at 12:19:26 AM UTC-3, Kevin Liu wrote: > > After which I have to code Felix into Julia, a relational optimizer for > statistical inference with Tuffy <http://i.stanford.edu/hazy/tuffy/> > inside, for enterprise settings. > > On Tuesday, August 9, 2016 at 12:07:32 AM UTC-3, Kevin Liu wrote: >> >> 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 >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>> >>>>
