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 <[email protected]> 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 < >>>>>> [email protected]> 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.washingto >>>>>>>>>> n.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 <[email protected]> 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 < >>>>>>>>>>>>>>>> [email protected]> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> I am wondering how Julia fits in with the unified tribes >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> mashable.com/2016/06/01/bill-g >>>>>>>>>>>>>>>>> ates-ai-code-conference/#8VmBFjIiYOqJ >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> https://www.youtube.com/watch?v=B8J4uefCQMc >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>
