The explicit message here with no implicit one is that the unsubscribe option exists for a reason.
On Sep 2, 2016, at 12:18, John Myles White <[email protected]> wrote: >> May I also point out to the My settings button on your top right corner > My >> topic email subscriptions > Unsubscribe from this thread, which would've >> spared you the message. > > I'm sorry, but this kind of attitude is totally unacceptable, Kevin. I've > tolerated your misuse of the mailing list, but it is not acceptable for you > to imply that others are behaving inappropriately when they complain about > your unequivocal misuse of the mailing list. > > --John > >> On Friday, September 2, 2016 at 7:23:27 AM UTC-7, Kevin Liu wrote: >> May I also point out to the My settings button on your top right corner > My >> topic email subscriptions > Unsubscribe from this thread, which would've >> spared you the message. >> >>> On Friday, September 2, 2016 at 11:19:42 AM UTC-3, Kevin Liu wrote: >>> Hello Chris. Have you been applying relational learning to your Neural >>> Crest Migration Patterns in Craniofacial Development research project? It >>> could enhance your insights. >>> >>>> On Friday, September 2, 2016 at 6:18:15 AM UTC-3, Chris Rackauckas wrote: >>>> This entire thread is a trip... a trip which is not really relevant to >>>> julia-users. You may want to share these musings in the form of a blog >>>> instead of posting them here. >>>> >>>>> On Friday, September 2, 2016 at 1:41:03 AM UTC-7, Kevin Liu wrote: >>>>> Princeton's post: >>>>> http://www.nytimes.com/2016/08/28/world/europe/france-burkini-bikini-ban.html?_r=1 >>>>> >>>>> Only logic saves us from paradox. - Minsky >>>>> >>>>>> On Thursday, August 25, 2016 at 10:18:27 PM UTC-3, Kevin Liu wrote: >>>>>> Tim Holy, I am watching your keynote speech at JuliaCon 2016 where you >>>>>> mention the best optimization is not doing the computation at all. >>>>>> >>>>>> Domingos talks about that in his book, where an efficient kind of >>>>>> learning is by analogy, with no model at all, and how numerous >>>>>> scientific discoveries have been made that way, e.g. Bohr's analogy of >>>>>> the solar system to the atom. Analogizers learn by hypothesizing that >>>>>> entities with similar known properties have similar unknown ones. >>>>>> >>>>>> MLN can reproduce structure mapping, which is the more powerful type of >>>>>> analogy, that can make inferences from one domain (solar system) to >>>>>> another (atom). This can be done by learning formulas that don't refer >>>>>> to any of the specific relations in the source domain (general >>>>>> formulas). >>>>>> >>>>>> Seth and Tim have been helping me a lot with putting the pieces together >>>>>> for MLN in the repo I created, and more help is always welcome. I would >>>>>> like to write MLN in idiomatic Julia. My question at the moment to you >>>>>> and the community is how to keep mappings of first-order harmonic >>>>>> functions type-stable in Julia? I am just getting acquainted with the >>>>>> type field. >>>>>> >>>>>>> On Tuesday, August 9, 2016 at 9:02:25 AM UTC-3, Kevin Liu wrote: >>>>>>> Helping me separate the process in parts and priorities would be a lot >>>>>>> of help. >>>>>>> >>>>>>>> On Tuesday, August 9, 2016 at 8:41:03 AM UTC-3, Kevin Liu wrote: >>>>>>>> Tim Holy, what if I could tap into the well of knowledge that you are >>>>>>>> to speed up things? Can you imagine if every learner had to start >>>>>>>> without priors? >>>>>>>> >>>>>>>> > On Aug 9, 2016, at 07:06, Tim Holy <[email protected]> wrote: >>>>>>>> > >>>>>>>> > I'd recommend starting by picking a very small project. For example, >>>>>>>> > fix a bug >>>>>>>> > or implement a small improvement in a package that you already find >>>>>>>> > useful or >>>>>>>> > interesting. That way you'll get some guidance while making a >>>>>>>> > positive >>>>>>>> > contribution; once you know more about julia, it will be easier to >>>>>>>> > see your >>>>>>>> > way forward. >>>>>>>> > >>>>>>>> > Best, >>>>>>>> > --Tim >>>>>>>> > >>>>>>>> >> On Monday, August 8, 2016 8:22:01 PM CDT Kevin Liu wrote: >>>>>>>> >> 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 <[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.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 >>>>>>>> >>>>>>>>>>>>>>>>>>> <[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: >>>>>>>> >>>>>>>>>>>>>>>
