I agree with John here. This is totally unacceptable, and is making the experience poorer for others.
-viral On Friday, September 2, 2016 at 8:48:44 PM UTC+5:30, John Myles White 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 >>>>>> <https://github.com/hpoit/Kenya.jl/issues/2>, 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 <tim....@gmail.com> 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 < >>>>>>>> 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 >>>>>>> >>>>>>>
