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 <[email protected] <javascript:>> >>>> 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: >>>> >>>>>>>>>>>>>>>>>>>>> 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 fo >>> >>>
