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]> 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 for wildly off-topic, 
>>> speculative 
>>> >>>>>>>>>>>>>>>>>>>>>> discussion. 
>>> >>>>>>>>>>>>>>>>>>>>>> 
>>> >>>>>>>>>>>>>>>>>>>>>> Take this to Reddit, Hacker News, etc. 
>>> >>>>>>>>>>>>>>>>>>>>>> 
>>> >>>>>>>>>>>>>>>>>>>>>> 
>>> >>>>>>>>>>>>>>>>>>>>>> On Thu, Jun 2, 2016 at 10:01 PM, Kevin Liu < 
>>> >>>>>>>>>>>>>>>>>>>>>> 
>>> >&gt
>>
>>

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