Another important cool thing I think is worth noting: he added the possibility of weights to rules (attachment). Each line is equivalent to a desired conclusion.
On Wednesday, August 3, 2016 at 4:27:05 PM UTC-3, Kevin Liu wrote: > > 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 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 <kvt...@gmail.com> >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> I am wondering how Julia fits in with the unified tribes >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> mashable.com/2016/06/01/bill-gates-ai-code-conference/#8VmBFjIiYOqJ >>>>>>>>>> >>>>>>>>>> https://www.youtube.com/watch?v=B8J4uefCQMc >>>>>>>>>> >>>>>>>>> >>>>>>>>>
