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 <[email protected]> >>>>>>>> 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 >>>>>>>>> >>>>>>>> >>>>>>>>
