Here is a demo with some impressions: https://youtu.be/UwJxLztoI1o
The MXNet blog post will follow soon. We wanted to show it on GTC as well, but couldn't allocate the needed time. You can see the code in Thomas repository: https://github.com/ThomasDelteil/RobotTracker_MXNet But it's far from being just reusable and lacks documentation. I could see though that if we get enough time, we would wrap most things into docker containers, write proper instructions and give the community the opportunity to contribute and to show it on their own. Best Anton ср, 20 мар. 2019 г. в 17:08, Aaron Markham <aaron.s.mark...@gmail.com>: > Anton, can you share the design and specs and code for the robot arm demo? > I wish that was being shown at GTC now. It would be great to let people > borrow it for West coast events. Maybe I can get one built here in Palo > Alto. > > On Tue, Mar 19, 2019, 05:54 Anton Chernov <mecher...@gmail.com> wrote: > > > I don't know whether that is enough, but here are a few efforts we make > to > > promote MXNet: > > > > * The robotic arms demo at the embedded world > > We promoted MXNet as the framework to go on embedded devices with our > > robotic arms demo. We've got a lot of attention from different people > > including professors from multiple universities. A blog post about the > demo > > will be posted in the next days MXNet Medium blog [1]. > > > > Here again some impressions from twitter: > > https://twitter.com/lebegus/status/1100839414228500485 > > > > * MLPerf results > > We intend to publish more benchmark results to MLPerf [2], showing proof > of > > the performance advantages of MXNet. > > > > * Recurring user group meetings > > We offer recurring VC meetings [3], free for everyone. We dedicate our > time > > to anyone that would like to know more about MXNet or to ask any other > > related question. > > > > * Collaborative meetups > > We organize meetups with attendants from various companies [4], sharing > > their interesting use cases and best practises with ML and MXNet. > > > > Tracking works and papers on popular science conferences is a valid > metric, > > but it's focused on research. More and more people that don't write > papers > > use ML and MXNet in production without knowing all the scientific > details. > > How to measure how many are out there is an open question. > > > > Best > > Anton > > > > [1] https://medium.com/apache-mxnet > > [2] https://mlperf.org/ > > [3] https://cwiki.apache.org/confluence/x/7BY0BQ > > [4] https://www.meetup.com/Deep-Learning-with-Apache-MXNet-Berlin > > > > > > вт, 19 мар. 2019 г. в 07:23, Isabel Drost-Fromm <isa...@apache.org>: > > > > > > > > > > > Am 19. März 2019 02:49:23 MEZ schrieb "Zhao, Patric" < > > > patric.z...@intel.com>: > > > >I suggest to encourage and fund the students/researchers to present > > > >their works on the popular conference. > > > >I know talking is easy but maybe the decision maker can allocate more > > > >resources for marketing. > > > > > > Just for clarity, who exactly do you mean with "the decision maker"? > > > Decision maker for what? > > > > > > On another note, beyond that one conference, which other channels do > > > people here follow? How did you first hear about mxnet? > > > > > > > > > Isabel > > > > > > > > > -- > > > Diese Nachricht wurde von meinem Android-Gerät mit K-9 Mail gesendet. > > > > > >
