Thank you @Microsoft for renewing @Azure sponsorship to support http://ReproIndex.com and http://cKnowledge.org - our community projects for #reproducible research, portable workflows, reusable research components, #Collaboration and #OpenScience
@eembc_org released MLMark (a #benchmark for #machinelearning at the Edge) with object detection and image classification models (ResNet-50, MobileNet and SSDMobileNet): https://www.eembc.org/mlmark/scores.php …
Just noticed this interesting article from last year about the "Troubling Trends in Machine Learning Scholarship": https://arxiv.org/pdf/1807.03341.pdf …#reproducibility #machinelearning
If you plan to participate in the Student Cluster Competition at @Supercomputing'19, please check out this #workflow to help you prepare your submission: https://github.com/reproindex/ck-scc … #StudentClusterCompetition #automation #customization #portability #reproducibility #HPC
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches: https://arxiv.org/abs/1907.06902v1 …#reproducibility #ai #ml #dnn
An interesting project on Deterministic Workflows from @Penn and @IndianaUniv: https://iu-parfunc.github.io/detbox-project - they have built deployable, user-space
solutions for determinizing preexisting, binary Linux-x86
programs using runtime sandboxing ...
We are very excited to announce a new reproducibility initiative at @ASPLOSConf (the @TheOfficialACM Conference on Architectural Support for Programming Languages and Operating Systems). Please visit https://reproindex.com/event/repro-asplos2020 … for more info!
We plan to organize an open session at ASPLOS'20 to discuss artifact evaluation results and a common methodology to perform a full validation and comparison of computer architecture experiments - please stay tuned for more info!
#MLPerf announced the v0.5 inference benchmark suite: https://www.mlperf.org/press#mlperf-inference-launched … . Submissions for two image classification tasks, two object detection tasks, and one machine translation task are due September 6th, 2019: https://www.mlperf.org/inference-overview … !
Honoured and humbled to receive a Certificate of Appreciation from the #MLPerf community for contributions to #MLPerf #Inference: https://www.linkedin.com/feed/update/urn:li:activity:6546356191541383168 …
The #MLPerf community has recently presented our CEO @lokhmotov with a Certificate of Appreciation for contributions to #MLPerf #Inference, including reference workload implementations, and automated, customizable and reproducible #CollectiveKnowledge workflows. https://twitter.com/lokhmotov/status/1140591182977884160
Submit awesome papers to @ASPLOSConf 2020! Can’t wait to build an exciting program! https://twitter.com/JamesLarus/status/1127978581378916353
Cray Secures $600M DOE Contract to Build AI-Based Supercomputer https://www.govconwire.com/2019/05/cray-secures-600m-doe-contract-to-build-ai-based-supercomputer/ …
Very excited to see that our #CollectiveKnowledge framework has reached 100K+ PyPi downloads today: https://github.com/ctuning/ck ! I would like to thank all our users and contributors for their interest and support of #ReproducibleResearch and #OpenScience: http://crowd-research.com !
So glad and proud to see that our #CollectiveKnowledge framework supported a great hackathon on #QuantumComputing at the @UniofOxford (organized by @dividiti and @RiverLane_): https://www.linkedin.com/feed/update/activity:6512290010874679296 … . The results are available at http://cknowledge.org/dashboard/hackathon.20190315 … !
I am extremely honored to be the recipient of the 2018 ACM A.M. Turing Award, and absolutely delighted to be sharing it with my friends and colleagues Geoffrey Hinton and Yoshua Bengio.
NYT:... https://www.nytimes.com/2019/03/27/technology/turing-award-hinton-lecun-bengio.html …
The SysML whitepaper is out http://www.sysml.cc/doc/sysml-whitepaper.pdf …
Instead of worrying about AGI talking over the world, lets first worry about
performance, fairness, robustness, security, privacy, interpretability, and causality for systems deployed over evolving software and hardware. https://twitter.com/atalwalkar/status/1112447019816148992
I was very pleased to receive positive feedback and many helpful suggestions from the #SysML'19 participants during our demo of "Customizable and Reusable Collective Knowledge Pipelines to Automate and Reproduce Machine Learning Experiments": http://reproducible-research.com
The possibility to easily change different ML/AI frameworks, models, data sets, libraries and compilers in the #CollectiveKnowledge workflows, run them across different hardware, and apply DevOps principles were of particular interest at #SysML'19: https://bit.ly/sysml19 !
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