Top news of the week: 30.07.2020.
Parallel computing, Artificial intelligence, Algorithm, Professor, Production system, Data parallelism
Research
RT @OptunaAutoML: Optuna 2.0, the next major evolution of Optuna is here!
2.0 introduces hyperparameter importance to see which hyperparameters matter most, Hyperband pruning, and many performance improvements!
See what’s new ↓
https://t.co/jKWA4LBoVv
OpenAnnouncing Optuna 2.0
We are pleased to announce the second major version of Optuna, a hyperparameter optimization (HPO) framework in Python, is now available…
RT @DeepMind: Being able to bring together new ideas & fresh perspectives is incredibly important to the advancement of AI.
That’s why we’re very excited to announce our scholarship programme renewal with @imperialcollege!
https://t.co/yPob6VXgWk
OpenNew DeepMind scholarships create AI study opportunities for postgraduates
New scholarships offer students from underrepresented backgrounds the chance of postgraduate study in AI and machine learning.
RT @CuraiHQ: How do you inject prior knowledge and expertise in your data and machine learning approaches when working in the medical domain? An important piece for us is our medical knowledge graph. Learn more about it in our new post on our tech blog https://t.co/ikM50rJpNq
OpenHow BMW Used Pandemic Plant Stoppages to Boost Artificial Intelligence
When the coronavirus pandemic forced BMW AG to close factories across Germany in March, Matthias Schindler saw an opportunity to boost plants’ use of artificial intelligence.
RT @Livermore_Lab: LLNL researchers and collaborators turn to machine learning to perfect two-photon lithography - a widely used 3D nanoprinting technique. More at https://t.co/XPvhO92t74. https://t.co/TxQqM6QibU
OpenMachine learning model may perfect 3D nanoprinting
Two-photon lithography (TPL) — a widely used 3D nanoprinting technique that uses laser light to create 3D objects — has shown promise in research applications but has yet to achieve ...
RT @NVIDIAAI: NVIDIA A100 #GPU and the DGX SuperPOD system deliver training performance needed for most important #AI workloads in the latest round of #MLPerf benchmarks. Learn more: https://t.co/mMSgkZvNqL
OpenNVIDIA Breaks 16 AI Performance Records in Latest MLPerf Benchmarks
NVIDIA A100 GPUs and DGX systems broke 16 records in MLPerf AI training benchmarks.
RT @omarsar0: Excited about this profiler included in the new release of @PyTorch. You can use this to better optimize your code and check for model bottlenecks.
I will try this later but curious to see how developers will use this.
https://t.co/BhfGv9lEI5 https://t.co/33X4CcZpXs
OpenStable release of automatic mixed precision (AMP). New Beta features include a TensorPipe backend for RPC, memory profiler, and several improvements to distributed training for both RPC and DDP.
PyTorch 1.6.0 Release Notes Highlights Backwards Incompatible Changes Deprecations New Features Improvements Bug Fixes Performance Documentation Highlights The PyTorch 1.6 release ...
RT @PyTorch: v1.6: native mixed-precision support from NVIDIA (~2x perf improvement), distributed perf improvements, new profiling tool for memory consumption, Microsoft commits to developing and maintaining Windows PyTorch.
Release Notes: https://t.co/7LMXQYlaAd
Blog:https://t.co/0cwKG82iOB
OpenPyTorch 1.6 released w/ Native AMP Support, Microsoft joins as maintainers for Windows
An open source deep learning platform that provides a seamless path from research prototyping to production deployment.