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Liang-Chi Hsieh proslijedio/la je Tweet
Excellent and perceptive article by
@philipcball on the state of AI and whether machines could ever attain human-level intelligence or consciousness. Features discussion of recent books by@GaryMarcus & Ernest Davis; Christof Koch; and me.https://www.prospectmagazine.co.uk/magazine/the-ai-delusion-why-humans-trump-machines-robots-artificial-intelligence-alpha-go-deepmind …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
[ANNOUNCEMENT] The Apache Spark 3.0 Preview 2 is here! It is the second preview release. Try it now and let us know what you think! View the release notes https://spark.apache.org/news/spark-3.0.0-preview2.html … Happy Holidays!
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Liang-Chi Hsieh proslijedio/la je Tweet
OpenJDK Startup - Late 2019 Update: 40% less memory, 40% less CPUhttps://cl4es.github.io/2019/11/20/OpenJDK-Startup-Update.html …
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Liang-Chi Hsieh proslijedio/la je Tweet
Introduction to Adversarial Machine Learning A tutorial by
@amarunava that presents an overview of current approaches for adversarial attacks and defenses in the literature. https://blog.floydhub.com/introduction-to-adversarial-machine-learning/ …pic.twitter.com/Ek5gfxkyh0
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Liang-Chi Hsieh proslijedio/la je Tweet
Great results finding DNN optimizations automatically by
@JiaZhihao at@SOSP_2019 today. Zhihao is also on the academic job market this year. More info and source code: https://github.com/jiazhihao/TASO pic.twitter.com/V2cJpHWXJS
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Liang-Chi Hsieh proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Liang-Chi Hsieh proslijedio/la je Tweet
This is the rejection letter for the work that just won the Nobel Prize. Believe in yourself. Everyone else will catch up eventually.pic.twitter.com/gi5Jk1rEzt
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Liang-Chi Hsieh proslijedio/la je Tweet
New research demonstrates how a model for multilingual
#MachineTranslation of 100+ languages trained with a single massive#NeuralNetwork significantly improves performance on both low- and high-resource language translation. Read all about it at: https://goo.gle/325DlY4 pic.twitter.com/N8TogHbbC6Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
No opinion on favorite or not, but this paper
@geoffreyhinton,@OriolVinyalsML, & I submitted to NeurIPS'14 was rejected (~2K citations): Distilling the Knowledge in a Neural Network https://arxiv.org/abs/1503.02531 2/3 said "1: This work is incremental and unlikely to have much impact"Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
Nice interview with my PhD student
@sppalkia on Weld!https://twitter.com/unbalancedparen/status/1175455883138150400 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
We see more significant improvements from training data distribution search (data splits + oversampling factor ratios) than neural architecture search. The latter is so overrated :)
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Liang-Chi Hsieh proslijedio/la je Tweet
Simple statistical methods are shown to much better than fancy machine learning on a whole bunch of real-world sequence-prediction datasets. The reason: the time series used are tiny by ML standards, and all the ML methods overfit.https://twitter.com/spyrosmakrid/status/1172499153869529088 …
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Liang-Chi Hsieh proslijedio/la je Tweet
New EMNLP paper “Investigating Multilingual NMT Representation at Scale” w/
@ankurbpn,@orf_bnw, @caswell_isaac,@naveenariva. We study transfer in massively multilingual NMT@GoogleAI from the perspective of representational similarity. Paper: https://arxiv.org/pdf/1909.02197.pdf … 1/npic.twitter.com/oai93dFsOw
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Liang-Chi Hsieh proslijedio/la je Tweet
New research into cross-modal learning applies
#AutomaticSpeechRecognition to video content, enabling self-supervised training of#NeuralNetworks to understand high-level semantic features in video that occur over long time frames. Learn more at ↓http://goo.gle/2lLgDEaHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
Today, we’re happy to release two new natural language dialog datasets, which capture the richness of natural dialog, for use in training more effective digital assistants that can understand complex language. Learn more and grab the data at ↓https://goo.gle/2kwg4hj
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Liang-Chi Hsieh proslijedio/la je Tweet
Can neural network architectures alone, without learning any weight parameters, encode solutions for a given task? We search for “weight agnostic neural network” architectures that can perform various tasks even when using random weight values. Learn more→https://goo.gle/2Lf77Cx pic.twitter.com/J58sAAly2K
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Liang-Chi Hsieh proslijedio/la je Tweet
Nice case study from HyperloopOne about running pandas code on
#ApacheSpark with the new Koalas library: https://databricks.com/blog/2019/08/22/guest-blog-how-virgin-hyperloop-one-reduced-processing-time-from-hours-to-minutes-with-koalas.html …. No more complex rewrite into Spark DataFrames needed.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
Google’s sibling DeepMind lost $572 million last year. What does it mean? Some thoughts I wrote for
@Wired.https://www.wired.com/story/deepminds-losses-future-artificial-intelligence/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Liang-Chi Hsieh proslijedio/la je Tweet
Speaker diarization—separating speech from different speakers—is critical for joint speech recognition. New research based on a recurrent neural network transducer architecture improves diarization performance by a factor of ~10. Learn how it's done here:https://goo.gle/2H5fpeT
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Liang-Chi Hsieh proslijedio/la je Tweet
SQL on Hadoop friends: We're publishing a HadoopDB retrospective in VLDB 2019. Section 5 speaks more broadly about the current SQL on Hadoop ecosystem. Please let me know if we're missing anything important. Camera ready (final vers) of paper due tomorrow. http://www.cs.umd.edu/~abadi/papers/20001-Abadi.pdf …
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