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Anshul Choudhary proslijedio/la je Tweet
In January,
@anishathalye,@jjgort, and I ran a short class at@MIT_CSAIL on topics we think are missing in most CS programs — tools we use every day that everyone should know, like bash, git, vim, and tmux. And now the lecture notes and videos are online! https://missing.csail.mit.edu/ pic.twitter.com/xNSlLgJfd4Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Got tears in my eyes. Wisdom comes from clean heart not knowledge.https://twitter.com/Shalupcrf/status/1223585343234023425 …
2:19Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Anshul Choudhary proslijedio/la je Tweet
OK, maybe you can mess with Texas, but definitely don't mess with the Sun: https://www.nso.edu/telescopes/dkist/first-light-context-full-sun/ …pic.twitter.com/zpnVBL8Htx
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Anshul Choudhary proslijedio/la je Tweet
We just released a large public dataset of >10k echocardiogram videos with clinical annotations https://echonet.github.io/dynamic/ . Great resource for the medical ML community!pic.twitter.com/rmdIYtFBv3
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The fact that we have the concept of careers even today is so sickening. Can't u be a person who knows/have ability to know to work out things?
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This is the stupidest argument I have ever seen. Granted we are not growing but in order to reach optimal resource to population ratio, we need perhaps TFR of 1.0 or below. We need to decelarate now!https://twitter.com/sandeep_PT/status/1218725419878211584 …
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Anshul Choudhary proslijedio/la je Tweet
Beautiful quantum physics animations from the basics like • Wave-Particle duality • How lasers work • Tunneling effect to research level stuff like • Bose-Einstein condensate • Pump-probe technique All freely available on http://QuantumMadeSimple.com pic.twitter.com/H3DK5pAZXF
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Anshul Choudhary proslijedio/la je Tweet
We worked with
@harvardbrainsci to show that distributional RL, a recent development in AI research, can provide insight into previously unexplained elements of dopamine-based learning in the brain. Read the blog: https://deepmind.com/blog/article/Dopamine-and-temporal-difference-learning-A-fruitful-relationship-between-neuroscience-and-AI … (2/2)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Anshul Choudhary proslijedio/la je Tweet
Understanding how proteins fold is a fundamental scientific question that could one day help unlock treatments for a range of diseases. Excited that our
#AlphaFold work, which uses deep neural networks to predict protein structures, is published in@Nature today!https://twitter.com/DeepMind/status/1217510494984134657 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Anshul Choudhary proslijedio/la je Tweet
How To Train Interpretable Neural Networks That Accurately Extrapolate From Small Data. Today we released a new paper that showcases how to do just that using Scientific Machine Learning (
#sciml) techniques to encode non-data scientific information. https://www.stochasticlifestyle.com/how-to-train-interpretable-neural-networks-that-accurately-extrapolate-from-small-data/ …pic.twitter.com/sHrqGZaFy7
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Anshul Choudhary proslijedio/la je Tweet
By restructuring math expressions as a language, Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems. https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/ …pic.twitter.com/IL2H8ygDYC
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Anshul Choudhary proslijedio/la je Tweet
The funny thing about AIDungeon is due to all the GPT-2 pre-training on swaths of random web text, you can create an adventure game about literally anything. Here's one about installing OpenCV from source:pic.twitter.com/zJvtjBwcbq
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Anshul Choudhary proslijedio/la je Tweet
Thermodynamically-Efficient Local Computation: Classical and quantum information reservoirs and generators. http://arxiv.org/abs/2001.02258
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Anshul Choudhary proslijedio/la je Tweet
A ResNet 9 using Mish activation function beat the fastest CIFAR-10 training time to 94% accuracy on the Stanford DAWN Benchmark. Previous best - 28 seconds. New Score - 10.7 seconds. Find the PR - https://github.com/stanford-futuredata/dawn-bench-entries/pull/124 … . Official Results (not updated) - https://dawn.cs.stanford.edu/benchmark/#cifar10-train-time …pic.twitter.com/JEkAlqDc9x
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Art is separate from the artist. I would still read his work even though I would be least interested in him personally.https://twitter.com/nevalalee/status/1214581593618161665 …
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Anshul Choudhary proslijedio/la je Tweet
We are really happy to announce that our paper on 'Long-term stability of cortical population dynamics underlying consistent behavior' has finally appeared in Nature Neuroscience https://www.nature.com/articles/s41593-019-0555-4 …. A great collaboration with
@JAlGallego@mattperich@raeedcho@PresNCM 1/nPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Anshul Choudhary proslijedio/la je Tweet
I completed my 1st data science project ~30 years ago. Since then I've been continuously developing a questionnaire I use for all new data projects, to ensure the right info is available from the start. I'm sharing it publicly today for the first time.https://www.fast.ai/2020/01/07/data-questionnaire/ …
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Anshul Choudhary proslijedio/la je Tweet
New from
@zhixin_lu "Supervised Chaotic Source Separation by a Tank of Water" https://arxiv.org/abs/1912.07444 -- a bit of magic for the new year, in which water can be trained to separate signals from two chaotic attractors.pic.twitter.com/OWdTcLRhlG
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Anshul Choudhary proslijedio/la je Tweet
In 1956 "The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information” by George A. Miller of Harvard University was published. It was a landmark of human memory research. Bell Labs adopted memory chunking in phone numbers (xxx)-xxx-xxxxpic.twitter.com/SDsB22DRNu
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One describes AlphaFold, which uses deep neural networks to predict protein structures with high accuracy. AlphaFold made the most accurate predictions at the 2018 scientific community assessment CASP13. 1/4