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Andrew Trask Retweeted
OpenMined +
@PyTorch collaborating to advance open source software development. Learn about these talented teams on our blog: https://blog.openmined.org/pytorch-grant-recipients … Many opportunities ahead. Join our Slack community to find out more!Thanks. Twitter will use this to make your timeline better. UndoUndo -
Andrew Trask Retweeted
Welcome OpenAI to the PyTorch community!https://twitter.com/OpenAI/status/1222927584033247232 …
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Andrew Trask Retweeted
Here's a lecture by Andrew Trask (
@iamtrask) on privacy-preserving AI as part of the MIT Deep Learning lecture series. Preserving privacy boosts our ability to do science at a large-scale and to engineer intelligent systems that learn from data: https://www.youtube.com/watch?v=4zrU54VIK6k …pic.twitter.com/1jshZWpoJ9
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IMO, this is the best work I've ever read on AI & Human Values Highly recommended read for everyone in the
#AI field It's a dense read - but push through. You'll be glad you did.#100DaysOfMLCode#ArtificialIntelligence#DeepLearning#AIForGood https://twitter.com/IasonGabriel/status/1222154213674967040 …pic.twitter.com/HXqgotAZOX
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Andrew Trask Retweeted
If you want to learn about privacy-preserving machine learning, then there is no better resource than this step-by-step notebook tutorial by
@iamtrask. From the basics of private deep learning to building secure ML classifiers using PyTorch & PySyft.https://github.com/OpenMined/PySyft/tree/master/examples/tutorials …Thanks. Twitter will use this to make your timeline better. UndoUndo -
Commercial Encyclopaedia ->
@Wikipedia Commercial Software ->@github Commercial AI -> ???? Intelligence has a history of becoming free on the internet. AI will be no different.Thanks. Twitter will use this to make your timeline better. UndoUndo -
In the future - you will be able to own and control the only copies of your information While still receiving the same goods and services you receive now. Let's build the future we want to live in Don't know where to start? Join
@openminedorgThanks. Twitter will use this to make your timeline better. UndoUndo -
+1 for homeschooling
https://twitter.com/CJ_Johnson17th/status/1221130412237512704 …Thanks. Twitter will use this to make your timeline better. UndoUndo -
When I learn new idea, I must repeatedly learn it from multiple
#tutorials before it *clicks* If you're learning#convolutional nets - add this to your list It discusses#CNNs for: - images - audio - databases#100DaysOfMLCode#100DaysOfCode#AI http://brohrer.github.io/how_convolutional_neural_networks_work.html …pic.twitter.com/LKURUK36QQ
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#TransferLearning is one of the most important#AI techniques I don't often recommend PhD Thesis' -@seb_ruder's is exceptional. He's a brilliant writer! Check out this taxonomy / table of contents!!!

#100DaysOfMLCode#100DaysOfCode https://ruder.io/thesis/neural_transfer_learning_for_nlp.pdf …pic.twitter.com/ZSbZSwD9DT
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My phone should check each image I take for skin
#cancer The model should be: - Free - Apache 2 licensed - Crowdsourced using#FederatedLearning Similar to what#OpenSource did for software This is what@OpenMinedorg wants to do for AI Join us! http://slack.openmined.orgThanks. Twitter will use this to make your timeline better. UndoUndo -
If *anyone* would be un-hackable, surely it would be: 1) the world's wealthiest person 2) who leads one of the world's largest and most secure cloud platforms 3) running the world's second most popular phone OS Lesson learned: no-one is un-hackable.https://www.nytimes.com/2020/01/22/technology/jeff-bezos-hack-iphone.html …
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Googling Tip: when you want to learn some ML concept, google "python <concept name> from scratch". This will often lead to a blogpost with: - intuitive explanation - a toy implementation - reference to more formal papers which you can unpack in that order :)
#100DaysOfMLCodeThanks. Twitter will use this to make your timeline better. UndoUndo -
Andrew Trask Retweeted
Today we typically use centralized learning, but: - Centralized learning is good when you can bring the data to the model; - Federated learning is good when you can bring the model to the data; - Encrypted learning is for when you can’t do either.
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These guys scraped social media and created a smartphone app for facial recognition. "Sure, that might lead to a dystopian future or something, but you can’t ban it" "Clearview’s investors predict that its app will eventually be available to the public"https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html …
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Papers are published online - conferences should be too!!! More attendees ($30 instead of $2000+, no visa issues) More content (anyone could stream a talk) More often (
#NeurIPS every quarter)#NoTravel#GlobalWarming Seems like a no brainer Would you go to an#ArxivUnConf?Thanks. Twitter will use this to make your timeline better. UndoUndo -
Many
#privacy#AI experts have heard of#FederatedLearning, which is data-parallel Equally compelling, but less well known is#SplitNN, which is model-parallel Here@AJH4LL gives a step-by-step#tutorial implementing#SplitNN! A great piece!#100DaysOfMLCode#100DaysOfCodehttps://twitter.com/openminedorg/status/1217761044891938818 …
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After a year of dev, I am *extremely* excited to share this step-by-step
#notebook tutorial Goal: to be the *easiest* intro to#privacy preserving,#decentralized Deep Learning It's in@PyTorch I hope you enjoy it#GDPR#100DaysOfMLCode#100DaysOfCode https://github.com/OpenMined/PySyft/tree/master/examples/tutorials …pic.twitter.com/8XypqZ1TDS
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If you've wondered - "Which
#DeepLearning optimizer should I use?#SGD?#Adagrad?#RMSProp?" This blogpost by@seb_ruder is the best explanation I've seen. It's a surprisingly easy read! http://ruder.io/optimizing-gradient-descent/ … Definitely a great#100DaysOfMLCode /#100DaysOfCode project!pic.twitter.com/P4VWcL55eQThanks. Twitter will use this to make your timeline better. UndoUndo -
The *easiest* way to learn Deep Learning is to build it from scratch! IMO, the same is true when learning a Deep Learning framework. In
#GrokkingDeepLearning I show how to build a@PyTorch-like framework Here's the step-by-step code!!#100DaysOfMLCode https://github.com/iamtrask/Grokking-Deep-Learning …pic.twitter.com/xvekVP04qP
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