Anil Ananthaswamy
@anilananth
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Sci journalist/TED speaker/MIT KSJ Fellow/Books: The Edge of Physics, The Man Who Wasn't There, Through Two Doors at Once / Mastodon: @[email protected]
itinerant
Joined April 2010
Don't know how other authors feel, but seeing the first physical copy of your book, after years of looking at Word files and PDFs. Seems surreal. It's as if someone else wrote it. Anyway, this advance copy arrived in the mail. One more month to pub date
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The Theoretical Minimum (for Machine Learning)โฆAnd Why Linear Algebra, Calculus, and Probability & Statistics often get mentioned as the minimum math you need to start on your machine learning journey. But why these disciplines? Hereโs an intuition for why:. Linear Algebra:
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The Many Moods of Machine Learning. If you feel overwhelmed by the jargon of machine learning and wonder how it all ties together, you arenโt alone. There's training vs test data, supervised vs unsupervised vs self-supervised learning, regression vs classification, linear vs
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Imagine being ๐๐๐๐ฎ๐ฌ๐๐, even in jest, of being the man who ๐ด๐ฆ๐ต ๐ฃ๐ข๐ค๐ฌ ๐ฅ๐ฆ๐ฆ๐ฑ ๐ญ๐ฆ๐ข๐ณ๐ฏ๐ช๐ฏ๐จ ๐ฃ๐บ ๐ต๐ธ๐ฐ ๐ฅ๐ฆ๐ค๐ข๐ฅ๐ฆ๐ด. ๐๐๐จ๐ซ๐ ๐ ๐๐ฒ๐๐๐ง๐ค๐จ, who proved one of the seminal ๐ฎ๐ง๐ข๐ฏ๐๐ซ๐ฌ๐๐ฅ ๐๐ฉ๐ฉ๐ซ๐จ๐ฑ๐ข๐ฆ๐๐ญ๐ข๐จ๐ง ๐ญ๐ก๐๐จ๐ซ๐๐ฆ๐ฌ, showed that a 1-hidden
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Before one groks it, ๐ฆ๐๐๐ก๐ข๐ง๐ ๐ฅ๐๐๐ซ๐ง๐ข๐ง๐ (๐๐) can seem abstruse, even for those with software and math backgrounds (I found it so, despite having once learned the necessary skills). But once you get it, the simplicity of the conceptual building blocks is striking.
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Key Resources for Deeper Dives into AI/ML. A number of people have asked about the lectures/courses on AI/ML that I found useful while researching and writing WHY MACHINES LEARN. Here's a redo of an earlier post, with some additions. ๐๐๐๐ก๐ข๐ง๐ ๐๐๐๐ซ๐ง๐ข๐ง๐
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There must be a ๐๐จ๐ฆ๐ฉ๐จ๐ฎ๐ง๐ ๐๐๐ซ๐ฆ๐๐ง ๐ฐ๐จ๐ซ๐ for how authors feel the day their book is released :-) Today is pub date for ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐: ๐๐ฉ๐ฆ ๐๐ญ๐ฆ๐จ๐ข๐ฏ๐ต ๐๐ข๐ต๐ฉ ๐๐ฆ๐ฉ๐ช๐ฏ๐ฅ ๐๐ฐ๐ฅ๐ฆ๐ณn ๐๐. Nearly 4-5 yrs of work in relative obscurity sees
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Sometimes, when writing a book, you encounter an idea so mind-bending, it doesn't leave you. For me, it was the answer this question: Why are deep neural networks universal function approximators? Turns out, understanding why functions are vectors is key; it's a truly eye-opening
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What? Linear algebra and calculus and machine learning for the holidays! Might a math-y book be a good gift to give someone for the holidays? I hope so :-). โA masterpiece.โ โGeoffrey Hinton, 2024 Nobel Laureate and Turing Award winner. โAfter just a few minutes of reading Why
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The Unreasonable Effectiveness of Linear Algebra. If you really want to understand whatโs happening in machine learning/AI, coming to grips with the basics of linear algebra is super important. I continue to be blown away by how much of ML becomes increasingly intuitive as one
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Some scientists I met and wrote about in 3 of my 4 books have won Nobel Prizes in physics after the book came out :-) The joy of writing about cutting-edge science! Not saying anything more, just in case anyone thinks otherwise. I'm trying to figure out who is most likely to win
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I'm never going to get another chance for this particular humble brag, so I'll take it :-) When Geoff Hinton endorsed WHY MACHINES LEARN sometime back in March/April, my impostor syndrome came to the fore (yes, writers have it too, not just scientists). Surely not, I thought at
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๐๐ก๐ ๐๐ก๐๐จ๐ซ๐๐ญ๐ข๐๐๐ฅ ๐๐ข๐ง๐ข๐ฆ๐ฎ๐ฆโฃโฃ.โฃโฃ.I owe a huge debt to two books that inspired ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐. Leonard Susskind's THE THEORETICAL MINIMUM (for classical mechanics) and Steven Strogatz's ๐๐๐
๐๐๐๐๐ ๐๐๐๐๐๐. They are different
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How do brains learn if not via the backpropagation algorithm that powers #DeepLearning and #ArtificialIntelligence ? Computational neuroscientists are closing in on some answers. My story for @QuantaMagazine .
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Did not have seen this coming! The Physics Nobel goes to John Hopfield and Geoff Hinton. Interviewing them was among the many highlights of writing Why Machines Learn. It took some persuasion to get Hopfield to talk to me--but he did, and it was such a joy! In fact, the chapter
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Will simply scaling up LLMs get us to AGI? My feature for @Nature, with inputs from @fchollet, @Yoshua_Bengio, @RaiaHadsell, @andrewgwils, @dileeplearning, @keyonV, @MelMitchell1 and Karl Friston.
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As the pub date for a new book approaches, writers harbor conflicting emotions: ๐ฃ๐จ๐ฒ๐๐ฎ๐ฅ of soon seeing the book out in the wild, ๐ง๐๐ซ๐ฏ๐จ๐ฎ๐ฌ that it's out in the wild and they can do little now to control its fate. ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐ is a week away from
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Finally, after a long pandemic-induced hiatus, @NCBS_Bangalore announces its 10th annual science journalism workshop. Application deadline: Jan 5, '23. Workshop dates: Feb 12-25, 2023. Apply! Spread the word!
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As authors, we have favorite stories that we couldn't somehow fit into our books. In ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐, I failed to find a place to tell the story of how AI pioneers ๐๐๐ซ๐ง๐ข๐ ๐๐ข๐๐ซ๐จ๐ฐ and ๐
๐ซ๐๐ง๐ค ๐๐จ๐ฌ๐๐ง๐๐ฅ๐๐ญ๐ญ had a friendly face-off in the
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#gravitationalwaves so hard to find because space-time is 1000 billion times stiffer than diamond; it takes immense energy to create ripples.
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What's the clearest example of neuroscience influencing AI? One might argue that the very idea of artificial neural networks is brain inspired. People quibble about just how realistic ANNs are compared to biological neural networks (they are not, but that's not the point).
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A simple ๐ฏ๐ข๐ฌ๐ฎ๐๐ฅ๐ข๐ณ๐๐ญ๐ข๐จ๐ง of why ๐ง๐๐ฎ๐ซ๐๐ฅ ๐ง๐๐ญ๐ฐ๐จ๐ซ๐ค๐ฌ, despite first being proposed in the late 1950s, remained a side-show in machine learning, until the back-propagation algorithm was developed in 1986. ๐
๐ซ๐๐ง๐ค ๐๐จ๐ฌ๐๐ง๐๐ฅ๐๐ญ๐ญ'๐ฌ ๐ฉ๐๐ซ๐๐๐ฉ๐ญ๐ซ๐จ๐ง
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Dan Dennett is no more.๐ This is really sad. He touched so many lives, with his deep and uncompromising philosophy, his humor and a gentle kindness that lay beneath it all. I'd say RIP Dan, but he'd have admonished anyone for saying that! From Bacteria to Bach and Back, Dan.
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Neural networks that map from one infinite-dimensional space to another solve partial differential equations orders of magnitude faster than numerical methods. My story for @QuantaMagazine @unique9881 #DeepLearning #AI #NeuralNetworks
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โWe are raising a generation of algorithms that are like undergrads [who] didnโt come to class the whole semester and then the night before the final, theyโre cramming." Alexei Efros on supervised learning. My story for @Quanta on self-supervised learning:
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1/20 #QuantumPhysics: Test your grasp of the double-slit experiment with this thread. Answer the polls as they come up and then read on to understand the central mystery of the #quantum world (images in this thread ยฉ Anil Ananthaswamy, Through Two Doors at Once, @DuttonBooks )
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You'll often see arguments that ๐๐๐๐ก๐ข๐ง๐ ๐๐๐๐ซ๐ง๐ข๐ง๐ is "๐ซ๐ถ๐ด๐ต" ๐ ๐ฅ๐จ๐ซ๐ข๐๐ข๐๐ ๐ฌ๐ญ๐๐ญ๐ข๐ฌ๐ญ๐ข๐๐ฌ. I respectfully beg to differ. To write ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐, I began coding after a 20-year gap (I was a distributed systems software architect in
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More evidence for predictive processing in the brain, from computational models to studies in mice. My story for @QuantaMagazine on work by @bill_lotter @neurobongo @TimKietzmann @tyrell_turing @KanakaRajanPhD @flodlan. Great editing by @tvjrennie
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Would it surprise you to learn that the algorithm used to train the simplest possible artificial neural network with just 1 hidden layer and 1 hidden neuron is exactly the same as the algorithm to train the largest deep neural networks (with 100s of hidden layers and millions of
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Wasn't expecting this when my UK publisher, Duckworth Books, decided to publish Through Two Doors at Once and The Man Who Wasn't There. They are bringing out all three of my books as a set (!) @Duckbooks @Matt_Casbourne #QuantumMechanics #consciousness #Self #physics
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Machine Learning is not just (glorified) statistics! Sure, in its most basic form, ML doesn't seem that far removed from fancy statistics. But ML is its own thing!. Steve Brunton, @eigensteve of the University of Washington, in his fabulous short lecture series on probability
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What does physics have to do with #DALLยทE 2? Diffusion models are all the rage; their origins lie in some cool principles from non-equilibrium thermodynamics. Work by @jaschasd @hojonathanho @YSongStanford @AnimaAnandkumar
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Sometimes, as an author, you get an endorsement that delights because of the endorser's way with words. My sincere thanks to @stevenstrogatz for this lovely blurb; it gets to the heart of why I wrote Why Machines Learn; @DuttonBooks @penguinrandom
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Back in 2007, Steven Weinberg's casual remark during a chat triggered an entire story, a deep look at supersymmetry(SUSY). Weinberg worried that the LHC would find the Higgs and nothing more. "I'm terrified. Discovering just the Higgs would really be a crisis." He was prescient!
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We first discovered the laws of gravity, and then those of quantum mechanics. But @seanmcarroll et. al. say nature may go about it the other way around: space-time and gravity could emerge from a fundamental quantum mechanical description of the universe.
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This long chat on WHY MACHINES LEARN and the basic math of ML with @MLStreetTalk's Tim Scarfe (@ecsquendor) remains my favorite.
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Teaching yourself machine learning using an AI code assistants is full of irony. While it's staggering how easy it is learn ML coding this way, the process also opens a window to what's at stake in terms of jobs and the future of at least some kinds of work. Recently, @Google
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A graph hypernetwork predicts parameters for other #deepneuralnetworks. Imitates pre-training and cuts down on thousands of steps of stochastic gradient descent. My story for @QuantaMagazine. @BorisAKnyazev @mengyer @thomaskipf & @PetarV_93
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1/n When my first book, The Edge of Physics, came out, a filmmaker, Steve Elkins, got in touch. He wanted to film the places I had been to (Siberia, Chile, Antarctica, Ladakh . ) and weave the story of these places and the physics, with other stories about slowness and silence
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Quantum quiz. Here's a build-up to a simple version of the double-slit experiment. It starts with light falling on a half-silvered mirror, or beamsplitter, which transmits half the light and reflects the rest (images in this thread ยฉ: Anil Ananthaswamy, Through Two Doors at Once)
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It's been three months of being a fellow at @KSJatMIT, and I still pinch myself. Studying at MIT and Harvard and Tufts. could not have imagined that science journalism would have landed me here, to think about philosophy of mind, machine learning and fiction
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The Unbearable Strangeness of Neural Networks. Maybe one day weโll fully understand why deep neural networks behave the way they do, but as of now their behavior stumps standard statistical machine learning theoryโat least, many ML theorists think so. The final chapter in WHY
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What LSD, magic mushrooms are telling us about the brain's predictive prowess. My story about #psychedelics, predictive processing, #perception and #hallucination for @KnowableMag. Featuring research by @anilkseth @RCarhartHarris @Artipago @KatrinPreller
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The 10th annual #sciencejournalism workshop @NCBS_Bangalore wrapped up yesterday. Last Fri, we marked 10 editions of the workshop with a dinner with alumni and faculty who have been a big part of the effort to foster #scicomm in India
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Anyone who has attended a #RogerPenrose talk will recognize his insanely complicated presentations using multiple overhead projector slides stacked atop each other. He would even attempt animations by jiggling the slides ๐ #NobelPrize2020
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Here's a simple, beautiful intuition for why neural networks with at least one hidden layer are universal function approximators: meaning they can model (to some arbitrary accuracy) any function that converts an input to an output. Recall integral calculus from high-school or
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One small thing Geoff Hinton and David Rumelhart did -- apropos of his physics #NobelPrize2024 -- that often goes unnoticed when we talk of his neural network work is the idea of symmetry breaking. Granted it's not quite the same as how physicists think of it, but it's worth
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Not often do you get to write a quantum physics story that starts in a Viennese cafรฉ, about an #AI that designs #quantum physics experiments that human imagination had failed to figure out. #MachineLearning My story for @sciam .
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We begin the 2nd decade of our science journalism workshop @NCBS_Bangalore. Application deadline: Feb 19, 2024. Please spread the word!
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Despite the ๐๐ฎ๐ซ๐ฌ๐ ๐จ๐ ๐๐ข๐ฆ๐๐ง๐ฌ๐ข๐จ๐ง๐๐ฅ๐ข๐ญ๐ฒ, sometimes machine learning algorithms work better by pushing data into higher dimensions. But why? Hereโs an ๐ข๐ง๐ญ๐ฎ๐ข๐ญ๐ข๐ฏ๐ ๐๐ฑ๐ฉ๐ฅ๐๐ง๐๐ญ๐ข๐จ๐ง.โฃ.โฃ.The very first single-layer neural networks, such as
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"The effort to understand the universe is one of the very few things that lifts a human life a little above the level of farce, and gives it some of the grace of tragedy"-Steven Weinberg in The First Three Minutes. His life was lived with immense grace! 1/n
Steven Weinberg, the 1979 Nobel laureate for physics, died today. A delightful companion who loved theater, he could recite the poetry of Gerard Manley Hopkins by heart, and wrote profoundly about the mysteries of creation. He loved life and left it reluctantly. Heโll be missed.
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The 9th Annual Science Journalism workshop @NCBS_Bangalore ended today. The class of 2019 below. For the first time we had 2 computer scientists and 2 physicists, a great, diverse group! Good luck to all of you. #Journalism #science Now for some beer ๐
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The moments when a book you are writing becomes real, sometimes frighteningly so: 1) When your publisher lists it on Amazon and you are in the dark: .And . (see next tweet).
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DO WE LIVE IN A SIMULATION? My @sciam story, with a nod to comic @chucknicecomic and @neiltyson and @StarTalkRadio; shows why @elonmusk is wrong and asks if . we test that we are in a matrix. The odds flip the day we create our own sim @LeeBillings
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Thereโs no better illustration of how uncertainty messes with our minds than the Monty Hall dilemma. If you havenโt tried answering the question posed by the host of the game show Letโs Make a Deal, give it go and see why it fooled the best of mathematicians. Hereโs the
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Marginal Revolution (@MargRev) picks this year's best non-fiction. I'm both a little stunned and very glad that WHY MACHINES LEARN, a book that doesn't eschew math and equations, made the list and almost made the "two to top the list"!. Marginal Revolution's @tylercowen writes:.
Best non-fiction books of 2024:
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Could dark matter as we think we know it be dead? Yet another ultra-diffuse galaxy found with seemingly no #darkmatter. If confirmed--a big if--the galaxy and its ilk pose challenges for theories of cold dark matter and MOND! @sciam @LeeBillings
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My #Penrose memory: Here's Penrose explaining to me his ideas about gravity-induced collapse of quantum superpositions, using his spectacles. One of the nicest physicists I have met! Congratulations to him on getting the physics #NobelPrize2020
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This needs widespread attention. A $5 hand centrifuge from @PrakashLab for #SARSCoV2 testing. No electricity! @kvijayraghavan.
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Call for applications for the 9th Science Journalism Workshop @NCBS_Bangalore. The deadline is 10th May! Get application in, or please spread the word. Details here:
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This weekend a dear friend took out his copies of my four books--and it's the first time I saw them stacked together. Served as a lovely reminder that it's worth pursuing something that at first is only visible faintly on the horizon. I'd have never have in a million years
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"Everywhere I went led me to where I didn't want to be. So I was stuck": Paul Simon on writing Bridge Over Troubled Waters. Beautiful!.
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Renewing call for applications. @NCBS_Bangalore. hosts the 10th Annual Science Journalism Workshop, after 2 years of pandemic-induced absence. Apply by Jan 10, 2023, to learn the nuts-and-bolts of science journalism. Details here: #SciComm
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.@NCBS_Bangalore announces the 9th edition of its Annual Science Journalism Workshop. We are open for applications. For details see: @thattai @stpalli @kvijayraghavan
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An intense 2 wks of @NCBS_Bangalore's journalism workshop ended. A fab cohort. I'm sure we'll see them write for others and for themselves @Shubawrite @prarabdh2804 @charudatta_n @dbdttpl @malavikakkumar @mahimasamraik_ @RithikaFernand7 Nishant Singh, Karthik Vinod, Hardi Talwani
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AN AI-based transcription service I am using just transcribed "Lorentz boost symmetry" as "Orange Juice Cemetery" ๐.
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Why does ๐ฆ๐๐๐ก๐ข๐ง๐ ๐ฅ๐๐๐ซ๐ง๐ข๐ง๐ suffer from the ๐๐ฎ๐ซ๐ฌ๐ ๐จ๐ ๐๐ข๐ฆ๐๐ง๐ฌ๐ข๐จ๐ง๐๐ฅ๐ข๐ญ๐ฒ? Because, as Julie Delon of the Universitรฉ ParisโDescartes says in her talks, "๐๐ฏ ๐ฉ๐ช๐จ๐ฉ-๐ฅ๐ช๐ฎ๐ฆ๐ฏ๐ด๐ช๐ฐ๐ฏ๐ข๐ญ ๐ด๐ฑ๐ข๐ค๐ฆ๐ด, ๐ฏ๐ฐ๐ฃ๐ฐ๐ฅ๐บ ๐ค๐ข๐ฏ ๐ฉ๐ฆ๐ข๐ณ ๐บ๐ฐ๐ถ
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The awesome ๐ฌ๐ฎ๐ฉ๐ฉ๐จ๐ซ๐ญ ๐ฏ๐๐๐ญ๐จ๐ซ ๐ฆ๐๐๐ก๐ข๐ง๐๐ฌ that ruled the roost in 2000s, before ๐ง๐๐ฎ๐ซ๐๐ฅ ๐ง๐๐ญ๐ฐ๐จ๐ซ๐ค๐ฌ became the darlings of ๐ฆ๐๐๐ก๐ข๐ง๐ ๐ฅ๐๐๐ซ๐ง๐ข๐ง๐ , can be traced back to ๐๐ญ๐ข๐ฅ๐ช๐ฎ๐ช๐ณ ๐๐ข๐ฑ๐ฏ๐ช๐ฌ'๐ด algorithm, which was an appendix in his 1964
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"Smarty Plants!" Are plants intelligent, maybe conscious even? @newscientist cover feature http://t.co/EejYLiusMv
http://t.co/VrjnCZReYO.
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A machine learning face-off that the world never got to see. In the late 1950s, there were two researchers working seriously on single-layer neural networks: Frank Rosenblatt at Cornell University and Bernie Widrow at Stanford. Rosenblatt had invented the perceptron and Widrow
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My alma mater @iitmadras's alumni association, @IITMAA, and @Infosys Science Foundation have organized a fireside chat. Prof. Balaraman Ravindran, head of @WSAI_IITM and I will talk about AI and Learning: 430PM onward, Jan 6, at the Infosys Science Foundation, Bangalore.
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To add to the research done at Bell Labs-it had an amazing group of #MachineLearning researchers in the 80s & 90s, who pioneered SVMs, neural networks, etc. Some I can think of : Sara Solla, Isabel Guyon, Yann LeCun, Corinna Cortes, Vladimir Vapnik. ML owes much to Bell Labs.
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Why the double-slit experiment should NOT be used to make definitive statements about #consciousness or the nature of #quantum reality: The experiment can be interpreted in many different ways and each offers a different view of what's going on. @sciam
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Adam Becker (@FreelanceAstro) and I, almost at the end of our stay @sfiscience, as journalism fellows attending the complex systems summer school in Santa Fe, NM.
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The Importance of Being Vectors. We hear over and over that to do machine learning is to do linear algebra. Which, in turn, has to do with learning about vectors and matrices. But why? Whatโs so amazing about this particular mathematical discipline as it pertains to ML?. Here,
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Many folks asked about the level of ๐ฆ๐๐ญ๐ก ๐ค๐ง๐จ๐ฐ๐ฅ๐๐๐ ๐ assumed of the reader of ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐. Anyone with exposure to high school-level math (mainly basic ๐ญ๐ซ๐ข๐ and ๐๐๐ฅ๐๐ฎ๐ฅ๐ฎ๐ฌ) can follow along easily. More important, I'm targeting the
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Machine Learningโs Debt to Nearest Neighbors. The simplicity of the k-Nearest Neighbor ruleโone of the staples of machine learningโbelies its rich history and enormous impact. Hereโs why the k-NN rule can help us appreciate some key conceptual underpinnings of ML. First, what is
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The hardcover of Through Two Doors at Once arrived yesterday @DuttonBooks @EmilyCanders @penguinrandom @PenguinRH_News
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We knew of the three possible fates for our universe: Big Freeze, Big Rip and Big Crunch. But there's a kid on the block, a possible unfurling of an extra dimension, making the cosmos indescribable with the physics we have: A @newscientist cover feature.
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To see WHY MACHINES LEARN mentioned alongside lecture videos by @AndrewYNg and @karpathy was not on my bingo card! I learned my ML from these experts (and others) and owe them a huge debt of gratitude. @BorisMeinardus.
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Bangalore folks who were asking about WHY MACHINES LEARN being available in local bookstores, looks like @blossombookhous (yes, that Blossom book house!) has a few :-).
#NewArrival ๐ Dive into the fascinating world of mathematics that has paved the way for machine learning and the rapid growth of artificial intelligence! ๐คโจ. Machine-learning systems are now making life-changing decisions: from approving mortgages to diagnosing cancer, and
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For all the fuss about who invented backpropagation, it's worth remembering that the Frank Rosenblatt--who designed the first single-layer artificial neural network, or the perceptron, back in the late 1950s--identified the problem of training multi-layer neural networks, or
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Never thought I'd author 3 books when I became a writer. It's Pub Day for Through Two Doors at Once. Please share/re-tweet--it's much appreciated. Available at local indie booksellers and at @DuttonBooks @penguinrandom @PenguinRH_News @EmilyCanders
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We might soon see neural networks that sip rather than gulp energy. My story on spiking #neuralnetworks for @SimonsInstitute, featuring work by @SanderBohte, @hisspikeness (Friedemann Zenke), @neuralreckoning (Dan Goodman) and @ChristianPehle :
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Of all the joys of @KSJatMIT fellowship, I did not expect this: talking about quantum mechanics to @danieldennett's class on Free Will. Loving the class, in which we grapple with the nuances of whether or not we have free will. Did I have any choice in taking this class? ๐
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"Will there be math? Oh, yes, there will be math. But Ananthaswamy is the best guide you could ask for on such a perilous journey." . This line in @theinformation about WHY MACHINES LEARN, named as one of the 5 best AI books of 2024, made me smile! I'm thrilled that an.
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Huge congrats to @aathiperinchery for winning the 2021 #Kavli #AAAS Science Journalism Award for her story Succession (. Her journey began with the @NCBS_Bangalore science journalism workshop (our first batch, 2011; @paldhous missing in this group photo):
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I wish I had found out about this murderous double-slit before I wrote THROUGH TWO DOORS AT ONCE ๐.
This is deep philosophical shit.
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Relieved! The 8th edition of the science journalism workshop @NCBS_Bangalore comes to a happy ending. all of us celebrating after a hard two weeks
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The Agony and Ecstasy of Machine Learning. I wrote WHY MACHINES LEARN because I was besotted by some of the math behind ML. The affair began during the peak of pandemic: repeated watching of YouTube lectures on ML during those weeks and months of isolation led me to appreciate
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.@MLStreetTalk asks about the basic mathematical disciplines needed to grasp machine learning. A clip from our conversation about WHY MACHINES LEARN:.via @YouTube.
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Science journalism workshop @NCBS_Bangalore. Deadline for applications is 15th May. Announcement at: .Please spread the word again: @thattai @1amnerd @sandygrains @SekarSandhya @PriyankaPulla @TIFRScience @ViditaVaidya @stpalli @kvijayraghavan
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What a place to think and write about consciousness! Beginning my writer's residency at The Bellagio Center, Lake Como, Italy! #RFBellagio @RockefellerFdn.
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๐๐ฒ ๐ฅ๐ข๐ฌ๐ญ ๐จ๐ ๐ฌ๐จ๐ฆ๐ ๐๐ง๐ ๐๐ ๐ข๐ง๐ , ๐ข๐ฅ๐ฅ๐ฎ๐ฆ๐ข๐ง๐๐ญ๐ข๐ง๐ ๐๐ง๐ ๐ข๐ง๐๐ซ๐๐๐ข๐๐ฅ๐ฒ ๐ฎ๐ฌ๐๐๐ฎ๐ฅ ๐ฏ๐ข๐๐๐จ ๐ฅ๐๐๐ญ๐ฎ๐ซ๐๐ฌ ๐จ๐ง ๐ฆ๐๐๐ก๐ข๐ง๐ ๐ฅ๐๐๐ซ๐ง๐ข๐ง๐ โฃโฃโฃ.โฃโฃโฃ.I could not have written ๐๐ก๐ฒ ๐๐๐๐ก๐ข๐ง๐๐ฌ ๐๐๐๐ซ๐ง without having had the luxury.
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An entirely unexpected outcome of researching WHY MACHINES LEARN during the pandemic was that I got to talk to my sources on Zoom (how many you can recognize? Some are, of course, extremely well-known--including the three new Nobel Laureates). There were so many highlights of
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One of the joys of opening boxes of books that I hadn't seen for 2 years+. And finding gems I want to reread. The late Dan Dennett's Intuition Pumps and @anilkseth's Being You.
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A generous endorsement from @skdh, gratefully received, for Why Machines Learn. โIf you were looking for a way to make sense of the AI revolution that is well underway, look no further." Preorder from your favorite indie bookstore or from, where else,
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A Quantum Cheshire Cat was separated from its grin in 2013. Now, a controversial thought experiment says two quantum Cheshire cats can exchange their grins. The upshot: properties of particles, such as their spin, may not belong to the particles. @sciam
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