#cnns — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #cnns, aggregated by home.social.
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Speaking to #CNN’s #StateoftheUnion on Sunday, #TomHoman said “we’ll see” when host #JakeTapper asked whether #ICE "agents" will leave airports after #TSA personnel are paid. Homan said some of that decision will depend on whether TSA agents “come back to work” www.washingtonpost.com/politics/202...
ICE agents may remain at airpo... -
Speaking to #CNN’s #StateoftheUnion on Sunday, #TomHoman said “we’ll see” when host #JakeTapper asked whether #ICE "agents" will leave airports after #TSA personnel are paid. Homan said some of that decision will depend on whether TSA agents “come back to work” www.washingtonpost.com/politics/202...
ICE agents may remain at airpo... -
Speaking to #CNN’s #StateoftheUnion on Sunday, #TomHoman said “we’ll see” when host #JakeTapper asked whether #ICE "agents" will leave airports after #TSA personnel are paid. Homan said some of that decision will depend on whether TSA agents “come back to work” www.washingtonpost.com/politics/202...
ICE agents may remain at airpo... -
#Canadian political analyst @[email protected] discusses #CNN's #JakeTapper and #AndersonCooper, who have embraced a new look, and it's getting a lot of people talking.. or laughing. youtu.be/tfrurOwYmU8?...
CNN Embraces New ‘Streamer’ Ae... -
#Canadian political analyst @[email protected] discusses #CNN's #JakeTapper and #AndersonCooper, who have embraced a new look, and it's getting a lot of people talking.. or laughing. youtu.be/tfrurOwYmU8?...
CNN Embraces New ‘Streamer’ Ae... -
#Canadian political analyst @[email protected] discusses #CNN's #JakeTapper and #AndersonCooper, who have embraced a new look, and it's getting a lot of people talking.. or laughing. youtu.be/tfrurOwYmU8?...
CNN Embraces New ‘Streamer’ Ae... -
Former Transportation Secretary @[email protected], who served as a Navy officer, spoke to #CNN’s @[email protected] about the loss of US service members in the #Iran conflict and the Trump administration’s handling of the military campaign. #USpoli youtu.be/61mDCG2PFvs?...
‘Amateur hour’: Buttigieg slam... -
#CNN's #ScottJennings shrugged off the death of the blind #NurulAminShahAlam after #BorderPatrol dropped him off in the freezing cold. #CenkUygur, @[email protected] and #ElliottMorgan discuss on #TheYoungTurks. youtu.be/IGgXlcwdLTA?...
Scott Jennings' DEPRAVED Take ... -
#CNN's #ScottJennings shrugged off the death of the blind #NurulAminShahAlam after #BorderPatrol dropped him off in the freezing cold. #CenkUygur, @[email protected] and #ElliottMorgan discuss on #TheYoungTurks. youtu.be/IGgXlcwdLTA?...
Scott Jennings' DEPRAVED Take ... -
#CNN's #ScottJennings shrugged off the death of the blind #NurulAminShahAlam after #BorderPatrol dropped him off in the freezing cold. #CenkUygur, @[email protected] and #ElliottMorgan discuss on #TheYoungTurks. youtu.be/IGgXlcwdLTA?...
Scott Jennings' DEPRAVED Take ... -
#CNN's #ScottJennings shrugged off the death of the blind #NurulAminShahAlam after #BorderPatrol dropped him off in the freezing cold. #CenkUygur, @[email protected] and #ElliottMorgan discuss on #TheYoungTurks. youtu.be/IGgXlcwdLTA?...
Scott Jennings' DEPRAVED Take ... -
#CNN's #ScottJennings shrugged off the death of the blind #NurulAminShahAlam after #BorderPatrol dropped him off in the freezing cold. #CenkUygur, @[email protected] and #ElliottMorgan discuss on #TheYoungTurks. youtu.be/IGgXlcwdLTA?...
Scott Jennings' DEPRAVED Take ... -
"House Speaker #MikeJohnson dismissed bipartisan calls for Commerce Secretary #HowardLutnick to resign over his ties to convicted child sex predator #JeffreyEpstein as “absurd” #CNN’s #ManuRaju asked Johnson on Tuesday about the resignation calls against Lutnick www.mediaite.com/media/news/m...
Mike Johnson Defends Trump Off... -
"House Speaker #MikeJohnson dismissed bipartisan calls for Commerce Secretary #HowardLutnick to resign over his ties to convicted child sex predator #JeffreyEpstein as “absurd” #CNN’s #ManuRaju asked Johnson on Tuesday about the resignation calls against Lutnick www.mediaite.com/media/news/m...
Mike Johnson Defends Trump Off... -
"House Speaker #MikeJohnson dismissed bipartisan calls for Commerce Secretary #HowardLutnick to resign over his ties to convicted child sex predator #JeffreyEpstein as “absurd” #CNN’s #ManuRaju asked Johnson on Tuesday about the resignation calls against Lutnick www.mediaite.com/media/news/m...
Mike Johnson Defends Trump Off... -
#DonaldTrump made misogynistic comments to #CNN's #KaitlanCollins, Speaker #MikeJohnson claims to know more about #TheBible than the Pope, and journalists are outraged at #JeffBezos over mass layoffs in the newsroom at @[email protected] youtu.be/6Irn2IPmGvk?...
Donald Trump Is Nothing To Smi... -
#DonaldTrump made misogynistic comments to #CNN's #KaitlanCollins, Speaker #MikeJohnson claims to know more about #TheBible than the Pope, and journalists are outraged at #JeffBezos over mass layoffs in the newsroom at @[email protected] youtu.be/6Irn2IPmGvk?...
Donald Trump Is Nothing To Smi... -
#DonaldTrump made misogynistic comments to #CNN's #KaitlanCollins, Speaker #MikeJohnson claims to know more about #TheBible than the Pope, and journalists are outraged at #JeffBezos over mass layoffs in the newsroom at @[email protected] youtu.be/6Irn2IPmGvk?...
Donald Trump Is Nothing To Smi... -
#CNN's @[email protected] asked #SecretaryofAgriculture #BrookeRollins for MORE details about Trump's most recent farmer bailout. @[email protected] 's @[email protected] breaks it down on #RebelHQ. youtu.be/1Cab7xaaR90?...
Reporter Fact-Checks Trump Sec... -
#CNN's @[email protected] asked #SecretaryofAgriculture #BrookeRollins for MORE details about Trump's most recent farmer bailout. @[email protected] 's @[email protected] breaks it down on #RebelHQ. youtu.be/1Cab7xaaR90?...
Reporter Fact-Checks Trump Sec... -
#CNN's @[email protected] asked #SecretaryofAgriculture #BrookeRollins for MORE details about Trump's most recent farmer bailout. @[email protected] 's @[email protected] breaks it down on #RebelHQ. youtu.be/1Cab7xaaR90?...
Reporter Fact-Checks Trump Sec... -
#CNN's Chief International Anchor and host of the global affairs program, #Amanpour, #ChristianeAmanpour sits down with #JonStewart to discuss how the #Epsteinscandal has highlighted the IMPORTANCE of truth-based journalism. youtu.be/A0qdQto1T9k?...
Christiane Amanpour - Journali... -
#CNN's Chief International Anchor and host of the global affairs program, #Amanpour, #ChristianeAmanpour sits down with #JonStewart to discuss how the #Epsteinscandal has highlighted the IMPORTANCE of truth-based journalism. youtu.be/A0qdQto1T9k?...
Christiane Amanpour - Journali... -
Join @tarapalmeri.bsky.social on a special edition of #TheTaraPalmeriShow as she appears on #CNN’s #ErinBurnettOutFront, diving into the seismic news of #PrinceAndrew losing his royal title in the wake of #VirginiaGiuffre’s explosive book, #Nobody’sGirl. youtu.be/RAmGjopFUxU?...
Prince Andrew STRIPPED of Roya... -
Join @tarapalmeri.bsky.social on a special edition of #TheTaraPalmeriShow as she appears on #CNN’s #ErinBurnettOutFront, diving into the seismic news of #PrinceAndrew losing his royal title in the wake of #VirginiaGiuffre’s explosive book, #Nobody’sGirl. youtu.be/RAmGjopFUxU?...
Prince Andrew STRIPPED of Roya... -
"Ah, the riveting showdown between #ViTs and #CNNs, where you get a convoluted explanation on how images are turned into a mush of pixels and self-attention. 😴 But don't worry, you won't be distracted by any tracking or analytics, because apparently, nobody cares to watch this spectacle. 🤷♂️ If you can't read code without JavaScript, that's your problem, not ours. 🖼️🔍"
https://lucasb.eyer.be/articles/vit_cnn_speed.html #imageprocessing #selfattention #techhumor #HackerNews #ngated -
Today I tried out #AMD #Instinct #MI300a for my existing Deep Learning pipeline. Good news: It worked out of the box. Bad news: For some reason it could not beat my local #Nvidia #1080ti...
After trying all sorts of #ROCM installation methods via prebuild wheels, #apptainer images etc I tried #nanogpt by @karpathy and sure enought: The gpt code ran approx 2x faster than on a #a100 ... I hope that this is due to my programming skills. Not AMD prefering #transformers over #CNNs ... -
Today I tried out #AMD #Instinct #MI300a for my existing Deep Learning pipeline. Good news: It worked out of the box. Bad news: For some reason it could not beat my local #Nvidia #1080ti...
After trying all sorts of #ROCM installation methods via prebuild wheels, #apptainer images etc I tried #nanogpt by @karpathy and sure enought: The gpt code ran approx 2x faster than on a #a100 ... I hope that this is due to my programming skills. Not AMD prefering #transformers over #CNNs ... -
Today I tried out #AMD #Instinct #MI300a for my existing Deep Learning pipeline. Good news: It worked out of the box. Bad news: For some reason it could not beat my local #Nvidia #1080ti...
After trying all sorts of #ROCM installation methods via prebuild wheels, #apptainer images etc I tried #nanogpt by @karpathy and sure enought: The gpt code ran approx 2x faster than on a #a100 ... I hope that this is due to my programming skills. Not AMD prefering #transformers over #CNNs ... -
🧠 Exploring secrets of human vision today at #McGill University! I'll be talking about how our brains achieve efficient visual processing through foveated retinotopy - nature's brilliant solution for high-res central vision.
👉 When: Wednesday 9th of January 2025 at 12 noon.
👉 Where: CRN seminar room, Montreal General Hospital, Livingston Hall, L7-140, with hybrid option.
with Jean-Nicolas JÉRÉMIE and Emmanuel Daucé
📄 Read our findings: https://arxiv.org/abs/2402.15480
TL;DR: Standard #CNNs naturally mimic human-like visual processing when fed images that match our retina's center-focused mapping. Could this be the key to more efficient AI vision systems?
https://laurentperrinet.github.io/talk/2025-01-08-brain-seminar/
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#ConvolutionalNeuralNetworks (#CNNs in short) are immensely useful for many #imageProcessing tasks and much more...
Yet you sometimes encounter some bits of code with little explanation. Have you ever wondered about the origins of the values for image normalization in #imagenet ?
- Mean:
[0.485, 0.456, 0.406](for R, G and B channels respectively) - Std:
[0.229, 0.224, 0.225]
Strangest to me is the need for a three-digits precision. Here, after finding the origin of these numbers for MNIST and ImageNet, I am testing if that precision is really important : guess what, it is not (so much) !
👉 if interested in more details, check-out https://laurentperrinet.github.io/sciblog/posts/2024-12-09-normalizing-images-in-convolutional-neural-networks.html
- Mean:
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'A Rainbow in Deep Network Black Boxes', by Florentin Guth, Brice Ménard, Gaspar Rochette, Stéphane Mallat.
http://jmlr.org/papers/v25/23-1573.html
#cnns #deep #randomness -
'Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds', by Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao.
http://jmlr.org/papers/v25/24-0066.html
#cnns #cnn #dimensional -
'A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks', by Yuxin Sun, Dong Lao, Anthony Yezzi, Ganesh Sundaramoorthi.
http://jmlr.org/papers/v25/23-0137.html
#sgd #gradient #cnns -
@arasrinivas
Entertainment aside, getting rid of #CNNs for real-world #AI deployment is almost impossible. Even if you went for a ViT architecture, you must process the input using local patches with shared weights for efficiency and generalization. It is even more the case for processing multiple frames at a video level, like in Tesla FSD.Full thread https://x.com/aravsrinivas/status/1795509237550059733?s=46
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I remembered playing with DeepDream computer vision program that uses CNN (Convolutional Neural Network) almost 10 years ago. How fun it was to be able to run it locally on one my machines despite being very slow. Luckily I was able to find an already trained model, because training it locally was not feasible for me.
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I remembered playing with DeepDream computer vision program that uses CNN (Convolutional Neural Network) almost 10 years ago. How fun it was to be able to run it locally on one my machines despite being very slow. Luckily I was able to find an already trained model, because training it locally was not feasible for me.
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I remembered playing with DeepDream computer vision program that uses CNN (Convolutional Neural Network) almost 10 years ago. How fun it was to be able to run it locally on one my machines despite being very slow. Luckily I was able to find an already trained model, because training it locally was not feasible for me.
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I remembered playing with DeepDream computer vision program that uses CNN (Convolutional Neural Network) almost 10 years ago. How fun it was to be able to run it locally on one my machines despite being very slow. Luckily I was able to find an already trained model, because training it locally was not feasible for me.
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Please join us for this exciting public seminar from Mario Doumet (University of Toronto) who will be talking about their most recent work on #FPGA acceleration of #CNNs.
Zoom: https://utoronto.zoom.us/j/82613229697
October 24, 2023 at 9am EST (2pm UK time) -
A perspective on #chatGPT (or Large Language Models #LLMs in general): #Hype or milestone?
[Rodney Brooks (https://spectrum.ieee.org/amp/gpt-4-calm-down-2660261157) tells us that
What large language models are good at is saying what an answer should sound like, which is different from what an answer should be.
For a nice in-depth technical analysis, see this blog post by Stephen Wolfram (himself!) on "What is ChatGPT Doing ... and Why Does It Work? ". Worth reading -even for non-experts- in a non-trivial effort to make the whole process explainable. The different steps are:
#LLMs compute probabilities for the next word. To do this, they aggregate huge datasets of text so that they create a function that, given a sequence of words, computes for all possible words in the dictionary the probability that adding this new word is statistically congruent with past words. Interestingly, this probability, conditioned on what has been observed so far, falls of as a power law, just like the global probability of words in the dictionary,
These #probabilities are computed by a function that leans on the dataset to generate the best approximation. Wolfram makes a minute description of how to do such an approximation, starting from linear regression to using non-linearities. This leads to deep learning methods and their potential for universal function approximators,
Crucial is how these #models are trainable, in particular by way of #backpropagation. This leads the author to describe the process, but also to point out some limitations of the trained model, especially, as you might have guessed, compared to potentially more powerful systems, like #cellularautomata of course...
This now brings us to #embeddings, the crucial ingredient to define "words" in these #LLMs models. To relate "alligator" to "crocodile" vs. a "vending machine," this technique computes distances between words based on their relative distance in the large dataset of text corpus, so that each word is assigned an address in a high-dimensional space, with the intuition that words that are syntactically closer should be closer in the embedding space. It is highly non-trivial to understand the geometry of high-dimensional spaces - especially when we try to relate it to our physical 3D space - but this technique has proven to give excellent results, I highly recommend the #cemantix puzzle to test your intuition about word embeddings: https://cemantle.certitudes.org
Finally, these different parts are glued together by a humongous #transformer network. A standard #NeuralNetwork could perform a computation to predict the probabilities for the next word, but the results would mostly give nonsensical answers... Something more is needed to make this work. Just as traditional Convolutional Neural Networks #CNNs hardwire the fact that operations applied to an image should be applied to nearby pixels first, transformers do not operate uniformly on the sequence of words (i.e., embeddings), but weight them differently to ultimately get a better approximation. It is clear that much of the mechanism is a bunch of heuristics selected based on their performance - but we can understand the mechanism as giving different weights to different tokens - specifically based on the position of each token and its importance in the meaning of the current sentence. Based on this calculation, the sequence is reweighted so that a probability is ultimately computed. When applied to a sequence of words where words are added progressively, this creates a kind of loop in which the past sequence is constantly re-processed to update the generation.
Can we do more and include syntax? Wolfram discusses the internals of #chatGPT, and in particular how it trained iOS to "be a good bot" - and adds another possibility, which is to inject the knowledge that language is organized grammatically, and whether #transformers are able to learn such rules. This points to certain limitations of the architecture and the potential of using graphs as a generalization of geometric rules. The post ends with a comparison of #LLMs, which just aim to sound right, with rule-based models, a debate reminiscent of the older days of AI...
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What are convolutional neural networks? - Convolutional neural networks (CNNs) are a class of deep neural n... - https://cointelegraph.com/explained/what-are-convolutional-neural-networks #convolutionalneuralnetworks #cnns
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'Topological Convolutional Layers for Deep Learning', by Ephy R. Love, Benjamin Filippenko, Vasileios Maroulas, Gunnar Carlsson.
http://jmlr.org/papers/v24/21-0073.html
#cnn #cnns #topological -
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Liyao Gao, Guang Lin, Wei Zhu
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MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth
Chenjie Cao, Xinlin Ren, Yanwei Fu
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Omg omg omg there's a new #3blue1brown video and it's about convolutions and it is beautiful ✨✨✨ https://youtu.be/KuXjwB4LzSA
#MachineLearning #ExplainableAI #Education #AI #XAI #ArtificialIntelligence #NeuralNetworks #CNNs #ComputerScience #learning
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A demo from 1993 of 32-year-old Yann LeCun showing off the world's first convolutional network for text recognition. #tbt #ML #neuralnetworks #CNNs #MachineLearning
🐦🔗: https://twitter.com/MIT_CSAIL/status/1347237563342340097
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Google used deep learning to improve short-term weather forecasts - Enlarge (credit: YakobchukOlena)
A research team at Google has developed a deep neural network t... more: https://arstechnica.com/?p=1643443 #weatherforecasts #machinelearning #deeplearning #science #google #cnns
