Mingxing Tan @tanmingxing
Waymo Research, Google Brain Joined October 2013-
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Learn how DeepFusion, a fully end-to-end multi-modal 3D detection framework, applies a simple yet effective feature fusion strategy to unify the signals from two sensing modalities and achieve state-of-the-art performance. goo.gle/3M2UgRI
Open-domain dialog—where a model converses about any topic—is a key challenge for language models. Learn about LaMDA, a project to build dialog models that are more safe, grounded, high quality, and in line with our Responsible AI Principles ↓ goo.gle/3KJ2oXJ
As in past years, I've spent part of the holiday break summarizing much of the work we've done in @GoogleResearch over the last year. On behalf of @Google's research community, I'm delighted to share this writeup (this year grouped into five themes). ai.googleblog.com/2022/01/google…
Wish your neural networks faster and more accurate? Check out our recent EfficientNetV2 and CoAtNet, which significantly speed up the training and inference, while achieving state-of-the-art 90.88% top-1 accuracy on ImageNet.
Wish your neural networks faster and more accurate? Check out our recent EfficientNetV2 and CoAtNet, which significantly speed up the training and inference, while achieving state-of-the-art 90.88% top-1 accuracy on ImageNet.
🆕 The new EfficientNet V2 models are available on #TFHub! They’re a family of image classification models that achieves greater parameter efficiency and faster training speed. Take a look → goo.gle/3fAfmJ3
Happy to introduce CoAtNet: combining convolution and self-attention in a principled way to obtain better capacity and better generalization. 88.56% top-1 with ImageNet21K (13M imgs), matching ViT-huge with JFT (300M imgs). Paper: arxiv.org/abs/2106.04803
For those may have missed it, the official EfficientNetV2 weights are out for Tensorflow/Keras. I've converted the weights and verified all variants in #PyTorch (github.com/rwightman/pyto…). Thanks @tanmingxing and Google Brain for the consistent releases.
For those may have missed it, the official EfficientNetV2 weights are out for Tensorflow/Keras. I've converted the weights and verified all variants in #PyTorch (github.com/rwightman/pyto…). Thanks @tanmingxing and Google Brain for the consistent releases.
AK @_akhaliq
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54K Followers 1K Following PhD at 19 | Founder and CEO at @MedARC_AI | Research Director at @StabilityAI | @kaggle Notebooks GM | Biomed. engineer @ 14 | TEDx talk➡https://t.co/xPxwKTq6QbAleksa Gordić 🍿�.. @gordic_aleksa
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2K Followers 2K Following Creates AI projects useful to the world. Loves to educate. Do only good everyday, be wholesome to people. Dogecoin tip jar: DL8XxKdUtz4qthNr6yi2NUbJoSJdSprZXr₿bernard @b_bernardeschi
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310K Followers 3K Following AI research paper tweets, ML @Gradio (acq. by @HuggingFace 🤗) dm for promo follow on Hugging Face: https://t.co/q2Qoey80GxAndrej Karpathy @karpathy
980K Followers 905 Following 🧑🍳. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets 🧠🤖💥Yann LeCun @ylecun
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1.0M Followers 913 Following Co-Founder of Coursera; Stanford CS adjunct faculty. Former head of Baidu AI Group/Google Brain. #ai #machinelearning, #deeplearning #MOOCsRoss Wightman @wightmanr
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380K Followers 77 Following Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundationJeremy Howard @jeremyphoward
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107K Followers 0 Following Invented principles of meta-learning (1987), GANs (1990), Transformers (1991), very deep learning (1991), etc. Our AI is used many billions of times every day.rohan anil @_arohan_
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2.2M Followers 23 Following Google AI is focused on bringing the benefits of AI to everyone. In conducting and applying our research, we advance the state-of-the-art in many domains.Jeff Dean (@🏡) @JeffDean
296K Followers 6K Following Chief Scientist, Google DeepMind and Google Research. Co-designer/implementor of things like @TensorFlow, MapReduce, Bigtable, Spanner, Gemini .. (he/him)Eric Jang @ericjang11
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85 Followers 57 Following Husband. Father. Engineering Director. Science & book nerd. Lifelong hockey player. Grew up in small town USA. Adult life lived in Madison,SF Bay Area, Boulder.Saining Xie @sainingxie
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19K Followers 2K FollowingTanishq Mathew Abraha.. @iScienceLuvr
54K Followers 1K Following PhD at 19 | Founder and CEO at @MedARC_AI | Research Director at @StabilityAI | @kaggle Notebooks GM | Biomed. engineer @ 14 | TEDx talk➡https://t.co/xPxwKTq6QbNew open-source language model from Google AI: Flan-T5 🍮 Flan-T5 is instruction-finetuned on 1,800+ language tasks, leading to dramatically improved prompting and multi-step reasoning abilities. Public models: bit.ly/3sbNPDJ Paper: arxiv.org/abs/2210.11416
Honored that our 2012 paper "Building High-level Features Using Large Scale Unsupervised Learning" received an @icmlconf Test of Time Award honorable mention! Joint work with @quocleix, @MarcRanzato, @rajatmonga, Matthieu Devin, Kai Chen, @greg_corrado, myself, & @AndrewYNg.
I've been comparing a lot of transformer variants on large models (400M params): Post/Pre-LN, DeepNet, NormFormers, Swin v2, GLU variants, RMSNorm, Sandwich LN, with GELU, Swish, SmeLU… More than 2,000h of total training time on TPU v3's 😯 Here are my findings 🤓
PolyLoss (openreview.net/forum?id=gSdSJ…) is an ICLR 2022 paper which investigates the modifying the Cross Entropy objective in various ways, seemed like a strange idea to me that we might modify or even learn the loss function so played around with it a bit. 🧵
#AI #MachineLearning #DeepLearning #DataScience #ICLR2022 #PolyLoss #Mathematics #Math
Still using cross-entropy loss or focal loss? Now you have a better choice: PolyLoss Our ICLR’22 paper shows: with one line of magic code, Polyloss improves all image classification, detection, and segmentation tasks, sometimes by a large margin. Arixv: arxiv.org/abs/2204.12511
Wow! I am yet to read the paper and play with the code. But I find such simple and "basic" ideas really beautiful.
Still using cross-entropy loss or focal loss? Now you have a better choice: PolyLoss Our ICLR’22 paper shows: with one line of magic code, Polyloss improves all image classification, detection, and segmentation tasks, sometimes by a large margin. Arixv: arxiv.org/abs/2204.12511
A new framework for designing loss functions, PolyLoss, that outperforms cross-entropy loss and focal loss on image classification, instance segmentation, object detection, and 3D object detection tasks. #DeepLearning
Still using cross-entropy loss or focal loss? Now you have a better choice: PolyLoss Our ICLR’22 paper shows: with one line of magic code, Polyloss improves all image classification, detection, and segmentation tasks, sometimes by a large margin. Arixv: arxiv.org/abs/2204.12511
@tanmingxing Adding this to my bag of magic ML tricks
@tanmingxing Congrats! I am one of reviewers for this paper. 😅 I like it.
Learn how DeepFusion, a fully end-to-end multi-modal 3D detection framework, applies a simple yet effective feature fusion strategy to unify the signals from two sensing modalities and achieve state-of-the-art performance. goo.gle/3M2UgRI
Introducing the 540 billion parameter Pathways Language Model. Trained on two Cloud #TPU v4 pods, it achieves state-of-the-art performance on benchmarks and shows exciting capabilities like mathematical reasoning, code writing, and even explaining jokes. goo.gle/3j6eMnK
Revisiting Multi-Scale Feature Fusion for Semantic Segmentation abs: arxiv.org/abs/2203.12683 ESeg-Lite-L runs at 79 FPS and achieves 80.1% mIoU, largely closing the gap between real-time and high performance segmentation models
"We build a grid of Block-NeRFs from 2.8 million images to create the largest neural scene representation to date, capable of rendering an entire neighborhood of San Francisco."
Block-NeRF: Scalable Large Scene Neural View Synthesis abs: arxiv.org/abs/2202.05263 project page: waymo.com/research/block…
As in past years, I've spent part of the holiday break summarizing much of the work we've done in @GoogleResearch over the last year. On behalf of @Google's research community, I'm delighted to share this writeup (this year grouped into five themes). ai.googleblog.com/2022/01/google…
I’ve been tweeting about Covid for nearly 2 years. But this week it became personal when my 28-year-old younger son got it. With his permission, I’ll describe his experience & how I approached his situation, given the realities of life and the rapidly changing evidence.(1/25)
New in the #WolframNetRepo: Detect and localize objects with EfficientDet Trained on MS-COCO Data. wolfr.am/10Yc6jEHg Thanks @tanmingxing, @ruomingpang, @quocleix at @Google for creating this model wolfr.am/10YcakozM. #WolframNetRepo #neuralnetwork #ML #AI
Day 24/30: 🥇 EfficientDet is a very popular object detection model for a good reason! Let’s see why 📌 EfficientDet achieved State-Of-The-Art (SOTA) accuracy while reducing both the size of parameters, and the FLOPS, when it was released. It’s still a very good contender.
EfficientNetV2 from @GoogleAI proposes faster training with smaller datasets for image classification. Try it directly in the browser with this @Gradio demo! huggingface.co/spaces/osansev… Blog: ai.googleblog.com/2021/09/toward…