CogView2 checkpoints are now publicly available! A huge win for open ML research and the first time a text-to-image model of this quality has been publicly released
https://t.co/epOolumZSv
Distill will be taking a one year hiatus starting today, which may be extended indefinitely. Our editorial team has written some reflections on what we've learned over the past five years, and the factors that led to this decision.
https://t.co/E31QPnPbMt
Forget large datasets like ImageNet. Researchers in Japan have shown that AIs can start learning to recognize everyday objects by being trained on computer-generated fractals instead.
https://t.co/fk17IG5hOK
Today, we’re introducing TextStyleBrush, the first self-supervised AI model that replaces text in existing images of both scenes and handwriting — in one shot — using just a single example word: https://t.co/0QfLraAQvV
Today we are #open-sourcing FLORES-101, a many-to-many evaluation data set covering 101 languages from all over the world. Our goal is helping empower researchers to create more diverse (and locally relevant) translation tools — learn more: https://t.co/oKWly6C1Jh
🎉🎉We are on ProductHunt today. 😻EasyOCR: No Code AI as a service. Automate text extraction from images https://t.co/FAdBVr0lOs @ProductHunt#NoCode#SaaS#OpenSource
🎉🎉We are honored to present our no code OCR solution: https://t.co/8hMovZBPj0. It is easy as its name: "EasyOCR". Experience more features beyond the open source version. Finetune OCR model to your use case with a few images. #CloudComputing#apidevelopment#NoCode#AI
💃 Dance, jump, and twirl! 🤸
We just released MoveNet, a new lightning-fast pose model in browser that's #MadeWithTFJS and designed to track fast motions and tough poses.
Learn more at #GoogleIO and try it yourself → https://t.co/QpfnVL0YYI
RepVGG: Making VGG-style ConvNets Great Again
paper: https://t.co/Y5WfgvqxHO
PyTorch code: https://t.co/ydk0RUf6JU
👌Spells out the benefits of very simple/uniform/fast (latency, not FLOPS) deployment architectures. A lot of complexity often due to optimization, not architecture.
ML model saves 90% on bandwidth during video-calls by using just an image of your face & some basic motion data.
Paper: https://t.co/AK5zxCRl9L (v/@nvidia)
Video: https://t.co/kuTiC4QoNQ (v/@twominutepapers)
#CVPR2021#Compression#DeepFakes#KindOf