Data Science by ODS.ai 🦜

2023-02-13 22:53:04 We really love machine learning competitions! Competitions help us to explore new methods and solve problems that are not available at work.

We are organizing a new semester of ML training.
We are waiting for you online and offline in Moscow.

When: February 16, 2023, (19:00 Moscow time, 16:00 UTC)

Registration is required, the language is Russian. Open / Comment

2023-02-13 14:50:05 ​​Dual PatchNorm

The authors propose a new method, Dual PatchNorm, for Vision Transformers which involves adding two Layer Normalization layers before and after the patch embedding layer. Experiments across three datasets show that this method improves the performance of well-tuned ViT models, and qualitative experiments support this.

Paper: https://arxiv.org/abs/2302.01327

A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-dual-patch-norm

#deeplearning #cv #transformer Open / Comment

2023-02-11 15:26:22 An interesting perspective here. What if LLMs are viewed though the lens of Microsoft willing to take some part of the search market?

Trends in the dollar training cost of machine learning systems - https://epochai.org/blog/trends-in-the-dollar-training-cost-of-machine-learning-systems
The Inference Cost Of Search Disruption – Large Language Model Cost Analysis - https://www.semianalysis.com/p/the-inference-cost-of-search-disruption
The AI Brick Wall – A Practical Limit For Scaling Dense Transformer Models, and How GPT 4 Will Break Past It - https://www.semianalysis.com/p/the-ai-brick-wall-a-practical-limit
Training Compute-Optimal Large Language Models - https://arxiv.org/pdf/2203.15556.pdf Open / Comment

2023-02-06 13:24:22 ​​Cut and Learn for Unsupervised Object Detection and Instance Segmentation

CutLER (Cut-and-LEaRn) is a new approach for training unsupervised object detection and segmentation models without using any human labels. It uses a combination of a MaskCut approach to generate object masks and a robust loss function to learn a detector. The model is simple and compatible with different detection architectures and can detect multiple objects. It is a zero-shot detector, meaning it performs well without additional in-domain data and is robust against domain shifts across various types of images. CutLER can also be used as a pretrained model for supervised detection and improves performance on few-shot benchmarks. Results show improved performance over previous work, including being a zero-shot unsupervised detector and surpassing other low-shot detectors with finetuning.

Paper: https://arxiv.org/abs/2301.11320

Code link: https://github.com/facebookresearch/CutLER1

A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-cutler

#deeplearning #cv #objectdetection #imagesegmentation Open / Comment

2023-02-03 12:12:30 Dreamix: Video Diffusion Models are General Video Editors

New Google's text-based motion model.

Given a small collection of images showing the same subject, Dreamix can generate new videos with the subject in motion.

Всего из нескольких картинок или ролику новая модель от Google - Dreamix генерирует видео по текстовому описанию!

На видео Dreamix превращает обезьяну в танцующего медведя по промпту «Медведь танцует и прыгает под веселую музыку, двигая всем телом».

Project: https://dreamix-video-editing.github.io/

Paper: https://arxiv.org/pdf/2302.01329.pdf

Video:


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ai_machinelearning_big_data Open / Comment

2023-01-29 17:04:18 ​​StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis

In this paper, the authors propose StyleGAN-T, a model designed for large-scale text-to-image synthesis. With its large capacity, stable training on diverse datasets, strong text alignment, and controllable variation-text alignment tradeoff, StyleGAN-T outperforms previous GANs and even surpasses distilled diffusion models, the previous frontrunners in fast text-to-image synthesis in terms of sample quality and speed.

StyleGAN-T achieves a better zero-shot MS COCO FID than current state of-the-art diffusion models at a resolution of 64×64. At 256×256, StyleGAN-T halves the zero-shot FID previously achieved by a GAN but continues to trail SOTA diffusion models.

Paper: https://arxiv.org/abs/2301.09515

Project link: https://sites.google.com/view/stylegan-t?pli=1

A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-stylegan-t

#deeplearning #cv #gan #styletransfer Open / Comment

2023-01-21 16:22:48 GPT-3 for self-therapy

Just came across an interesting article about using #GPT-3 to analyze past journal entries and summarize therapy sessions for gaining new perspectives on personal struggles. Dan Shipper loaded person journal into the neural network so he could ask different questions, including asking about his own Myers-Briggs personality type (INTJ for those who wondered).

It's a powerful example of how AI tools can help individuals become more productive, effective, and happy. As we continue to see the integration of #AI in various industries, it's important for modern blue collar workers to learn how to properly work with these tools in order to stay at the peak of efficiency.

Let's embrace the future and learn to use AI to our advantage rather than to spread FUD about AI replacing workforce. It won’t but it will enable some people to achieve more and be way more productive.

Link: https://every.to/chain-of-thought/can-gpt-3-explain-my-past-and-tell-me-my-future

#aiusecase #toolsnotactors Open / Comment

2023-01-13 11:06:27 Open / Comment

2023-01-06 16:02:28 Top Python libraries `22
by @tryolabs

link: https://tryolabs.com/blog/2022/12/26/top-python-libraries-2022

#python #tools Open / Comment

2023-01-04 18:37:54 Open / Comment