​​AutoFlip: An Open Source Framework for Intelligent Video Reframing

Google released a tool for smart video cropping. Video cropping doesn't seem like a poblem until you release that object that should be in focus can be in different parts of picture. Now there is great attempt to provide one-click solution to cropping.

Interesting part: #AutoFlip is an application of #MediaPipe framework for building multimodal ML #pipelines.

Github: https://github.com/google/mediapipe/blob/master/mediapipe/docs/autoflip.md
MediaPipe: https://github.com/google/mediapipe/

#Google #GoogleAI #DL #CV

​​Racial Disparities in Automated Speech Recognition

To no surprise, speech recognition tools have #bias due to the lack of diversity in the datasets. Group of explorers addressed that issue and provided their’s research results as a paper and #reproducible research repo.

Project link: https://fairspeech.stanford.edu
Paper: https://www.pnas.org/cgi/doi/10.1073/pnas.1915768117
Github: https://github.com/stanford-policylab/asr-disparities

#speechrecognition #voice #audiolearning #dl #microsoft #google #apple #ibm #amazon

Lo-Fi Player

The team from the magenta project, that does research about deep learning and music powered by TensorFlow in Google, obviously, release a new fun project lofi-player powered by their open-source library magenta.js.

So it's basically a lo-fi music generator which popular genre on youtube streams and other kinds of stuff. You can customize the vibe on your manner and wish from sad to moody, slow to fast, etc.

It is based on their earlier work MusicVae to sample latent space of music and MelodyRNN to generate music sequences from different instruments. The project is not about new research, but to show what can do with an already done library in a creative way.

They also create a stream on youtube to listen lo-fi generated by that application and users in chat can together tune lo-fi player in stream :)

#magenta #lo-fi #music #google #tensorflow #fun

​​Waymo started driverless tests in Phoenix

This #Google company plans to expand tests to cover whole state later.

Blog: https://blog.waymo.com/2020/10/waymo-is-opening-its-fully-driverless.html
Redditers’ experience: https://www.reddit.com/r/waymo/comments/j7rphd/4_minute_full_video_in_waymo_one_no_driver_short/

#autonomousrobots #selfdriving #rl #DL

Introducing Model Search: An Open Source Platform for Finding Optimal ML Models

#Google has released an open source #AutoML framework capable of hyperparameter tuning and ensembling.

Blog post: https://ai.googleblog.com/2021/02/introducing-model-search-open-source.html
Repo: https://github.com/google/model_search

🦜 Hi!

We are the first Telegram Data Science channel.

Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.


Ultimate Posts

* Where to start learning more about Data Science. https://github.com/open-data-science/ultimate_posts/tree/master/where_to_start
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ODS.ai is an international community of people anyhow related to Data Science.

Website: https://ods.ai



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Through the years we accumulated a big collection of materials, most of them accompanied by hashtags.

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#cv — posts related to Computer Vision. Pictures and videos
#nlp #nlu — Natural Language Processing and Natural Language Understanding. Texts and sequences
#audiolearning #speechrecognition — related to audio information processing
#ar — augmeneted reality related content
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Imagen — new neural network for picture generation from Google

TLDR: Competitor of DALLE was released.

Imagen — text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation. #Google key discovery is that generic large language models (e.g. T5), pretrained on text-only corpora, are surprisingly effective at encoding text for image synthesis: increasing the size of the language model in Imagen boosts both sample fidelity and image-text alignment much more than increasing the size of the image diffusion model.

Website: https://imagen.research.google

#GAN #CV #DL #Dalle

⚡️ Gemma 3 QAT

Google DeepMind выпустили обновленные версии своих языковых моделей Gemma 3, которые стали значительно эффективнее по использованию памяти без существенной потери производительности.

Ключевая технология: QAT (Quantization-Aware Training)

Что это? QAT — это техника обучения, при которой модель во время дообучения "учится" работать с пониженной точностью вычислений (используя меньше бит для представления чисел). Это имитирует условия, в которых модель будет работать после квантизации (сжатия).

Обычная квантизация после обучения может привести к падению точности. QAT позволяет модели заранее адаптироваться к работе в низкоточном режиме, минимизируя потерю качества после финальной квантизации.

Каждая модель (1B, 4B, 12B, 27B) была дообучена примерно на 5000 шагов с имитацией низкой разрядности весов​. При этом использовался приём, похожий на знание-дистилляцию: оригинальная неквантованная модель выступала в роли «учителя».

Преимущество QAT-подхода для Gemma 3 оказалось колоссальным. Официально заявлено, что квантованные модели Gemma 3 QAT сохраняют качество, практически не упало, при этом требуют в ~3 раза меньше памяти​.

Например, объём памяти для хранения весов самой крупной модели на 27B параметров сократился с ~54 ГБ (в формате bfloat16) до ~14 ГБ в 4-битном целочисленном формате​ – это экономия памяти примерно в ~3–4 раза.

ollama run hf(.)co/google/gemma-3-4b-it-qat-q4_0-gguf

✔️HF


@ai_machinelearning_big_data


#google #gemma #AI #ML #LLM #Quantization