Google Research AI blog

FEBRUARY 10, 2023

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Hence, developing algorithms with improved efficiency, performance and speed remains a high priority as it empowers services ranging from Search and Ads to Maps and YouTube. You can find other posts in the series here.)

Algorithm 110

Algorithm Neural Network Auto-classification ML 110

AWS Machine Learning Blog

MARCH 2, 2023

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. The code can be found on the GitHub repo. eks-create.sh

BERT 98

BERT Deep Learning Metadata Auto-complete 98

Snorkel AI

JANUARY 12, 2023

Language complexity: Some languages, such as Chinese and Arabic, have complex characters and scripts that can make them more difficult to process using NLP algorithms. For text classification, however, there are many similarities. Snorkel Flow’s “Auto-Suggest Key Terms” feature works on any language with “white-space” tokenization.

BERT 52

BERT NLP Natural Language Processing Auto-classification 52

DataRobot Blog

FEBRUARY 2, 2023

These models are trained on massive amounts of text data using deep learning algorithms. Then you can use the model to perform tasks such as text generation, classification, and translation. If you already run your experiments on the DataRobot GUI, you could even add it as a custom task. pip install transformers==4.25.1 datarobot==3.0.2

BERT 52

BERT Large Language Models Natural Language Processing Machine Learning 52

Google Research AI blog

FEBRUARY 28, 2023

Throughout 2022, we gave over 224 grants to researchers and over $10M in Google Cloud Platform credits for topics ranging from the improvement of algorithms for post-quantum cryptography with collaborators at CNRS in France to fostering cybersecurity research at TU Munich and Fraunhofer AISEC in Germany.

Robotics 72

Robotics Deep Learning Auto-classification ML 72

AWS Machine Learning Blog

JANUARY 9, 2023

The base models can be diverse and trained by different algorithms. For example, an image classification use case may use three different models to perform the task. The scatter-gather pattern allows you to combine results from inferences run on three different models and pick the most probable classification model.

ML 98

ML Auto-complete Auto-classification Deep Learning 98

AWS Machine Learning Blog

NOVEMBER 1, 2023

The system is further refined with DistilBERT , optimizing our dialogue-guided multi-class classification process. Additionally, you benefit from advanced features like auto scaling of inference endpoints, enhanced security, and built-in model monitoring. To mitigate the effects of the mistakes, the diversity of demonstrations matter.

Auto-classification 121

Auto-classification LLM Auto-complete Generative AI 121