![]() ![]() The new model OpenAI model is called text-embedding-ada-002. This is a numeric representation of the text thatĪllows words with similar meanings to have a similar representation. The embedding model converts a text concept into a numeric vector which then can be used for various ML tasks. Links: original blog post, original paper, models and code here OpenAI presents an improved embedding model priced 99.8% lower than the Davinci model RoBERTa model in 2x less time on GLUE natural language understanding Wav2vec 2.0 in 10.6x less time on Librispeech speech recognition Masked Autoencoders in 16.4x less time on computer vision Links: original blog post, original paper, the project’s website Meta AI published a paper detailing the data2vec 2.0 algorithm with an increased training efficiency (a new version of data2vec) From the original paperĭata2vec 2.0 performs as well as these models with significant improvements in pre-training time: ![]() Robotics Transformer 1 (RT-1) is a multi-task model that tokenizes robot inputs and outputs actions (e.g., camera images, task instructions, and motor commands) to enable efficient inference at runtime, which makes real-time control feasible. New research from Google AI addresses the lack of efficient, scalable, and fast-enough-for-real-time-inference models in robotics. ML Research Google AI presented RT-1: Robotics Transformer model □ Let’s dive into the news! Make sure you read the article to find all links. IBM released the first episode of its free series explaining how quantum computing works Machine Learning University curated by Amazon Science presented their free, online Responsible AI course ![]() Hugging Face created the “Ethics and Society Newsletter” and already published its #2 edition Meta AI open-sourced its Anonymous Credential Service (ACS) for user authentification in a de-identified manner Google AI thought Recorder to detect different speakers in real time Researchers from Carnegie Mellon University presented a framework for requirements engineering in machine learningĪmazon Science detailed the methods behind continual learning in Alexa OpenAI presents an improved embedding model priced 99.8% lower than the Davinci model Meta AI published a paper detailing the data2vec 2.0 algorithm with an increased training efficiency (a new version of data2vec) Google AI presented RT-1: Robotics Transformer model □ We cover main points of each of them in the article below. This week is full of fascinating announcements: research papers, technologies behind popular services, and open-source announcements! From Transformers in Robotics (Google AI) to multimodal SSL (Meta AI) to requirements engineering in ML (CMU) to free courses. ![]()
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |