AI Technology & Industry Review
On October 11, Microsoft introduced the largest and “the most powerful monolithic transformer language model” trained to date, a 530 billion parameter GPT-3-style generative language model.
A research team from DeepMind and University College London have released Alchemy, a novel open-source benchmark for meta-RL research.
A recent study by the Google Brain Team proposes a new way of programming automated machine learning (AutoML) based on symbolic programming.
A new AI Expert Roadmap developed by German software company AMAI is garnering keen interest from aspiring AI professionals around the world.
Google Research released a paper tackling this issue with a new open-source analytic platform: the Language Interpretability Tool (LIT).
The NeurIPS 2020 paper reviews were sent out last Friday, starting the author response phase.
Researchers dive deep into the large language model to discover how it encodes the structured commonsense knowledge it leverages on downstream commonsense tasks.
ArXiv announced that all of its research papers are now available on Kaggle.
A Seoul National University Master’s student and developer has trained a face generating model to transfer normal face photographs into cartoon images in the distinctive style of Lee Mal-nyeon.
OpenAI’s 175 billion parameter language model GPT-3 has gone viral once again.
BigBird is shown to dramatically improve performance across long-context NLP tasks, producing SOTA results in question answering and summarization.