AI Technology & Industry Review
An OpenAI research team fine-tunes the GPT-3 pretrained language model to enable it to answer long-form questions by searching and navigating a text-based web browsing environment, achieving retrieval and synthesis improvements and reaching human-level long-form question-answering performance.
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 OpenAI proposes Codex, a specialized GPT model fine-tuned on publicly available code from GitHub that can produce functionally correct Python code bodies from natural language docstrings and could excel at a variety of coding tasks.
The Beijing Academy of Artificial Intelligence (BAAI) releases Wu Dao 1.0, China’s first large-scale pretraining model.
A research team from UC Berkeley, University of Maryland and UC Irvine identifies pitfalls that cause instability in the GPT-3 language model and proposes a contextual calibration procedure that improves accuracy by up to 30 percent.
OpenAI has trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language.
Microsoft announced today that it has teamed up with OpenAI to exclusively license the AI research institute’s GPT-3 language model.
Although OpenAI hasn’t yet officially announced the GPT-3 pricing scheme, Branwen’s sneak peek has piqued the interest of the NLP community.
OpenAI’s 175 billion parameter language model GPT-3 has gone viral once again.
OpenAI announced the upgraded GPT-3 with a whopping 175 billion parameters.