MIT and Google researchers discover how GPT-3 can learn new tasks with minimal data
Similar research is being conducted by a team from the same Massachusetts Institute of Technology and the joint MIT and IBM Watson Artificial Intelligence Laboratory. They have developed a technique that allows the model to quantify uncertainty more efficiently with less computing power than is used in other techniques. It also does not require additional data. This technique does not involve additional retraining or model modification, and can be used in most applications. It includes a simple complementary model that helps the basic ML model calculate uncertainty.
In today's era of digitalisation, businesses in all sectors are facing new challenges. Competition is intensifying, customers are becoming more demanding and technology is evolving at breakneck speed. To remain competitive, businesses need to change. And one of the key steps along the way may be migrating to the cloud.
The right choice of a business partner is one of the main tasks of any business. The quality of goods or services that the company receives, as well as its reputation, depend on the reliability of the supplier. To make the process transparent and convenient, scoring models for assessing reliability come to the rescue.
Summer is coming to an end, but life in the analytics field is bustling. New vendor announcements, promising projects, and the pervasive penetration of AI into all areas of our lives are paving the way for the upcoming business season.
Maksim Karankevich, Director of Data and Digital Transformation, Ultramar, in his presentation shared his experience of implementing a cellular-based industrial radio network.