In this week’s roundup, learn about how artificial intelligence (AI) is being used to predict future cancer and how it is used to generate high-value artwork. Explore how “liquid” networks work and what they can be used for. Consider the areas that AI might advance this year. Finally, understand the need for location in advanced analytics and how it can be used to better business.
“Liquid” Machine-Learning System Adapts To Changing Conditions
By Daniel Ackerman, contributing writer for News.MIT.edu
Researchers have developed a type of neural network–called a “liquid” network– that learns on the job, not just during the training phase. They change their underlying equations to continuously adapt to new data inputs. This could aid decision making based on data streams that change over time, including those involved in medical diagnosis and autonomous driving.
Artificial Intelligence Generated Artwork Sells for $432,500 – Is AI a Simple Tool or Creative Genius?
By Max Planck Institute for Human Development, contributing writer for SciTechDaily.com
A portrait was developed by an artist collective feeding real paintings by human painters into an AI algorithm, training it to create images autonomously. One of those images was selected and it was sold at auction for $432,500. AI tends to be humanized, especially in the media. Yet the payment went to the collective—not the machine or the programmers. This begs the question: who gets credit for the art? Read about a study that aims to answer this question.
Here’s Where AI Will Advance in 2021
by Bob Wiener, Daniel Hannah, Allan Ogwong, and Christopher Thissen; contributing writers for VentureBeat.com
Despite 2020 being jam-packed with compelling and important news updates, AI advances still commanded mainstream attention. Stories highlighted the new and surprising ways that we may start to see AI showing up in daily life. This article dives into what we might expect to see from AI this year, particularly in the realms of Transformers, graphic neural networks, and applications.
Robust Artificial Intelligence Tools To Predict Future Cancer
By Rachel Gordon, contributing writer for News.MIT.edu
In order to catch cancer earlier, we need to predict who is likely to get diagnosed in the future. However, the adoption of AI in medicine has been slow due to poor performance and neglect of racial minorities. Researchers developed a new deep learning system using a patient’s mammogram, which showed significant promise and racial inclusivity. This “Mirai” algorithm was then tailored to the unique requirements of risk modeling and it is showing consistent performance across datasets from the US, Europe, and Asia.
The New Analyst: The Rise Of Location In Advanced Analytics
By Helen Thompson, contributing writer for Forbes.com
A new type of business analyst is becoming in demand due to the need to understand and apply the power of location data. Corporations have discovered that almost every dataset can be explained using geographic insight and relationships. These up-and-coming specialists are able to help analyze and adjust supply chains, determine optimal routes, decide where to expand operations, and more.
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