The MIT researchers said their generative model requires less memory to store than datasets, which can cost millions of dollars to create. MIT researchers have found a way to classify images using synthetic data, which they claim can rival models trained from real data. In the study, the team created a special type of machine learning model to generate extremely realistic synthetic data, which can then train another model for vision-related tasks. The researchers said that currently, massive amounts of data is required to train a machine to perform image classification tasks, such as identifying damage in satellite photos following a natural disaster. However, the datasets required to train the model can cost millions of dollars to generate.

From the Beatles Let It Be to John Coltrane's A Love Supreme and Radiohead's OK Computer, record labels often remaster classic albums from the greats in many genres of music. These higher fidelity remasters are a welcome treat for aficionados and mainstream fans alike. But what if I told you, just like Led Zeppelin's or Van Halen's greatest hits, semiconductor chips could be "remastered" as well, and these remasters could help bail us out of the current chip shortage? For some folks that would totally rock, pun intended, but let's take a step back and look at the problem and potential solutions at hand first. The process of designing and verifying chips like the modern processors, controllers and sensors in cars, for example, can take years and require millions of dollars of R&D.

The growing popularity of artificial intelligence technology probably will lead to millions of lost jobs, especially among less-educated workers, and could exacerbate the economic divide between socioeconomic classes in the United States, according to a newly released White House report. But that same technology is also essential to improving the country's productivity growth, a key measure of how efficiently the economy produces goods. That could ultimately lead to higher average wages and fewer work hours. For that reason, the report concludes, our economy actually needs more artificial intelligence, not less. To reconcile the benefits of the technology with its expected toll, the report states, the federal government should expand both access to education in technical fields and the scope of unemployment benefits.

The growing popularity of artificial intelligence technology will likely lead to millions of lost jobs, especially among less-educated workers, and could exacerbate the economic divide between socioeconomic classes in the United States, according to a newly released White House report. But that same technology is also essential to improving the country's productivity growth, a key measure of how efficiently the economy produces goods. That could ultimately lead to higher average wages and fewer work hours. For that reason, the report concludes, our economy actually needs more artificial intelligence, not less. To reconcile the benefits of the technology with its expected toll, the report states that the federal government should expand access to education in technical fields and increase the scope of unemployment benefits.