From cameras to self-driving cars, many of today’s technologies depend on artificial intelligence to extract meaning from visual information. Today’s AI technology has artificial neural networks at its core, and most of the time we can trust these AI computer …
Computers possess two remarkable capabilities with respect to images: They can both identify them and generate them anew. Historically, these functions have stood separate, akin to the disparate acts of a chef who is good at creating dishes (generation), and …
Artificial Intelligence has undeniably left an indelible mark on our lives. In a pioneering effort to further enhance AI capabilities, researchers from UCLA and the United States Army Research Laboratory have unveiled a unique approach that marries physics-awareness with data-driven …
Artificial intelligence (AI) technologies, particularly Vision Transformers (ViTs), have shown immense promise in their ability to identify and categorize objects in images. However, their practical application has been limited by two significant challenges: the high computational power requirements and the …
A robot manipulating objects while, say, working in a kitchen, will benefit from understanding which items are composed of the same materials. With this knowledge, the robot would know to exert a similar amount of force whether it picks up …
As a car travels along a narrow city street, reflections off the glossy paint or side mirrors of parked vehicles can help the driver glimpse things that would otherwise be hidden from view, like a child playing on the sidewalk …
Imagine sitting on a park bench, watching someone stroll by. While the scene may constantly change as the person walks, the human brain can transform that dynamic visual information into a more stable representation over time. This ability, known as …
Computer vision (CV) has reached 99% accuracy from 50% within 10 years. The technology is expected to improve further to an unprecedented level with modern algorithms and image segmentation techniques. Recently, Meta's FAIR lab has released the Segment Anything Model …
Maybe you can’t tell a book from its cover, but according to researchers at MIT you may now be able to do the equivalent for materials of all sorts, from an airplane part to a medical implant. Their new approach
Property assessments sit at the center of home appraisals, insurance claims, renovation projects, and a number of other important processes. Inaccurate or delayed assessments can set projects back and stick consumers with higher costs.
Now, a platform first developed at …
Enlarge / An example of SAM selecting the outline of a corgi in a photo. (credit: Meta)
On Wednesday, Meta announced an AI model called the Segment Anything Model (SAM) that can identify individual objects in images and videos, even
Deploying models at scale can be a cumbersome task for many data scientists and machine learning engineers. However, Amazon SageMaker endpoints provide a simple solution for deploying and scaling your machine learning (ML) model inferences. Our last blog post and GitHub …
In science and technology, there has been a long and steady drive toward improving the accuracy of measurements of all kinds, along with parallel efforts to enhance the resolution of images. An accompanying goal is to reduce the uncertainty in …
As a graduate student doing his master’s thesis on speech recognition at the MIT AI Lab (now the MIT Computer Science and Artificial Intelligence Laboratory), Dan Huttenlocher worked closely with Professor Victor Zue. Well known for pioneering the development of …
Before a machine-learning model can complete a task, such as identifying cancer in medical images, the model must be trained. Training image classification models typically involves showing the model millions of example images gathered into a massive dataset.
However, using …
Imagine the booming chords from a pipe organ echoing through the cavernous sanctuary of a massive, stone cathedral.
The sound a cathedral-goer will hear is affected by many factors, including the location of the organ, where the listener is standing, …