Stanford researchers have developed a new phase-change memory that could help computers process large amounts of data faster and more efficiently.
4 minutes read
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In this episode, we talk about how a driven undergraduate student from Columbia University mapped fingerprints from different fingers of the same person - which was widely known to be impossible by the experts in the field - using publicly available data and machine learning.
15 minutes read
Seeking a way to make their high-speed production equipment even more reliable and productive, AROL recently decided to develop an innovative solution to enable data monitoring and predictive maintenance, upgrading their offering with an Industry 4.0 approach.
2 minutes read
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
Imagine a task that used to take 11 minutes now taking less time than the blink of an eye. Couple that speed increase with 97% accuracy, and these are the results researchers achieved when combining ML, neural networks and novel compression in a new project advancing reservoir production forecasts.
4 minutes read
Columbia engineers have built a new AI that shatters a long-held belief in forensics–that fingerprints from different fingers of the same person are unique. It turns out they are similar, only we’ve been comparing fingerprints the wrong way!
4 minutes read
MSE researchers are using a Catalyst Award from the National Academy of Medicine to develop a pressure-relieving sensor system that could also be used in hospital beds.
3 minutes read
How BrainChip's Akida technology is revolutionizing time series data analysis.
5 minutes read
Umar Iqbal and collaborators developed a framework to measure data collection, sharing and use by smart speaker platforms
3 minutes read
StructCode, developed by MIT CSAIL researchers, encodes machine-readable data in laser-cut objects by modifying their fabrication features.
Unlocking AI Potential Through Strategic Dataset Curation: A Comprehensive Guide for Enhancing Machine Learning Models
The butterfly effect—the idea that a butterfly flapping its wings in South America could change the course of a tornado in Texas—has been a popular way to illustrate the difficulty of making predictions about the behavior of chaotic systems like the weather. Because such systems are extremely sensitive to their initial conditions, even the tiniest of changes can send their behavior careening off into unexpected directions.
4 minutes read
Using a simple and convenient touchscreen interface, the algorithm learns the assistance preferences of the wearer.
Training robust AI models can be challenging when using crowdsourced or publicly available datasets. The most useful neural networks are ones that replace expert knowledge to solve real problems. One example would be a visual inspection model for the factory floor.
3 minutes read
Sensor and actuator networks are systems that collect and transmit data from a physical environment for digital processing. Data is collected at sensors and actuators in the field, then digitized at the sensor or actuator. The digitized data can be used for a variety of applications, and the method for data processing depends on the application
