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Researchers Teaching Artificial Intelligence to Connect Senses Like Vision and Touch

The new AI-based system can create realistic tactile signals from visual inputs

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In this method, instructions are given to the companies staff members to perform transactions such as money transfers, as well as malicious activity on the company's network. Pixabay

A team of researchers at the Massachusetts Institute of Technology (MIT) have come up with a predictive Artificial Intelligence (AI) that can learn to see by touching and to feel by seeing.

While our sense of touch gives us capabilities to feel the physical world, our eyes help us understand the full picture of these tactile signals.

Robots, however, that have been programmed to see or feel can’t use these signals quite as interchangeably.

The new AI-based system can create realistic tactile signals from visual inputs, and predict which object and what part is being touched directly from those tactile inputs.

Teaching, Artificial Intelligence, Researchers
) A team of researchers at the Massachusetts Institute of Technology (MIT) have come up with a predictive Artificial Intelligence (AI). Pixabay

In the future, this could help with a more harmonious relationship between vision and robotics, especially for object recognition, grasping, better scene understanding and helping with seamless human-robot integration in an assistive or manufacturing setting.

“By looking at the scene, our model can imagine the feeling of touching a flat surface or a sharp edge”, said Yunzhu Li, PhD student and lead author from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

“By blindly touching around, our model can predict the interaction with the environment purely from tactile feelings,” Li added.

The team used a KUKA robot arm with a special tactile sensor called GelSight, designed by another group at MIT.

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Using a simple web camera, the team recorded nearly 200 objects, such as tools, household products, fabrics, and more, being touched more than 12,000 times.

Breaking those 12,000 video clips down into static frames, the team compiled “VisGel,” a dataset of more than three million visual/tactile-paired images.

“Bringing these two senses (vision and touch) together could empower the robot and reduce the data we might need for tasks involving manipulating and grasping objects,” said Li.

The current dataset only has examples of interactions in a controlled environment.

Teaching, Artificial Intelligence, Researchers
While our sense of touch gives us capabilities to feel the physical world, our eyes help us understand the full picture of these tactile signals. Pixabay

The team hopes to improve this by collecting data in more unstructured areas, or by using a new MIT-designed tactile glove, to better increase the size and diversity of the dataset.

“This is the first method that can convincingly translate between visual and touch signals”, said Andrew Owens, a post-doc at the University of California at Berkeley.

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The team is set to present the findings next week at the “Conference on Computer Vision and Pattern Recognition” in Long Beach, California. (IANS)

Next Story

Now AI Can Predict Cardiovascular Diseases

The AI technique was therefore shown for the first time to be able to predict which patients might die or suffer major adverse events

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Heart Disease
The AI technique was shown for the first time to be able to predict which patients might die or suffer major adverse Heart Diseases, better than a doctor could on their own with traditional approaches. Pixabay

Researchers have used Artificial Intelligence (AI) for the first time to instantly and accurately measure blood flow and Heart Diseases.

The results were found to be able to predict chances of death, heart attack and stroke, and can be used by doctors to help recommend treatments which could improve a patient’s blood flow, according to the study, published in the journal Circulation.

“We have tried to measure blood flow manually before, but it is tedious and time-consuming, taking doctors away from where they are needed most, with their patients,” said study researcher James Moon from University College London in the UK.

Heart disease is the leading global cause of death and illness. Reduced blood flow, which is often treatable, is a common symptom of many heart conditions. International guidelines therefore recommend a number of assessments to measure a patient’s blood flow, but many are invasive and carry a risk.

Non-invasive blood flow assessments are available, including Cardiovascular Magnetic Resonance (CMR) imaging, but up until now, the scan images have been incredibly difficult to analyse in a manner precise enough to deliver a prognosis or recommend treatment.

In the largest study of its kind, researchers took routine CMR scans from more than 1,000 patients and used a new automated artificial intelligence technique to analyse the images. By doing this, the teams were able to precisely and instantaneously quantify the blood flow to the heart muscle and deliver the measurements to the medical teams treating the patients.

By comparing the AI-generated blood flow results with the health outcomes of each patient, the team found that the patients with reduced blood flow were more likely to have adverse health outcomes including death, heart attack, stroke and heart failure.

Heart Disease
Researchers have used Artificial Intelligence (AI) for the first time to instantly and accurately measure blood flow and Heart Diseases. Pixabay

The AI technique was therefore shown for the first time to be able to predict which patients might die or suffer major adverse events, better than a doctor could on their own with traditional approaches. “The predictive power and reliability of the AI was impressive and easy to implement within a patient’s routine care,” said study researcher Kristopher Knott.

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“This study demonstrates the growing potential of artificial intelligence-assisted imaging technology to improve the detection of heart disease and may move clinicians closer to a precision medicine approach to optimize patient care,” said Peter Kellman, who developed the automated AI techniques to analyse the images that were used in the study. (IANS)