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Category: robotics/AI – Page 2248

Apple’s first paper on artificial intelligence, published Dec. 22 on arXiv (open access), describes a method for improving the ability of a deep neural network to recognize images.

To train neural networks to recognize images, AI researchers have typically labeled (identified or described) each image in a dataset. For example, last year, Georgia Institute of Technology researchers developed a deep-learning method to recognize images taken at regular intervals on a person’s wearable smartphone camera.

Example images from dataset of 40,000 egocentric images with their respective labels (credit: Daniel Castro et al./Georgia Institute of Technology)

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(NaturalNews) A diagnosis of amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig’s disease, was once considered a death sentence, but advanced automation technology is offering new hope to sufferers of the rare condition.

Most ALS patients eventually face an extremely difficult choice: either die from the lack of ability to breathe once the disease progresses or undergo a tracheostomy and spend the rest of one’s life on a ventilator – unable to move or speak.

Less than 10 percent of ALS patients choose the second option, but one man who suffers from the disease is helping to develop a viable third option: an opportunity to lead a relatively independent and mobile existence with the help of automation technology that can respond to head and eye movements, or even brain waves.

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The age of widespread autonomous flight came another step closer as DARPA announced its Aircrew Labor In-Cockpit Automation System (ALIAS) has completed Phase 2 of its development program. The drop-in, removable kit designed to convert conventional aircraft into advanced automated vehicles requiring fewer crew was installed in two different Cessna 208 Caravan fixed-wing aircraft, a Diamond DA-42 fixed-wing aircraft, and a Sikorsky S-76 helicopter.

According to DARPA, the ALIAS-equipped aircraft successfully completed flight demonstrations as well as responding to simulated flight emergencies while on the ground that included systems failures that could cause pilots to deviate from normal procedures. In both cases, the agency says that ALIAS worked without adversely affecting airworthiness.

ALIAS is intended as a way of automating various military aircraft without making bespoke modifications to each individual plane design. The idea is to develop a kit that can be installed in the cabin of an aircraft, where it can take control and fly missions from takeoff to landing as well as handling emergencies based on existing vehicle information, procedures, and flight mechanics.

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Well before the family came in to the Batson Children’s Specialty Clinic in Jackson, Mississippi, they knew something was wrong. Their child was born with multiple birth defects, and didn’t look like any of its kin. A couple of tests for genetic syndromes came back negative, but Omar Abdul-Rahman, Chief of Medical Genetics at the University of Mississippi, had a strong hunch that the child had Mowat-Wilson syndrome, a rare disease associated with challenging life-long symptoms like speech impediments and seizures.

So he pulled out one of his most prized physicians’ tools: his cell phone.

Using an app called Face2Gene, Abdul-Rahman snapped a quick photo of the child’s face. Within a matter of seconds, the app generated a list of potential diagnoses — and corroborated his hunch. “Sure enough, Mowat-Wilson syndrome came up on the list,” Abdul-Rahman recalls.

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When you engage in international travel, you may one day find yourself face-to-face with border security that is polite, bilingual and responsive—and robotic.

The Automated Virtual Agent for Truth Assessments in Real Time (AVATAR) is currently being tested in conjunction with the Canadian Border Services Agency (CBSA) to help border security agents determine whether travelers coming into Canada may have undisclosed motives for entering the country.

“AVATAR is a , much like an airport check-in or grocery store self-checkout kiosk,” said San Diego State University management information systems professor Aaron Elkins. “However, this kiosk has a face on the screen that asks questions of travelers and can detect changes in physiology and behavior during the interview. The system can detect changes in the eyes, voice, gestures and posture to determine potential risk. It can even tell when you’re curling your toes.”

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