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The Trouble With Trusting AI to Interpret Police Body-Cam Video

Axon is promising its AI will be able to describe events recorded in body-cam video, but we’re skeptical

12 min read
Photo-illustration: Stuart Bradford
Photo-illustration: Stuart Bradford

On 17 July 2014, a group of New York City police officers approached 43-year-old Eric Garner on a Staten Island sidewalk and attempted to arrest him—for allegedly selling cigarettes illegally. When Garner pulled free, one officer wrapped an arm around Garner’s neck, forced him to the ground, and pressed his face into the sidewalk. Garner, who had asthma and heart disease, repeatedly pleaded, “I can’t breathe,” before passing out. Unconscious, he was transported to a hospital, where he was pronounced dead an hour later. The medical examiner later ruled Garner’s death a homicide.

This tragedy drew national attention thanks to a cellphone video, which revealed in shocking detail the grossly excessive use of force that Garner was subjected to at the hands of police. Garner’s killing, and those of other unarmed black citizens by police, sparked protests throughout the United States.

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Deep Learning Gets a Boost From New Reconfigurable Processor

The ReAAP processor allows AI to be faster, more efficient

2 min read
different colored beams of light shooting up
iStock

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Deep learning is a critical computing approach that is pushing the boundaries of technology – crunching immense amounts of data and uncovering subtle patterns that humans could never discern on their own. But for optimal performance, deep learning algorithms need to be supported with the right software compiler and hardware combinations. In particular, reconfigurable processors, which allow for flexible use of hardware resources for computing as needed, are key.

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Rory Cooper’s Wheelchair Tech Makes the World More Accessible

He has introduced customized controls and builds wheelchairs for rough terrain

6 min read
portrait of a man in a navy blue polo with greenery in the background
Abigail Albright

For more than 25 years, Rory Cooper has been developing technology to improve the lives of people with disabilities.

Cooper began his work after a spinal cord injury in 1980 left him paralyzed from the waist down. First he modified the back brace he was required to wear. He then turned to building a better wheelchair and came up with an electric-powered version that helped its user stand up. He eventually discovered biomedical engineering and was inspired to focus his career on developing assistive technology. His inventions have helped countless wheelchair users get around with more ease and comfort.

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Learn How Global Configuration Management and IBM CLM Work Together

In this presentation we will build the case for component-based requirements management

2 min read

This is a sponsored article brought to you by 321 Gang.

To fully support Requirements Management (RM) best practices, a tool needs to support traceability, versioning, reuse, and Product Line Engineering (PLE). This is especially true when designing large complex systems or systems that follow standards and regulations. Most modern requirement tools do a decent job of capturing requirements and related metadata. Some tools also support rudimentary mechanisms for baselining and traceability capabilities (“linking” requirements). The earlier versions of IBM DOORS Next supported a rich configurable traceability and even a rudimentary form of reuse. DOORS Next became a complete solution for managing requirements a few years ago when IBM invented and implemented Global Configuration Management (GCM) as part of its Engineering Lifecycle Management (ELM, formerly known as Collaborative Lifecycle Management or simply CLM) suite of integrated tools. On the surface, it seems that GCM just provides versioning capability, but it is so much more than that. GCM arms product/system development organizations with support for advanced requirement reuse, traceability that supports versioning, release management and variant management. It is also possible to manage collections of related Application Lifecycle Management (ALM) and Systems Engineering artifacts in a single configuration.

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