Lifeboat Foundation

Sony is bringing machine intelligence to its image sensors. The electronics and entertainment giant announced this week a sensor that applies artificial intelligence while processing imagery without the need for extrema hardware or assistance.

Players in the photography industry have been focusing on increasingly greater numbers of pixels for ever-sharper enlargement and reproduction capabilities and on increasingly compressed devices for lighter weight and greater portability.

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Researchers at Zhejiang University of Technology, Tianjin University, Nanjing Institute of Technology and Ritsumeikan University have recently created a soft robotic finger that integrates a self-powered curvature sensor using multi-material 3D printing technology. The new robotic finger, presented in a paper published in Elsevier’s Nano Energy journal, is made of several materials, including a stretchable electrode, polydimethylsiloxane (PDMS), AgilusBlack, VeroWhite and FLX9060.

“Soft robots have the potential to bridge the gap between machines and humans, but it is important for them to ensure a safe interaction between humans, objects and the environment,” Mengying Xie, co-author of the paper, told TechXplore. “Embedded soft sensors are critical for the development of controllable soft robots that can fulfill their full potential in practical applications.”

In their previous research, part of the research team working at Ritsumeikan University developed a fully multi-material 3D printed gripper with variable stiffness that could achieve robust grasping of objects. In this new study, Xie, Zhu and their colleagues drew inspiration from this previous work and set out to create a 3D-printed soft finger with sensing capabilities that could monitor its bending movements.

UCSC researchers developed a deep-learning framework called Morpheus to perform pixel-level morphological classifications of objects in astronomical images.

Researchers at UC Santa Cruz have developed a powerful new computer program called Morpheus that can analyze astronomical image data pixel by pixel to identify and classify all of the galaxies and stars in large data sets from astronomy surveys.

Morpheus is a deep-learning framework that incorporates a variety of artificial intelligence technologies developed for applications such as image and speech recognition. Brant Robertson, a professor of astronomy and astrophysics who leads the Computational Astrophysics Research Group at UC Santa Cruz, said the rapidly increasing size of astronomy data sets has made it essential to automate some of the tasks traditionally done by astronomers.

CloudWalk has raised RMB 1.8 billion (US$254 million) in funding from a group of provincial and municipal funds in China to become the fourth most well-funded biometric facial recognition company in the country, according to a report in Chinese-language publication 36Kr covered by its English-language affiliate KrAsia.

CloudWalk intends to launch an IPO on Shanghai’s Star Market by the end of 2020, according to the report. The company has raised a total of RMB 2.8 billion ($400 million) so far.

CloudWalk provides facial recognition for numerous public agencies, including the Bank of China, Shanghai Pudong Airport, and China Mobile’s brick and mortar stores.

NVIDIA announced the Jetson Nano Developer Kit at the 2019 NVIDIA GPU Technology Conference (GTC), a $99 computer available now for embedded designers, researchers, and DIY makers, delivering the power of modern AI in a compact, easy-to-use platform with full software programmability. Jetson Nano delivers 472 GFLOPS of compute performance with a quad-core 64-bit ARM CPU and a 128-core integrated NVIDIA GPU. It also includes 4GB LPDDR4 memory in an efficient, low-power package with 5W/10W power modes and 5V DC input, as shown in figure 1.

CrumplePop RustleRemover AI and Levelmatic Audio Plugins, two plugins for audio cleanup we have a look at how they can clean up audio from anything to unwanted mic noises, to fixing levels in podcasts and interview audio.

CrumplePop makes some very clever and useful plugins for Mac-based editors. These include audio tools to fix and enhance sound and video tools for grading and stabilizing. The company has now announced two new audio plugins, RustleRemover AI and Levelmatic the former aimed at fixing a specific issue, and the latter leveling audio.

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Brain injuries can vary greatly in their severity, but assessing the extent of the damage is far from a simple undertaking. Scientists in the UK have developed a new AI algorithm that could help narrow the margin for error, with the ability to detect and categorize different types of brain lesions to gauge the impact of an injury.

One of the tools doctors use to assess brain injuries is a CT scan, which can reveal signs of damage, such as lesions, on the brain. But analyzing these scans to reach a diagnosis is a time-consuming process for radiologists, and given the complex nature of the organ, it can see tell-tale signs often overlooked.

“CT is an incredibly important diagnostic tool, but it’s rarely used quantitatively,” said Professor David Menon, from the University of Cambridge and senior author of the new study. “Often, much of the rich information available in a CT scan is missed, and as researchers, we know that the type, volume and location of a lesion on the brain are important to patient outcomes.”

“A wealth of information creates a poverty of attention,” said Andy McMurray, co-founder and CIO of Medal, an AI-based software company developing tools for health care, during an interview with Healthcare IT News.

This is especially true in the operating room, where surgery teams at the University of Iowa Hospital have reduced surgical site infection by 74% using DASH Analytics’ high-definition care platform (HDCP). This system observes data from the operation in real time and compares it to a patient’s history and its own infection models. Toward the end of the procedure, it automatically provides the surgeon with recommendations to reduce infection during wound closure. Furthermore, it notes whether the surgeon follows its suggestions or not and compares that to the outcome of the patient. This information is then used to both improve its infection model and improve the surgeon’s own performance in future surgeries.

Advances in AI build off of each other. One breakthrough opens the doors for more possibilities in the future, which in turn leads to even more breakthroughs at an exponential rate. Just as the Industrial Revolution automated back-breaking physical labor, the AI Revolution is poised to automate mind-numbing mental labor. Based on what we’ve seen in the last 10 years alone, we can expect to see this boom very soon.