Goto

Collaborating Authors

real time system


How AI Is Improving Healthcare -- AI Daily - Artificial Intelligence News

#artificialintelligence

Artificial intelligence can certainly transform the healthcare industry, and a recent analysis by accenture suggests that key applications of artificial intelligence in healthcare could generate annual savings of $150 billion for the US healthcare industry by 2026. Consider how artificial intelligence is transforming healthcare and improving patient outcomes by gaining a better understanding of it. From automating workflows to improving processing speed and image quality, medical imaging developers are discovering numerous ways to use artificial intelligence in healthcare to detect and diagnose diseases. As far as diagnostics are concerned, promising diagnostic results have been created for artificial intelligence, as it can be combined with advanced imaging technology to improve diagnostic results. In addition, AI tools can use similar information to develop unique treatment approaches and make recommendations to doctors.


Spatial Computing & IoT Can Unleash Data's Full Potential

#artificialintelligence

The enterprise has been talking about Digital Transformation and Industry 4.0 for years. We have seen transformation accelerate and the adoption of artificial intelligence, connected devices, and even virtual reality speed-up over the last few months due to the pandemic. As enterprise digitization continues to be top of mind and data becomes even more critical in this process, we need to look at how all the data created can be better visualized to generate better business outcomes. The Internet of Things (IoT) allows devices to talk to each other through connected sensors - producing real-time data. Companies had to learn how to process large amounts of data from IoT devices.


Cisco challenge winners use AI, IoT to tackle global problems

#artificialintelligence

An IoT-enabled system for transporting dairy products earned its designers the top prize in a competition run by Cisco. The Global Problem Solver Challenge, which is one of Cisco's corporate social responsibility (CSR) initiatives, pays cash awards to entrepreneurial companies using technology to solve the world's biggest challenges. The program also gives out four $25,000 awards and seven $10,000 prizes. This year, I was honored to be invited to help judge the 2020 winners. In full disclosure, I agreed to be a judge but I received no compensation, as I believe we all have to work together to make the world a better place.


Combining Spatial Computing & IoT Can Unleash Data's Full Potential

#artificialintelligence

The enterprise has been talking about Digital Transformation and Industry 4.0 for years. We have seen transformation accelerate and the adoption of artificial intelligence, connected devices, and even virtual reality speed-up over the last few months due to the pandemic. As enterprise digitization continues to be top of mind and data becomes even more critical in this process, we need to look at how all the data created can be better visualized to generate better business outcomes. The Internet of Things (IoT) allows devices to talk to each other through connected sensors - producing real-time data. Companies had to learn how to process large amounts of data from IoT devices.


AI Generator Learns to 'Draw' Like Cartoonist Lee Mal-Nyeon in Just 10 Hours

#artificialintelligence

A Seoul National University Master's student and developer has trained a face generating model to transfer normal face photographs into cartoon images in the distinctive style of Lee Mal-nyeon. The student (GitHub user name: bryandlee) used webcomics images by South Korean cartoonist Lee Mal-nyeon (이말년) as input data, building a dataset of malnyun cartoon faces then testing popular deep generative models on it. By combining a pretrained face generating model with special training techniques, they were able to train a generator at 256 256 resolution in just 10 hours on a single RTX 2080ti GPU, using only 500 manually annotated images. Since the cascade classifier for human faces provided in OpenCV-- a library of programming functions mainly aimed at real-time computer vision -- did not work well on the cartoon domain, the student manually annotated 500 input cartoon face images. The student incorporated FreezeD, a simple yet effective baseline for transfer learning of GANs proposed earlier this year by KAIST (Korea Advanced Institute of Science and Technology) and POSTECH ( Pohang University of Science and Technology) researchers to reduce the burden of heavy data and computational resources when training GANs. The developer tested the idea of freezing the early layers of the generator in transfer learning settings on the proposed FreezeG (freezing generator) and found that "it worked pretty well."


It's Personal: AI Leader Partners With IBM, Builds New Buy Zone

#artificialintelligence

As IBM (IBM) and Red Hat team up with Adobe (ADBE) on artificial intelligence and personalization technology, Adobe stock is trying to customize a new base and buy point. The IBD Long-Term Leader is also setting its sights on a fresh all-time high. In July, Adobe, IBM and Red Hat announced a strategic partnership aimed at accelerating the digital transformation and strengthening of real-time data security for enterprises, with a focus on regulated industries such as banking and health care. Building on IBM's acquisition of Red Hat in 2018, the goal of the partnership is to "enable companies to deliver more personalized experiences across the customer journey, driving improved engagement, profitability and loyalty." Having already made its own successful shift to a software-as-a-service model, Adobe has become a major player in cloud-based creative, personalization and analytics products.


Top 3 Considerations For Enterprise IoT Security

#artificialintelligence

Enterprise IoT, those connected devices you increasingly find on your organization's network like printers, VoIP phones, smart boards and TVs inside your network, is growing at a massive rate and is expected to reach USD 58 billion by 2023. These devices represent an uncontrolled risk that the majority of organizations don't have visibility into. The next generation of IoT is becoming more than a group of devices, and has morphed into mission critical enterprise-wide services that leverage edge-computing and modern hybrid architectures. This new paradigm requires high levels of uptime and most importantly improved security measures. Further exacerbating the risk, IoT and Security teams seldom, if ever, collaborate on IoT strategy and deployment.


Perimeter Medical Imaging Announces Expansion of ATLAS AI Project with Installation of OTISTM for AI development at Leading Cancer Care Center, MD Anderson

#artificialintelligence

DALLAS, TX / ACCESSWIRE / July 27, 2020 / Perimeter Medical Imaging, AI Inc. (TSXV:PINK) today announced the installation of their OTISTM device at the University of Texas MD Anderson Cancer Center (MD Anderson), to further develop ImgAssist AI technology marking an important milestone in this collaboration and Perimeter's ATLAS AI Project. Initiated in mid-July, the ATLAS AI Project allows Perimeter to collaborate with industry-leading cancer care centers that will use OTIS - its proprietary ultra-high resolution imaging platform - to collect images of breast tumors from approximately 400 patients for the purpose of training and testing Perimeter's ImgAssist AI technology. This technology, which is currently under development, is designed to utilize a machine learning model to help surgeons identify, in real-time, if cancer is still present when performing breast-conserving surgery (lumpectomy). This study was made possible, in part, by a $7.4 million grant awarded by the Cancer Prevention and Research Institute of Texas (CPRIT), a leading state body funding cancer research. Jeremy Sobotta, President and CFO stated, "Initiation at MD Anderson is an important milestone in part one of our ATLAS AI Project and marks the next step in our development and clinical validation efforts for our ImgAssist AI software. MD Anderson is one of the largest breast cancer centers in the United States, treating approximately 40,000 patients a year, and is a valued collaborator as we strive to help physicians improve surgical outcomes for breast cancer patients by providing an additional tool for real-time margin visualization and assessment."


Global Big Data Conference

#artificialintelligence

MCG Health, part of the Hearst Health network, announces it has successfully piloted its new machine learning solution, Indicia for Effective Focus, and it is now available for licensing. MCG is partnering with five major hospital systems for continued development and enhancement of this solution: Avera McKennan Hospital, Baptist Health System, Erlanger Health System, Franciscan Alliance, and IU Health. Indicia for Effective Focus prioritizes utilization management worklists based on the probability of appropriate patient placement, as well as the potential negative financial impact due to untimely decision making. The platform leverages MCG's extensive clinical evidence base, real-time data from the EHR (electronic health record), and machine learning technology to guide the case prioritization. Crissa Mulkey, Director of Utilization Management at IU Health said, "Indicia for Effective Focus shows an intuitive understanding of UM users, as well as how UM, or utilization review, is performed. It is a refreshing change."


ComplyAdvantage nabs $50M for an AI platform and database to detect and stop financial crime – TechCrunch

#artificialintelligence

The growth of digital banking has opened up a wealth of opportunities for making the world of finance more accessible and transparent to a greater number of people. But the darker underbelly is that it has also created more avenues for illicit activity to flourish, with some $2 trillion laundered annually but only 1-3% of that sum "caught". To help combat that, a London-based startup called ComplyAdvantage, which has built an AI platform and wider database of some 10 million entities to help identify and track those involved in financial crime, is today announcing a growth round of funding of $50 million expand its reach and operations. Specifically, the plan will be to use the funding for hiring, to invest in the tools it uses to detect entities and map the relationships between them, and to bring on more clients. "We've been focused on more granular analysis and being able to scale to hundreds of millions of searches across our database," said Charles Delingpole, founder and CEO, said in an interview.