Founded by Massachusetts General Hospital and later joined by Brigham & Women's Hospital, CCDS today announced it has received what it calls a purpose-built AI supercomputer from the portfolio of Nvidia DGX systems with Volta, said by Nvidia to be the biggest GPU on the market. Later this month, CCDS will also receive a DGX Station, which Nvidia calls "a personal AI supercomputer," that the organization will use to develop new training algorithms "and bring the power of AI directly to doctors" in the form of a desk-side system. With 640 Tensor Cores (8 per SM), the Tesla V100 delivers 120 teraflops of deep learning performance, providing 6-12 times higher peak teraflops for Tensor operations compared with previous-generation silicon, according to Nvidia. Nvidia said the new DGX-1 with Volta delivers AI computing performance three times faster than the prior DGX generation, providing the performance of up to 800 CPUs in a single system.
Leading safety metrics provide: Total number of noncompliances Number of near-misses enabling investigation to prevent potential incidents The time it takes to complete post-audit corrective and preventive actions Easy-to-view previous findings for corrective action launches and findings Automated audit management software that centralizes all risk items and allows users to automatically assess them and generate reports quickly to pinpoint high-risk gaps that may otherwise go unnoticed The same goes for automated employee training tools, which create: Integration of employee data Creation and linking of requirements Integration with document control Integration with adverse events, reporting, and change management Employee training software helps ensure the first step is laid out for proper training. Such automated tools allow managers more proactivity in delivering their work, continually making improvements as the organization's processes and systems grow. This latest technology wave is the engineered product equivalent, based on enabling engineering and development, design-in quality and reliability based on current field data." Whether in the form of an everyday tool like Siri, a new product being delivered to market, or in healthcare to generate early diagnoses or more accurate results, AI is truly an advantage fostering healthy change.
The remaining $12bn – over 80% of their revenue – was high margin, recurring service contracts. If you're currently the CEO of a power, transportation, construction, agriculture, oil & gas, life science or healthcare machine company, ask yourself this question – how big is your service business? Many software and hardware product companies already connect to their products to provide assisted services, which help both the manufacturers and users maintain or optimise the security, availability and performance of these products. If you build machines for transportation, power, water, agriculture, construction, oil, gas or healthcare, I hope that you can now see a roadmap that's based on the experiences of the software industry.
Engineers participating in a hackathon last weekend demonstrated an artificial intelligence that they say could someday detect cancerous moles, TechCrunch reports. Apps, mobile platforms, and camera devices designed to evaluate moles and estimate skin cancer risk have a long history filled with successes and failures. That same year, University of Michigan Health System physicians launched UMSkinCheck featuring reminders and instructions for patients to self-examine their moles and skin lesions over time. The FTC alleged that the marketers of both mole photography-based apps "deceptively claimed the apps accurately analyzed melanoma risk," and that the marketers had insufficient evidence to make these claims.
At Intel, we have an optimistic and pragmatic view of artificial intelligence's (AI) impact on society, jobs and daily life that will mimic other profound transformations – from the industrial to the PC revolutions. To drive AI innovation, Intel is making strategic investments spanning technology, R&D and partnerships with business, government, academia and community groups. We have also invested in startups like Mighty AI*, Data Robot* and Lumiata* through our Intel Capital portfolio and have invested more than $1 billion in companies that are helping to advance artificial intelligence. To support the sheer breadth of future AI workloads, businesses will need unmatched flexibility and infrastructure optimization so that both highly specialized and general purpose AI functions can run alongside other critical business workloads.
Data's emergence as a critical business asset has been a persistent theme in every Tech Trends report, from the foundational capabilities needed to manage its exploding volumes and complexity to the increasingly sophisticated analytics tools techniques available to unearth business insights from data troves. We are talking here about a number of cognitive tools that have evolved rapidly in recent years: machine learning, deep learning, advanced cognitive analytics, robotics process automation, and bots, to name a few. Effectively managing rapidly growing data volumes requires advanced approaches to master data, storage, retention, access, context, and stewardship. They may offer even greater business potential in the area of customer service, where cognitive agents could potentially replace some human agents by handling billing or account interactions, fielding tech support questions, and answering HR-related questions from employees.9 Cognitive automation: In the third--and potentially most disruptive--machine intelligence opportunity, machine learning, RPA, and other cognitive tools develop deep domain-specific expertise (for example, by industry, function, or region) and then automate related tasks.
Imagine an Air Force pilot flying an aircraft equipped with highly complex sensor platforms collecting data not only about the jet and the surrounding environment, but the pilot as well. Dr. James Christensen, a portfolio manager at the Air Force Research Lab, described the ability to sense and understand the state and capabilities of the operator as critical to the military's successful employment of highly automated systems. Dr. Justin Sanchez, director of the Defense Advanced Research Projects Agency's (DARPA) Biological Technologies Office, spoke about the challenge of developing precise neuro-technologies that interact with certain circuits of the brain or peripheral nervous system in real time, monitoring for changes in brain signals. Because this capability relies on quality optics, it is conceivable to someday measure this blood flow data from space--allowing collection of biometric data from huge populations.
Between Medicare's aggressive migration to value-based payment models and MACRA's 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design--as well as cultivating a grounding in health data analytics to enhance success. As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS's 24 MSSP ACOs generated savings and received payments of almost $27 million. Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.
Automation and Artificial Intelligence will affect every level of businesses and its people whatever the case, the report warns. Automation and Artificial Intelligence will affect every level of businesses and its people whatever the case, the report warns (stock image). In it, Ethan Hawke's character Vincent Freeman dreams of becoming an astronaut but the society in which he lives is determined by eugenics. In it Ethan Hawke's character Vincent Freeman (pictured) has to beat a society which views people like him, who have not had their genes enhanced, as inferior Overall, nearly three quarters (73 per cent) believe technology will never replace the human mind and the majority (86 per cent) say human skills will always be in demand.
While these factors are critical to achieving the desired performance of enterprise applications, a new processor started to gain attention – Graphics Processing Unit or GPU. Like most of the ML algorithms, deep learning relies on sophisticated mathematical and statistical computations. Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) are some of the modern implementations of deep learning. Irrespective of the type of neural network used, all the deep learning algorithms perform complex statistical computations.