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Power Is Limiting Machine Learning Deployments

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The total amount of power consumed for machine learning tasks is staggering. Until a few years ago we did not have computers powerful enough to run many of the algorithms, but the repurposing of the GPU gave the industry the horsepower that it needed. The problem is that the GPU is not well suited to the task, and most of the power consumed is waste. While machine learning has provided many benefits, much bigger gains will come from pushing machine learning to the edge. To get there, power must be addressed. "You read about how datacenters may consume 5% of the energy today," says Ron Lowman, product marketing manager for Artificial Intelligence at Synopsys.


BCI:SCIENCE AND PRACTICE.SAMARA 2017

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BCI: Science&Practice is the only annual international conference in Russia with the focus on direct brain-machine interaction. Since October 2015 it is annually organized by Samara State Medical University and IT Universe Ltd in Samara, where a wide range of healthcare technologies, including brain-computer interfaces, virtual reality and other modern IT applications are developed . The conference is supported by Department of Information Technologies of Samara Region and Neuronet Industrial Union. The organizing and program committees members are leading scientists, representatives of state and non-commercial organizations, innovative companies. Attendance is free of charge.


Brainworks uses smartphone camera and AI to detect your heart rate, breathing

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Brainworks is combining artificial intelligence and simple smartphone camera images to automatically detect someone's heart rate or breathing rate. And that's just one of the avenues the Emeryville, California-based company is pursuing in its work to use intelligent ambient biometric sensors to improve health care. Brainworks CEO Phillip Alvelda spoke at our VB Transform AI event on Thursday, and he demoed the technology in real time, both onstage and in an interview. He said health care should be more preventative than reactive. With that in mind, the company's technology is contactless and always-on, though it only works if users have opted in for the constant monitoring, which -- unlike most medical equipment -- is physically non-invasive.


The Power of Artificial Intelligence in Agriculture Analytics Insight

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The agriculture industry now is experiencing rapid growth and adopting advanced technologies in order to bolster the overall yield of the crops. Accessibility of a large number of equipment and state-of-the-art technologies like intelligent monitoring system, drones, robots, among others has totally revolutionized this sector. Artificial Intelligence is one such vital technology in today's digital agriculture that is being implemented and deployed on a large scale for more sustainable use of available resources. In 2017, the global market for artificial intelligence in agriculture was valued at around US$ 545 million, which is now increased and predicted to reach nearly US$ 2,075 million by 2024. The market will rise at a growing CAGR of 21% throughout the forecast period.


Artificial Intelligence Memory

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At the 2019 Semicon Conference Applied Materials (AMAT) had a day-long seminar focused on technology, particularly memory, for artificial intelligence (AI) applications. In addition to talks by AI experts, the company also talked about their tools for manufacturing magnetic random access memory (MRAM) as well as resistive random access memory (RRAM) and Phase Change Memory (PCM). We will talk about a workshop at Stanford in August will explore emerging memories enabling artificial intelligence, especially for embedded products, such as IoT devices. Gary Dickerson from Applied Materials gave a kick-off talk at the seminar. He talked about the growth of data and the importance of memory to support data centers as well as the edge.


Artificial Intelligence: A direction for future growth

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In present Digital age, Artificial intelligence has many prospects for developing countries. Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks associated with intellect and reasoning. According to report by Mc Kinsey 2018 Global institute, artificial intelligence has the potential to add to global output by about 16 percent or around $13 trillion by 2030. It has potential to contribute to an annual average productivity growth of about 1.2 percent by 2030. Artificial intelligence (AI) has potential to contribute towards productivity enhancement in various sectors through job and capacity creation.


Can AI Transform Patient Care from Reactive Craft to Strategic Art? -

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Personalized Analytics is becoming essential in healthcare, stemming from the movement from fee-for-service to a value-based market. The need to preempt and prevent disease on a more personal level, rather than merely reacting to symptoms, has created a significant opportunity for machine learning-based applications. This "analytics of one" approach (using advanced mathematical models and artificial intelligence techniques) is already impacting several key areas: Prime examples include cardiac imaging analysis that aides physicians in assessing conditions, including heart attacks and coronary artery disease, and retinal image analysis to detect diabetic retinopathy. The anticipated goal for AI in healthcare is to enhance and expand the "four Ps" of care delivery – predictive, preventative, personalized and participatory. Predictive: Predictions have existed in healthcare for some decades now, as statistical models based on structured data sources.


How are retailers using artificial intelligence right now?

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By now, most of us are comfortable with the idea that artificial intelligence (AI) is here to stay and that it holds enormous potential to change the way the world works. However, to the average person, the conversation can seem dominated by visions of the future, with experts keen to discuss what AI will do, rather than what it does right now. AI is making a practical impact as we speak, and for industries such as retail, it is already forming a fundamental part of a business strategy. AI learns from data and in particular, it learns how to predict. These predictions can be used in many applications and then integrated into business systems and processes to automate and truly harness the power of AI.


The potential (and limits) of artificial intelligence in HR and what it means for your business

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Jamie Hoobanoff is founder and chief executive officer of The Leadership Agency, a Toronto-based recruitment firm. With North America experiencing record-low levels of unemployment, companies are being forced to compete more than ever for the talent they need. These tight labour market conditions are especially acute for leadership and specialized hard-to-fill positions. When it comes to finding this talent, recruiters must embrace the technological solutions available to them. Although 25 per cent of Canadian jobs will be disrupted by technology over the next decade, new technology is emerging to make sourcing and screening candidates easier.


Student uses AI to diagnose plant diseases

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For some, a rose is a symbol of beauty or love. For Shaza Mehdi, it is a connection to her mother, but also a gateway to innovation. Mehdi's mother, Afshin, grows rose bushes at their Lawrenceville home. But a few years ago, the plants kept getting diseases, ruining the blooms. Mehdi tried diagnosing the flowers by Googling images of plant diseases and comparing those images with the sick roses.