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Now in 3D: Deep learning techniques help visualize X-ray data in three dimensions

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Computers have been able to quickly process 2D images for some time. Your cell phone can snap digital photographs and manipulate them in a number of ways. Much more difficult, however, is processing an image in three dimensions, and doing it in a timely manner. The mathematics are more complex, and crunching those numbers, even on a supercomputer, takes time. That's the challenge a group of scientists from the U.S. Department of Energy's (DOE) Argonne National Laboratory is working to overcome.


Council Post: Understanding Contextual AI In The Modern Business World

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Emilia Kirk is the Global Head of Growth at Seedtag, responsible for Client, Marketing and Product Growth. Visit Seedtag's site to hear more There are certain developments in the world of business that cannot be ignored. They revolutionize the way you work and become absolutely essential in the ways you operate. However, some developments, such as contextual AI, work quietly in the background and are sometimes seen as nice-to-have rather than business-critical. In my experience, this is a flawed assumption. I believe contextual AI needs to be seen as part of the absolute necessities to drive success.


Building trustworthy AI is key for enterprises

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One of the challenges with the pursuit of AI is the mismatch between the science fiction concept of artificial intelligence and the real-world, practical applications of AI. In movies and science fiction novels, AI systems are portrayed as super-intelligent machines that have cognitive capabilities equal to or greater than that of humans. However, the reality is that much of what organizations are implementing today for artificial intelligence are narrow applications of AI. This is in clear contrast to artificial general intelligence (AGI). The limit of our current AI abilities lets organizations implement specific cognitive abilities in narrow domains, such as image recognition, conversational systems, predictive analytics as well as pattern and anomaly detection.


Key elements of successful enterprise AI implementation

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There is no question that the enterprises that successfully leverage AI's potential will be the ones to get ahead. While businesses are more and more certain about the goals they want to use AI for, how to execute and deploy it successfully remains a difficult question. In today's world, the dynamics and efficiency of operations are crucial factors, and data is the key to flourishing in the rapidly changing business reality. Data provides insights from various areas of business activity. Solutions based on artificial intelligence or machine learning not only support the analysis of huge amounts of data, but also provide a new approach to optimizing and automating core processes.


SqueezeNet implementation in TensorFlow

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SqueezeNet provides a smart architecture that achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters. Additionally, with model compression techniques, the authors were able to compress SqueezeNet to less than 0.5MB (510 smaller than AlexNet). What is achieved using these strategies? Intuition for the third strategy was that large activation maps (due to delayed downsampling) can lead to higher classification accuracy, with all else held equal. The building block of the SqueezeNet is the fire module.


PEEZMO AI 21 NFT Collection

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PEEZMO AI 21 is a NFT collection of 4.000 unique NFTs -- created by a super advanced self learning Artificial Intelligence. The Machine is creating art through human emotions and serves the own smart contract with a new fresh digital high quality collage every hour until the end of 2021. PEEZMO AI 21 is HOLISTIC MAINSTREAM ART. It creates a digital collage art based on synthetic feelings. The Machine is in a constant learning process, comparable to a good bottle of wine which is tasting better by maturing over time.


How Coke Bottlers Save Millions with AI

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Retailers around the country rely on a network of nearly 70 independent Coca-Cola bottlers to manufacture and ship cases of liquid refreshments. It's a finely tuned supply chain, and it ultimately serves customers well. But getting a consolidated view into the millions of paper-based billing and shipping documents was a major headache for the network–that is, until an innovative use of computer vision and NLP technology helped digitize it. Starting around 2007, Coca-Cola North America worked to "refranchise" its bottling and shipping operations, which spans 51 production facilities, 350 distribution centers, and involves more than 55,000 employees. The company says the goal of this refranchising effort is to "bring the heart of Coca-Cola back to the local bottler," which in some cases are multi-generational companies more than 100 year's old. A key player in all this is the Coca-Cola Bottler's Sales and Services Company.


Catching the artificial intelligence buzz

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Backpacks to track bees, bushfire modelling and sensors to detect broken water pipes are some of the technologies being developed in Australia as part of an artificial intelligence boom. Digital Economy Minister Jane Hume says artificial intelligence has the capacity to improve the lives of all Australians. Senator Hume will tell a Committee for Economic Development of Australia event on Tuesday the government had two roles to play in terms of AI: an enabler and a standards setter, especially in terms of ethics. Earlier this year the government announced a $1.2 billion digital economic strategy which included an additional $124 million commitment to the AI initiatives. The CSIRO estimates AI technology will contribute $22 trillion into the global economy by 2030.


Shielded from scrutiny, Epic algorithms deliver inaccurate information

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Several artificial intelligence algorithms developed by Epic Systems, the nation's largest electronic health record vendor, are delivering inaccurate or irrelevant information to hospitals about the care of seriously ill patients, contrasting sharply with the company's published claims, a STAT investigation found. Employees of several major health systems said they were particularly concerned about Epic's algorithm for predicting sepsis, a life-threatening complication of infection. The algorithm, they said, routinely fails to identify the condition in advance, and triggers frequent false alarms. Some hospitals reported a benefit for patients after fine-tuning the model, but that process took at least a year. Unlock this article by subscribing to STAT and enjoy your first 30 days free!


Dialpad Introduces Meetings and Channels - UC Today

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Dialpad, a leading provider of AI-powered solutions for collaboration and communication, recently announced the arrival of two new communications solutions. Dialpad Meetings, previously known as UberConference, is the state-of-the-art solution designed to bring new capabilities for meetings and collaborative conversations into the UCaaS experience. Dialpad Channels, on the other hand, aims to provide a natural and smooth messaging experience to keep the conversation moving in the virtual work environment. The Channels offering delivers a watercooler chat alternative to the modern workforce, to improve employee engagement and strengthen bonds between team members. Dialpad Meetings is a tool giving companies a single and unified view of communications in one environment.