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Australians have low trust in artificial intelligence and want it to be better regulated

australians have low trust in artificial intelligence and want it to be better regulated

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Every day we are likely to interact with some form of artificial intelligence (AI). It works behind the scenes in everything from social media and traffic navigation apps to product recommendations and virtual assistants.

AI systems can perform tasks or make predictions, recommendations or decisions that would usually require human intelligence. Their objectives are set by humans but the systems act without explicit human instructions.
As AI plays a greater role in our lives both at work and at home, questions arise. How willing are we to trust AI systems? And what are our expectations for how AI should be deployed and managed?
To find out, we surveyed a nationally representative sample of more than 2,500 Australians in June and July 2020. Our report, produced with KPMG and led by Nicole Gillespie, shows Australians on the whole don’t know a lot about how AI is used, have little trust in AI systems, and believe it should be carefully regulated.
Most accept or tolerate AI, few approve or embrace it
Trust is central to the widespread acceptance and adoption of AI. However, our research suggests the Australian public is ambivalent about trusting AI systems.
Nearly half of our respondents (45%) are unwilling …

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SAS a leader in IDC MarketScape for advanced machine learning software platforms

sas a leader in idc marketscape for advanced machine learning software platforms

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CARY, N.C., Oct. 29, 2020 /PRNewswire/ — SAS has been named a leader in the IDC MarketScape: Worldwide Advanced Machine Learning Software Platforms 2020 Vendor Assessment (doc #US45358820, October 2020). The report noted “artificial intelligence and machine learning are the most transformative technologies of our time, and SAS is more committed than ever to investing in its potential for enterprises.”
The IDC MarketScape report is the latest recognition from top industry analyst firms for SAS® artificial intelligence (AI), machine learning and advanced analytics capabilities.
“Organizations with large amounts of data – which today is most organizations – value machine learning because it helps them quickly discover insights in their data and improve decision making,” said Susan Kahler, SAS Global Marketing Manager for AI and Machine Learning. “SAS machine learning technologies and the larger SAS® Viya® analytics platform help people at all skill levels – executives, data scientists, business analysts and more – transform data into decisions and bottom-line results through a powerful, collaborative and cloud-native environment.”
According to David Schubmehl, Research Director for AI Software Platforms at IDC, “Success in the rapidly evolving AI software platforms market requires advanced machine learning software platform vendors to continue to innovate and provide tools to help customers accelerate development and …

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How wearable sensor algorithms powered by machine learning could prevent injuries that sideline runners

how wearable sensor algorithms powered by machine learning could prevent injuries that sideline runners

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Vanderbilt technology provides a unique new capability to estimate internal tissue forces and damage due to repetitive loading, which is lacking in existing wearables. Credit: Karl Zelik

A trans-institutional team of Vanderbilt engineering, data science and clinical researchers has developed a novel approach for monitoring bone stress in recreational and professional athletes, with the goal of anticipating and preventing injury. Using machine learning and biomechanical modeling techniques, the researchers built multisensory algorithms that combine data from lightweight, low-profile wearable sensors in shoes to estimate forces on the tibia, or shin bone—a common place for runners’ stress fractures.
The research builds off the researchers’ 2019 study, which found that commercially available wearables do not accurately monitor stress fracture risks. Karl Zelik, assistant professor of mechanical engineering, biomedical engineering and physical medicine and rehabilitation, sought to develop a better technique to solve this problem. “Today’s wearables measure ground reaction forces—how hard the foot impacts or pushes against the ground—to assess injury risks like stress fractures to the leg,” Zelik said. “While it may seem intuitive to runners and clinicians that the force under your foot causes loading on your leg bones, most of your bone loading is actually from muscle …

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AI and Machine Learning Awards – and the winners are…

ai and machine learning awards – and the winners are…

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AI and Machine Learning Awards – and the winners are…

Artificial intelligence might not be a brand new concept, but its use in enterprise IT is certainly growing at start-up rates. Every vendor seemingly has an AI-based tool, or is using machine learning to solve common problems. The challenge is how to sort fact from fiction – or, to put it more charitably, find the absolute best of the best.
We launched the AI & Machine Learning Awards last year to solve exactly this issue. AI has applications in every sector and at every level of business: from simple automation to full-scale cyber defences. Even the most basic implementations can free a workforce from time-consuming manual tasks, with the most recent developments providing practical insights into customer data.

Now in its second year, the AI & Machine Learning Awards celebrate the companies, individuals, products and projects that are changing what it means to use artificial intelligence in the workplace today. Perhaps they are simplifying massive data sets, raising manufacturing efficiency, or even helping to counter the spread of COVID-19. Every finalist in the Awards was a standout example of how AI could be developed and used to change the world we live …

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The Next Generation Of Artificial Intelligence (Part 2)

the next generation of artificial intelligence (part 2)

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Deep learning pioneer Yoshua Bengio has provocative ideas about the future of AI.

Maryse Boyce, IEEE Spectrum

For the first part of this article series, see here.
The field of artificial intelligence moves fast. It has only been 8 years since the modern era of deep learning began at the 2012 ImageNet competition. Progress in the field since then has been breathtaking and relentless.
If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.

What will the next generation of artificial intelligence look like? Which novel AI approaches will unlock currently unimaginable possibilities in technology and business?
My previous column covered three emerging areas within AI that are poised to redefine the field—and society—in the years ahead. This article will cover three more.

4. Neural Network Compression
Recommended For YouAI is moving to the edge.
There are tremendous advantages to being able to run AI algorithms directly on devices at the edge—e.g., phones, smart speakers, cameras, vehicles—without sending data back and forth …

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Machine learning finds heart faults

machine learning finds heart faults

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The team tested their approach on 11 donated human hearts and located AF drivers with an accuracy of up to 81%.
Multi-electrode mapping (MEM) is a technique that can be applied during an operation, in which an array of electrodes is pressed against tissue to measure electrical activity. But AF drivers have proved difficult to locate with sufficient accuracy using this technique – as the remedy is to stop the AF driver by burning it away from within the heart tissue – called targeted ablation.
There is a technique that can accurately locate AF drivers, called sub-surface near-infrared optical mapping (NIOM), which has a resolution of 0.3mm, but is so invasive that it cannot be used inside someone during an operation.

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Deep Learning Market 2020 Detailed Analysis Focusing On Application, Types and Regional Outlook Google, IBM, Microsoft, Qualcomm Technologies

deep learning market 2020 detailed analysis focusing on application, types and regional outlook google, ibm, microsoft, qualcomm technologies

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Latest statistical data titled Deep Learning has been published by Research N Reports. The report offers an overview of various features of recent trends such as Deep Learning which are comprehensively discussed in order to provide an in-depth analysis of the progress of the industries. Effective exploratory techniques such as qualitative and quantitative analysis are also used in order to explore accurate data.
For an effective business outlook, the market study examines various global regions, such as North America, Latin America, Asia-Pacific, Japan, and India by considering different segments such as type, size, as well as applications. SWOT and Porter’s five analyses are also effectively discussed to analyze informative data such as cost, prices, revenue, and end-users.
Ask for Sample Copy of This Report: https://www.researchnreports.com/request_sample.php?id=64529
Top Key Players Included in This Report:
Google, IBM, Microsoft, Qualcomm Technologies, Inc, Skymind, Baidu, Hewlett Packard Enterprise, Sensory Inc., General Vision Inc., Intel, NVIDIA Corporation
Major highlights of this research report:-In-depth analysis of the degree of competition across the globe.-Estimation of Global Deep Learning Market values and volumes.– Global Deep Learning Market analysis through industry analysis tools such as SWOT and Porter’s five …

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Data Drift and Machine Learning Model Sustainability | Analytics Insight

data drift and machine learning model sustainability | analytics insight

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In many real-world applications where machine learning models have been deployed in production, often the data evolve over time and thus models built for analyzing such data quickly become obsolete over time. It becomes essential for data scientists to monitor the model performance over time. Is the machine learning model deployed sustainable and performing consistently? Usually, the scenario that occurs over time, is not because the model stops performing well but simply because the model can no longer capture the right variability of the data be it the dependent or independent variables. The reason for this is not to do with the machine learning model itself, but the data distributions. There is a shift that occurs at the data level, as the distribution of the data used to train an ML model, called the source distribution, is different from the distribution of the newly available data, the target distribution. As a result of this, the relationships between input and output data can change over time, meaning that in turn there are changes to the unknown underlying mapping function. This gap is where the concept of data drift comes in.

Over time, a machine learning model starts to lose its predictive …

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The Global Artificial Intelligence in Energy Market is expected to grow by $ 8.06 bn during 2020-2024 progressing at a CAGR of 48% during the forecast period

the global artificial intelligence in energy market is expected to grow by $ 8.06 bn during 2020-2024 progressing at a cagr of 48% during the forecast period

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Globe NewswireGlobal Intraocular Lens Market (2020 to 2025) – Growth, Trends, and ForecastsDublin, Oct. 29, 2020 (GLOBE NEWSWIRE) — The “Intraocular Lens Market – Growth, Trends, and Forecasts (2020 – 2025)” report has been added to ResearchAndMarkets.com’s offering. The global intraocular lens market is expected to witness a CAGR of 4.9% over the period, 2020-2025. Intraocular lenses (IOLs) are implantable medical devices used for vision correction. The key factors propelling the intraocular lens market are increasing ophthalmic issues, growing cases of cataract in the diabetic population, and rising adoption of advanced premium IOLs. A large section of people above the age of 60 years is affected by several kinds of ophthalmic issues, which are chronic and demand eye corrections. Owing to such scenarios, the growth IOLs has increased with the demand, offering more precise solutions and varied options for physicians for a particular disease. Moreover, the presence of reimbursement policies for essential ophthalmic surgeries and a definite regulatory framework are enhancing growth in the market. According to the National Eye Institute, the United States recorded 7.7 million diabetic retinopathy cases and 24 million cataract cases, and it is expected to reach 11.3 million and 38 million, respectively, by 2030. In addition, the American Association of Ophthalmology states that the major cause of …

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Artificial Intelligence Evangelist Olusola Amusan on Educating About Artificial Intelligence

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ARLINGTON, TX / ACCESSWIRE / October 28, 2020 / Since the advancement of technology, many concepts that were thought to be impossible have been realized. Among the greatest innovations that have emerged from the digital wave is Artificial Intelligence, an idea conceived as early as the stories in Greek mythology. Olusola Amusan is an expert who founded Coven Works, a company that educates people about Artificial Intelligence. Olusola Amusan, also known as the Artificial Intelligence Evangelist, came from humble beginnings. He grew up in Modakeke, Osun State in south-western Nigeria. From a young age, Olusola showed promise as he volunteered for Society for Women and Aids in Africa and founded the Young Elites Club, forming great leadership qualities. Since then, he would go on to greater things.Around 2008, Olusola began creating a high impact coding program that would train 4,600 people who are now top software developers and decision-makers in technology companies today. Olusola was inspired to start his first business when he attended the Federal University of Technology Akure, which taught computer science students Fortran 77, a language that was considered obsolete at the time.Olusola Amusan started his career by working as a research assistant intern with the First Bank of Nigeria Professional Chair in …

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