A Framework for Enterprise Artificial Intelligence Adoption

June 25, 2019

Artificial Intelligence (AI) is no longer a technology of the future – it’s recent popularity and the prevalence of machine learning makes the adoption and implementation of AI capabilities possible. But how can your organization adopt AI in a meaningful way, at the enterprise level, to achieve measurable results? This white paper demonstrates our framework to help organizations adopt and implement AI pilots to solve complex business problems and data challenges that require sophisticated techniques.

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OTHER WHITEPAPERS
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Getting Started with Data Acquisition Systems

whitePaper | August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.

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A Blueprint for Equity and Inclusion in Artificial Intelligence

whitePaper | June 28, 2022

Artificial intelligence (AI) has been accelerating across sectors. It has great potential to benefit society but the technology’s full potential can only be realized if it includes the diversity of the populations it represents throughout every step of its development. With growing concerns about bias, data privacy and lack of representation, it is critical to re-evaluate the way in which AI is both designed and deployed to ensure that all affected stakeholders and communities reap the benefits of the technology, rather than any harm.

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AI/ML Annual Research Report 2022

whitePaper | September 20, 2022

Artificial intelligence and machine learning (AI/ML) is on every organization’s radar. Businesses and IT professionals are finding some amazing use cases for AI/ML and already experiencing its benefits, but there’s still so much untapped and unrealized potential.

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Applying Artificial Intelligence to Built Environments through Machine Learning

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.

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The Commonsense Path to Simple and Secure Remote Worker IT Management

whitePaper | July 28, 2022

Many businesses have recently evolved to support large remote or hybrid workforces. This initial transition was imagined to be temporary, relying on home networks to provide the connectivity needed for work. Now, two years later, companies are contemplating technology improvements to address a more permanent remote workforce.

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Software Development Trends to Look Out for in 2022

whitePaper | October 6, 2022

It is not unusual to see software development trends change year after year. The pandemic has only accelerated the whole process, and it seems that the trends are changing even faster. What was once considered as acceptable practice in software development might no longer be the case in the foreseeable future. This is why startup founders and big corporation managers should be aware and well-informed of where all the software industry trends are heading to and how to strategize in the best possible app to develop and place an app.

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