Why companies are investing in Natural Language Processing

Speech bubbles

According to IBM’s Global AI Adoption Index, nearly one in three IT pros say their business is now using artificial intelligence, with 43 percent reporting their company has accelerated their rollout of AI because of the COVID-19 pandemic. While recent advances in the technology are making AI more accessible than ever, the annual survey, which included 5,501 companies, also found a lack of AI skills and increasing data complexity are continuing challenges.

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Customizing the infinitely configurable AI: It takes Data and Time

Data has a better idea

COVID-19 drastically impacted how businesses operate. In our virtual world where contactless is the norm, companies are finally prioritizing digital transformation so they can continue conducting business without needing to rely on in-person interactions. However, the digital world is vast and competition is steep. To operate their business more efficiently and compete effectively, companies are often forced to consider cutting-edge tools, such as artificial intelligence (AI).

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Make Responsible AI part of your Company’s DNA

AI as an enterprise DNA

Ethical AI is the foundation of successful and impactful AI systems. The European Union has gone as far to establish Ethical Guidelines for AI. This is timely, as demonstrated by a recent survey that reported that two-thirds of internet users believe companies should have an AI code of ethics and review board. But ethical AI is just the beginning. Beyond ethical AI is responsible AI.

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5 common ways companies use RPA to enhance Document Processing

Paper plane

With all the hype around robotic process automation (RPA), it can be helpful to remember that the vast majority of the data running through RPA automations originates or terminates with a document. In fact, I’d estimate that about 80% of RPA automations fall into this category.

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How the Open Edge is driving Digital Transformation

State of the Edge To understand and foster better practices across businesses and the technology industry, the Linux Foundation created the LF Edge in 2019 and rolled the State of the Edge into it last year. State of the Edge is a vendor-neutral platform for open research on edge computing that is dedicated to accelerating innovation by crowdsourcing a shared vocabulary for edge.

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A 5-step approach to implementing Machine Learning

Man climbing steps

Establishing machine learning within any organization requires planning and collaboration. As with any technology insertion and/or transition, it starts with a vision and moves on to execution followed by continuous monitoring and improvement. The basic steps to building an ML implementation plan are described in five simple steps below: VDOCR — Vision, Data, Organizational alignment, Change management and Revalidation.

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Agile Manifesto: 20 years on and Agile remains elusive

Agile-dancer

Last month marked the 20th anniversary of the Agile Manifesto. The manifesto emerged from meeting representatives from extreme programming, SCRUM, DSDM, adaptive software development, Crystal, feature-driven development, pragmatic programming and others sympathetic to the need for an alternative to documentation driven, heavyweight software development processes.

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Microsoft Exchange attack underlines how Vulnerable your organizational Data is

Lock on circuit board

It is a little over a week since Microsoft Exchange email servers were attacked by a group which Microsoft as described as a network of hackers it calls Hafnium. It is not clear who these people are, but the attack, which impacted as many as 60,000 companies – and by some estimates 100,000 – has forced Microsoft to release out of-band emergency patches for Exchange Server 2013, Exchange Server 2016, and Exchange Server 2019.

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We need Ethical Artificial Intelligence

Robotic Process Automation (RPA), Insights: The Productivity Step

The diverse use cases for AI raise ethical and moral questions about how technology is used in a fair and just manner. Artificial intelligence (AI) is doing what the tech-world Cassandras have been predicting for some time: It is sending out curve balls, leaving a trail of misadventures and tricky questions around the ethics of using synthetic intelligence. Sometimes, spotting and understanding the dilemmas AI presents is easy, but often it is difficult to pin down the exact nature of the ethical questions it raises.

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