Articles about AI

In an intensely competitive economic climate, midmarket customers are caught in an especially challenging position right now. Faced with many of the same problems we see large enterprise customers grappling with -- mushrooming data demands, unpredictable business growth etc. -- but with smaller budgets and fewer personnel to overcome them. 

How can these customers compete against the big IT-spenders? Automation and analytics tools integrated with Artificial Intelligence (AI) and Machine Learning (ML) capabilities hold the answer -- helping to manage ever-growing storage demands more efficiently with fewer personnel, fewer resources and less human intervention.  

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Language AI is one of the most challenging areas of artificial intelligence, one where mainstream AI is far from coming near human-level performance, because it needs world knowledge to be solved (AI complete).

The shortcomings of modern machine learning approaches can be explained by the low efficiency of artificial neural networks. Because natural evolution is mainly driven by efficiency, I developed a strong interest for biologically inspired natural language understanding, hence the following book recommendations.

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"The impediment to action advances action. What stands in the way becomes the way." -- Famous Stoic and Roman emperor, Marcus Aurelius.

Some organizations have heavily invested in analytics and data scientist teams -- particularly in the manufacturing, retail, and automotive sectors. COVID-19 has disrupted their supply chains, and they find themselves needing to source answers in a day, not in the weeks they would have had to plan through changes last year. They must turn to experts on the front-lines of the business for action, and yet combine this expertise with the power of data scientists’ models to ensure they take optimal measures.

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In the second of our series of pieces looking at technology predictions for 2021 we look at the field of AI and machine learning.

This has the potential to impact on many areas of commerce, science and digital transformation, but what do industry experts think?

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In response to the economic impact of COVID-19 companies are turning to their investments in AI to deliver both short-term cost-cutting and long-term technology innovation to drive revenue and efficiency.

A report from ML operations and management software specialist Algorithmia finds that 83 percent of organizations have increased their budgets for AI/ML and that the average number of data scientists employed has increased 76 percent year-on-year.

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The major challenges faced by businesses looking to implement AI and machine learning include transparency, bias, and quality of training data.

Swedish startup Unbiased is launching a new Data Marketplace on the Telos blockchain platform, aimed at providing privacy-centric and decentralized development tools to companies working with AI and Machine Learning applications.

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COVID-19 has highlighted the need for change in the healthcare industry. When the pandemic eventually subsides, medical systems will emerge with the knowledge of where they need to improve. AI in healthcare can and will address many of these issues.

Medical AI is nothing new, with 89 percent of healthcare executives reporting that AI is already helping them. Now that healthcare improvement is a more prominent issue, the adoption of this tech will only increase. The post-COVID medical world will rely on these technologies. Here are five ways healthcare organizations will use AI to improve after the pandemic.

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The COVID-19 pandemic has seen large numbers of people adapting to new working patterns and ways of interacting.

AI-based transcription platform Otter.ai has seen a fivefold increase in demand in recent months and has transcribed 750 million minutes from over 25 million meetings. We spoke to Otter's founder Sam Liang to find out more about how it's helping to shape the future of work and education.

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Companies are planning to increase their spending on AI/ML as a result of the pandemic, and many have realized that those initiatives should have been a higher priority for their organizations all along.

A new survey of enterprise IT leaders from Algorithmia, a provider of ML operations and management solutions, shows that 91 percent of respondents were spending at least $1,000,000 annually on AI/ML prior to the pandemic, and 50 percent say they are planning to spend more than that going forward.

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Let’s start with the definition of "REPLACE," from Merriam-Webster: To restore to a former place or position (e.g. replace cards in a file); To take the place of especially as a substitute or successor; To put something new in the place of (e.g. replace a worn carpet).

Now, let’s check the definition of "ENHANCE": To increase or improve in value, quality, desirability, or attractiveness (e.g. enhanced the room with crown molding); To increase or improve (something); To make greater or better (e.g. the products claim to enhance beauty).

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The future of work is happening now: despite skeptics prophesying growing unemployment rates, AI not only creates new job roles but also changes the employee experience for the better. Assisted with AI tools and analytics, workers no longer have to spend hours (and, consequently, years) on meaningless routines, since they can focus on job aspects that truly bring value.

So how will artificial intelligence transform employee experience and enhance employee engagement? Read on to learn how AI contributes to digital workplace transformation.

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In the past six months, COVID-19 has evolved from a speck on the world radar to a full-blown pandemic. While it has claimed the lives of many and shed a massive spotlight on some of the major issues in healthcare, it has also served as a catalyst for innovation.

As with nearly every element of the healthcare system, applications of machine learning and artificial intelligence (AI) have also been transformed by the pandemic. Although the power of machine learning and AI was being put to significant use prior to the Coronavirus outbreak, there is now increased pressure to understand the underlying patterns to help us prepare for any epidemic that might hit the world in the future.

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When progressive technologies start to deliver on their potential, we can expect a wholesale shift of vendors looking to get on the bandwagon. First the technology enthusiasts and early adopters will come to validate the promises of the newest technology and hone its potential into something viable for the mainstream. Once that is done, the early majority, late adopters and finally, even the skeptics jump in as well.

Finally the time is here for Artificial Intelligence and Machine Learning (AIML) in cyber. There is a widespread move out of the early adopter stage and into the early majority stage of adoption. We need to get onboard if we are going to thwart cybercriminals. The good news is that the industry is recognizing the power and the value of AIML and is finally making investments in this space.

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How do you know you had a good day at work? If you did, how would your boss know?

These questions are especially important in the current environment where so many people are working from home without the insight that watercooler discussions, office pop-ins and other face-to-face contact would typically provide. Our reliance on technology to get work done has been growing for decades, but work-from-home orders due to the coronavirus pandemic have accelerated that reliance even more.

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Microsoft and Sony Semiconductor Solutions have announced details of a new partnership that will see the two companies working on AI-powered smart cameras and video analytics together.

The partnership means that Microsoft Azure AI capabilities will be embedded on Sony’s intelligent vision sensor IMX500. Additionally, Sony will create an enterprise-focused smart camera managed app that will be powered by Azure IoT and Cognitive Services.

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