GoogleTranslate Service


AI and Edge computing

January 7th, 2021 by Graham Attwell
ball, abstract, pattern

geralt (CC0), Pixabay

A recent MIT Technology Review Insights reports on a survey of 301 business and technology leaders around their use and future planned us of Artificial Intelligence. The survey confirms that the deployment of AI is increasing, not only in large companies but also in SMEs. It also points to the emergence of what is known as edge  comput9ing, using a variety of devices closer to the applied use than cloud computing allows and capable of near real time processing.

38% report of those surveyed report their AI investment plans are unchanged as a result of the pandemic, and 32% indicate the crisis has accelerated their plans. The percentages of unchanged and revved-up AI plans are greater at organizations that had an AI strategy already in place.

AI is not a new addition to the corporate technology arsenal: 62% of survey respondents are using AI technologies. Respondents from larger organizations (those with more than $500 million in annual revenue) have, at nearly 80%, higher deployment rates. Small organizations (with less than $5 million in revenue) are at 58%, slightly below the average.

Cloud-based AI also allows organizations to operate in an ecosystem of collaborators that includes application developers, analytics companies, and customers themselves.

But while the cloud provides significant AI-fueled advantages for organizations, an increasing number of applications have to make use of the infrastructural capabilities of the “edge,” the intermediary computing layer between the cloud and the devices that need computational power.

Asked to rank the opportunities that AI provides them, respondents identify AI-enabled insight as the most important (see Figure 2). Real-time decision-making is the biggest opportunity, regardless of an organization’s size: AI’s use in fast, effective decision-making is the top-ranked priority for large and small organizations.

For small ones, though, it is tied to the need to use AI as a competitive differentiator.

Again, the need for real-time data or predictive tools is a requirement that could drive demand for edge-based AI resources.

Survey respondents indicate that AI is being used to enhance current and future performance and operational efficiencies: research and development is, by a large margin, the most common current use for AI, used by 53% of respondents, integrating AI-based analytics into their product and service development processes. Anomaly detection and cybersecurity are the next-most-deployed AI applications.

Large organizations have additional priorities: 54% report heavy use of robotic process automation to streamline business processes traditionally done by humans, and 41% use AI in sales and business forecasting. For organizations with AI strategies, 40% rely on robotic process automation, and 42% use AI to estimate future sales.

Please follow and like us:

Comments are closed.

  • Search Pontydysgu.org

    Social Media




    News Bites

    Cyborg patented?

    Forbes reports that Microsoft has obtained a patent for a “conversational chatbot of a specific person” created from images, recordings, participation in social networks, emails, letters, etc., coupled with the possible generation of a 2D or 3D model of the person.

    Please follow and like us:


    Racial bias in algorithms

    From the UK Open Data Institute’s Week in Data newsletter

    This week, Twitter apologised for racial bias within its image-cropping algorithm. The feature is designed to automatically crop images to highlight focal points – including faces. But, Twitter users discovered that, in practice, white faces were focused on, and black faces were cropped out. And, Twitter isn’t the only platform struggling with its algorithm – YouTube has also announced plans to bring back higher levels of human moderation for removing content, after its AI-centred approach resulted in over-censorship, with videos being removed at far higher rates than with human moderators.

    Please follow and like us:


    Gap between rich and poor university students widest for 12 years

    Via The Canary.

    The gap between poor students and their more affluent peers attending university has widened to its largest point for 12 years, according to data published by the Department for Education (DfE).

    Better-off pupils are significantly more likely to go to university than their more disadvantaged peers. And the gap between the two groups – 18.8 percentage points – is the widest it’s been since 2006/07.

    The latest statistics show that 26.3% of pupils eligible for FSMs went on to university in 2018/19, compared with 45.1% of those who did not receive free meals. Only 12.7% of white British males who were eligible for FSMs went to university by the age of 19. The progression rate has fallen slightly for the first time since 2011/12, according to the DfE analysis.

    Please follow and like us:


    Quality Training

    From Raconteur. A recent report by global learning consultancy Kineo examined the learning intentions of 8,000 employees across 13 different industries. It found a huge gap between the quality of training offered and the needs of employees. Of those surveyed, 85 per cent said they , with only 16 per cent of employees finding the learning programmes offered by their employers effective.

    Please follow and like us:


    Other Pontydysgu Spaces

    • Pontydysgu on the Web

      pbwiki
      Our Wikispace for teaching and learning
      Sounds of the Bazaar Radio LIVE
      Join our Sounds of the Bazaar Facebook goup. Just click on the logo above.

      We will be at Online Educa Berlin 2015. See the info above. The stream URL to play in your application is Stream URL or go to our new stream webpage here SoB Stream Page.

      Please follow and like us:
  • Twitter

  • Recent Posts

  • Archives

  • Meta

  • Categories