Computing Technology Trends to Look Out For in 2021 and Beyond (Podcast)


Key Podcast Takeaways: 

  • The digitization of data will continue to increase as more and more device come online but really the value is becoming clear as the transformation shifts to real-time machine intelligence and automation

  • The power-budget, thermal mechanics, and form factor are major requirements to deploy ruggedized hardware for rugged edge computing.

  • Hyperautomation, empowered or intelligent edge computing, and AI security are some popular technology trends that require incredible processing power

Computing Technology Trends to Look Out  For in 2021 and Beyond

Computing technology as whole provides major benefits from its conveniences and ability to streamline many traditional processes in the business world. A key reason why technology is so valuable for today’s digital economy is its ability to process, store, connect endless amounts of digital data for real-time insights or better business decisions. The digitization of data will continue to increase as more and more devices come online; but where the most value from data is becoming clear lies within machine intelligence and the ability for automation. New age technology advancements have helped shape new business models for incredible machine learning and artificial intelligence in many new market verticals and applications.

The value for technology will continue to explode as long as humans demand for more conveniences and better efficiencies across personal, operational and business goals. This is becoming more evident as more and more enterprises invest into digital transformation objectives that leverage data for actionable intelligence that benefit the bottom line.

See below for a brief overview and some summary bullet points from the podcast. Otherwise, tune into the podcast above for more information and a deeper dive into three trends that rely on the latest computing technology in 2021 and beyond. Premio's Product Marketing Director, Dustin Seetoo provides some thought leadership on some computing trends to be aware about in 2021 and Beyond.  


3 Industry Trends That Rely on The Latest Computing Technology

Trend #1: Hyperautomation

This tech trend is taking automation and empowering it with AI and ML across a variety of different tools, and not just to support automation itself, but for more holistic analysis, measuring, monitoring, and discovery. When we think about machine learning practically, how does it work with various enterprise tools to drive artificial intelligence?

Hyperautomation is a key trend because it enables automation in tasks that can eliminate the need for human interaction in traditional processes. Automation continues to be made possible through the aggregation of big data and the ability to train machines with programmable algorithms.Today, enterprise businesses are not just interested in the ability for faster and better processing but truly require a way to have better control. The podcast dives in three stages of autonomy where technology helps enable a closed-loop of autonomy:

  • 1st Stage of Hyperautomation = Cognition – the definition of cognition is the ability to acquire knowledge and understanding through thought, experience, and the senses. Humans use their 5 innate senses from sight, hearing, smell , taste and touch to generate contextual and situational awareness. This is the same in hyperautomation where machines need incredible amounts of data for their own context and awareness.
  • 2nd Stage of Hyperautomaton = Intelligence – once the machines can sense and have contextual situational awareness, it can run machine learning algorithms from sensory data input and streamline a level of decision making and intelligence. Ultimately this stage allows machines to provide early detection and predictive analytics which is a pivotal piece to hyperautomation but paves a means for control.
  • 3rd Stage of Hyperautomation = Full Control - A closed-loop of autonomy is to provide intelligence with real business results with speed and accuracy. This is made possible with AI-enabled processes that use both cognition and intelligence to accelerate real-time change and business decisions



Trend #2 – Empowered Edge or Intelligent Edge

As edge computing already focuses on bringing information processing, collection and delivery closer to the source, empowered edge looks to take that one step further to support the steadily increasing use of IoT devices. If edge computing is already pushing for this compute proximity, what is the value of a push for an empowered edge?

    • Another way to look an empowered edge is to define it also as an intelligent edge. Similar to the hyperautomation trend, intelligence models that have been trained are now being shifted closer to where data is being generated, creating this demand for performance at the edge with incredible processing, storage, and connectivity.

    • Smart applications today and their unique workloads now dictate the amount of compute hardware required to efficiently run inference models for real-time detection with incredible speed and accuracy. Ultimately, the key benefit by keeping the most critical workloads in close proximity to data is that it can reduce latency and open up more bandwidth for real-time results.

    •  A re-occurring theme among Premio engineers and embedded computing markets is an area where Premio is focusing its core capabilities which is defined as rugged edge computing. This specialized area embraces all the key elements of decentralized local processing with low-latency connectivity but ensures hardened reliability in the ruggedization of edge computers. These new demands are challenging engineers to design and deploy outside standard comfort zones.

    • Premio recognizes the need to support software advancements with hardware strategies providing the rugged, high-performance systems that enable reliable deployment in the most severe physical settings. From external enclosure to internal components, every element of a rugged edge computer is purpose-built through a combination of mechanical and thermal engineering to address environmental issues such as strong vibration, severe temperatures, and the presence of moisture or dirt. These industrial-grade computers are also validated to execute functions with extreme processing power and storage capacity, built to eliminate downtime and ensure stable 24/7 operation. Premio’s leadership in rugged edge system design and manufacturing opens a new realm of IoT integration and automation capabilities and powers a real transformation in how industrial businesses operate and compete.
To learn more about 10 essential hardware computing needs to empower the intelligent edge read this blog

Trend #3: AI Security 

While hyperautomation and empowered edge capabilities means more efficiency and more smart enterprise functionality, it also comes with new security vulnerabilities, often ones that IT teams are just not trained for. What makes AI deployments particularly vulnerable?

  •  As more enterprise business make their digital shift with hyper automation and data processing at the network edge, another trend that is extremely important is the factor of cybersecurity. It’s paramount that security risks are reviewed in detail in order to protect data transmissions and its security vulnerabilities across multiple stages of data manipulation. Cybersecurity best practices manage risk of attacks and implement processes to mitigate attacks on its most critical operations and applications.

  • There are three key aspects to AI security; protecting the AI systems, leveraging the AI to enhance security, and anticipating how attackers may use AI against you
  1. Protecting AI-powered systems: Data from AI powered systems are critical to many decision making results. Any potential attack on datasets that enable AI can be detrimental to operations and its business goals. Data AI security can help protect machine learning models, training pipelines and AI training data.

  2. Leveraging AI to enhance security defense: A key benefit from machine learning is its ability to determine results through data. Machine learning models can also be used to better understand patterns from past attacks as well as uncover potential attacks ahead of time for security prevention

  3. Anticipating nefarious use of AI by attackers: The ability to identify the type of attack and have necessary tools to defend against them is key for AI Security.

How Can Premio Inc Help Your IoT Deployments?

  • Expertise in The Design, Engineering And Manufacturing For Embedded Computers and Edge computers In The USA For Industrial IoT Deployments
  • Premio excels and drive market penetration with purpose-built hardware that consolidates system level design with the latest technology accelerators.
  • 30+ years of extensive design expertise in computing solutions to address rugged and industrial IoT requirements.
  • Thermal simulation chambers to guarantee wide operating temperatures for outdoor and remote environments.
  • Global turnkey manufacturing and support for rugged IoT gateways and computers for scalable mass deployments.
  • Long Product Life Cycles to ensure reliability and longevity.
  • Deep understanding of IoT technologies and how they benefit edge computing hardware solutions.
  • Regulatory testing and compliance options for embedded computers in the North America Markets.