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The future tech trends – 2021-22

No-code/Low-code and everything-as-a-service revolution
Ongoing democratization of data and technology has throttled a new trend that puts the necessary tools in the hands of a layperson – this revolution is being called as The Citizen Developer movement.

Innovation has been triggered more with the explosion of self-service and do-it-yourself models. Not every company needs to hire an army of computer geniuses to build their own digital brain when they can simply lease one for the work they need doing. Ready-built AI solutions exist for everything from marketing to HR, project management, and planning and design of production processes. More and more of AI and IoT infrastructure will be deployed, by and for companies, without owning a single server or proprietary piece of cognitive code.

No-code interfaces will become more popular as a lack of programming knowledge, or a detailed understanding of statistics and data structures, will cease to become a barrier to bringing a world-changing idea into reality.

OpenAI and Codex (a model that generates code from natural spoken human language) will soon be mainstream. As technology matures, lesser and lesser time will be spent in writing code and more time will be invested in analyzing the huge amounts of data accumulated by the organization over decades, to derive more value from it!

Cybersecurity mesh
This calls for a distributed and self-calibrating approach to the problems and threats of the extreme digital era. The future of cybersecurity is all about fanatical level of Heuristics detection.

  • Zero-trust strategy. Thirty-four percent of data leaks and breaches originate on the inside of the network itself. A zero-trust network philosophy, whereby any device is by default, not trusted to access the broader network.
  • Protecting applications and IT services. For rolling out large-scale applications in an enterprise environment, companies are increasingly deploying loosely coupled microservices modules instead of monolithic big-bang releases. This naturally creates a mess of microservices that are easy to identify in case any breach happens, and hence easier to mitigate too.
  • Mesh training. Adopting DataSecOps approach, where IT and data scientists collaborate from the very beginning on building security measures into the infrastructure and application layer, ensures applications transparently interface within the security mesh to improve integration of all relevant systems and devices.

Embedded data and embedded analytics

  • Companies that embed data and analytics in their business processes and digital thinking mindset will have a higher chance to succeed.
  • Embedded analytics is a set of capabilities that are tightly integrated into the existing systems (like CRM, ERP, marketing automation, and financial systems) that bring additional awareness, context, or analytic capability to support decision-making related to very specific tasks.
  • These tasks may require data from multiple systems, but the output is not the centralized overview of information. It is targeted information to support a decision or action in the context in which that decision or action takes place. In plain speak, embedded data/analytics is equivalent of your car GPS that keeps guiding you on the real-time situation on ground.

Transparency, governance, and accountability a.k.a. the responsible AI
Real-life applications of AI have dramatically matured/grown, which is why, more and more AI systems are facing increased and stringent scrutiny! Any AI-assistance technology needs to adhere to all the below paradigms:

  • Use a human-centered design approach.
  • Identify multiple metrics to assess training and monitoring.
  • When possible, directly examine your raw data to actually understand what is going on in real-life use-cases.
  • Understand and openly share the limitations of your dataset and model.
  • Test, test, test, and test yet again for the solution to be all-encompassing for human population.
  • Continue to monitor and update the system after deployment.

Always keep the kill-switch/human over-ride switch ready.

Transparent and explainable AI with a regulated and governance framework around it is essential.

Edge computing
Sovereignty and edge-computing needs are the new challenges for technology leaders. Extreme compute, happening closer to the users and resources, is now the need of the times. Edge computing and sovereign clouds are now counterbalancing extreme cloud consolidation.

Instead of a model, where clients connect to servers, thousands of clients are all connected to each other and then perform the processing tasks collectively. The ideal edge computing use-case connects millions of IoT devices to form an enormous intelligent network that can then perform tasks, which are usually only possible in very big data centers.

By combining edge and cloud compute, you can utilize the power of distributed systems by processing data on devices directly, which then send it to the cloud. Here it can be processed, analyzed, or saved, using less (or even unavailable) processing power.

Connected sensors and machines
Connected sensors and machines are at the peak of a revolution already. We have machines that offer unheard of parameters to now be measured.
Anything that can be measured can then be improved. The combination of sensor data and powerful analytics on the edge and cloud compute, will act as a catalyst for unprecedented innovations. IoT and embedded sensor technology will allow us to monitor even the most rudimentary of devices, and thereby help the manufacturers get better insights and users get more value from their invested machines

Digitization, datafication, and virtualization
During 2020 and 2021, many of us experienced the virtuali­zation of our offices and workplaces, as remote working arrangements were swiftly put in place. Coming months will make us embrace metaverse – persistent digital worlds that exist in parallel with the physical world we live in.

We will carry out many of the functions we are used to doing in the real world, including working, playing, and socializing in this metaverse.

While most of us today have experienced somewhat immersive virtual realities through VR headsets, a range of new devices will soon greatly improve the experience offering tactile feedback and even smells.

Ericsson, which provided VR headsets to employees working from home during the pandemic, and is developing what it calls an internet of senses, has predicted that by 2030, virtual experiences will be available that will be indistinguishable from reality.

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