The world will never be the same as it was during the pre-pandemic era. With COVID-19 halting certain advances and furthering the rest, selective innovation has been a cause for concern. With a majority of setups, both personal and commercial, planning to use their resources and finances with care, not every technological move is expected to see light. Regardless of adoption plans, artificial intelligence (AI) is expected to take center stage in 2021, more so with the global landscape shifting toward automation.

Then again, AI isn’t a market-moving resource in itself. Instead, it is a technology that has the capability to empower different walks of life, especially to make certain activities easier to do and companies more productive.

What Does AI Signify?

AI, like any fancy term, gets thrown around quite frequently. However, as a concept, it signifies a consortium of self-learning machines that can act on and respond to logical reasoning and mathematical approaches. While AI has numerous bookish definitions, it basically corresponds to any system that can think and act rationally, often by mimicking human intelligence.

AI Inspirations from 2020

Before we jump into the trends, we need to see how developed AI was in 2020. That way, we would be able to enlist only the most progressive trends capable of making an impact.

The first major AI-centric inroad has to be the OpenAI GPT-3. For those who aren’t aware of the concept, GPT-3 is better known as the “Generative Pre-Trained Transformer 3.” Basically, GPT-3 happens to be a more humane version of humanoid robots, continually trained to write and read text.

Those who followed advancements in AI up to GPT-2 will be amazed to see the number of parameters GPT-3 is stacked with as a part of a neural network.

In case you aren’t aware of neural networks, they are the typical building blocks of an AI-powered system, stacked with relational algorithms, patterns, and anything else that equates to a typical human mind.

Coming back to the advancement, GPT-3 and the language processing marvel were followed by AlphaFold 2, created by Google’s fabled DeepMind consortium. This system is still in its formative years, but aims to increase the rate and potency of pharmaceutical manufacturing, precisely by analyzing scopes, protein sources, structures, and almost anything relevant.

While the system is expected to work like humans when it comes to identifying and getting rid of structural anomalies, it only gets the job done faster.

Therefore, it wouldn’t be wrong to categorize an AI system as a more evolved and speedier version of a trained human mind.

Trends to Watch Out For

Now that we are aware of the direction AI is taking, it’s time to check out the trends that might change the fate for certain commercial setups, entertainment hubs, healthcare units, and more, going into the future.

Voice-Driven AI

Handsfree seems to be the way to go in a post-pandemic world. Moreover, with a majority of companies resorting to remote work setups, we should watch out for voice-driven AI systems in 2021 and beyond. Language-backed AI minimizes touch-based interactions and makes machines even more intelligent, responsive, and secure.

Moreover, corporations, streaming device manufacturers that rely on voice-controlled accessories, and home Internet of Things (IoT) solution providers will reap the benefits of this trend.

For those who aren’t aware of IoT, it is a network that connects each compatible smart device to others, allowing them to exchange commands and inputs.

AI in MarTech

Combining marketing with technology is what AI strives to achieve. While organizational marketing revolves around seamless data processing, the technology needs to be equipped to handle diverse data sets with ease. The likes of a recommender system, including AI-driven chatbots (i.e., automatic chat-based intimation protocols), wearable devices, IoT-based sensors, and more, are expected to be the handiest resources going into the future. 

Simplifying further, AI is expected to empower marketers with requisite technologies while helping them add proactivity to the scheme of things.

AI in Cybersecurity

Cyberthreats will remain imminent in a post-pandemic world, moreso as we shift closer to a work-from-home culture. However, AI can help mitigate a lot of threats by aiding organizations and independent setups in steering clear of most attacks. With AI, you can succinctly pair algorithms to mimic threat detection.

AI algorithms are subject-independent and can be paired with any cybersecurity resource. Therefore, if you are planning to identify virtual private networks (VPNs) that work with streaming devices or encrypted resources, AI-powered entities are the ones to look at. Besides, with AI making its way into the streaming arena, trained algorithms are expected to tighten the security standards associated with third-party app usage.

That means if you have a streaming device like Roku or a Fire TV stick, an AI-powered VPN and a compatible device can automatically allow you to select the best and most secure piece of content for consumption.

AI in Cloud Computing

If you are a melomaniac, you would be able to relate better to this trend and the numerous possibilities that come along with it. The role of AI in cloud-based approaches is accelerating rapidly. Starting from listening to music directly over a cloud-based application to ordering things from e-commerce stores, cloud-based resources have already made their presence felt in our lives.

However, the applications are expected to become even more intelligent, with AI-centric concepts added religiously to each. AI-powered cloud apps will be more scalable and responsive. Besides, the data deciphering capabilities of the same would be out of this world.

Services that are already trained for using AI and machine learning (ML) innovations include Amazon Web Services (AWS), Google Cloud, and more. Moving forward, we can expect a majority of AI-centric startups to make use of cloud resources and vice versa to manage key operations.

AI in Healthcare

As per the existing scenario, nothing makes more sense than AI in healthcare. However, online medical consultations have also picked up pace amid the pandemic, with social distancing becoming part of the new normal. Nevertheless, the healthcare sector is expected to reap the benefits of AI, with new and improved setups being capable of automatic diagnosis, anomaly detection, and more.

Besides, we might see major developments in and large-scale deployment of the previously discussed AlphaFold 2 resource as a new way to manufacture pharmaceutical products.

Edge Intelligence to Avoid Adverse Incidents

The marine, mining, and oil and gas sectors operate in rough environments that require complex equipment. These machines are equipped with an increased sensor to ensure safe, reliable, and efficient operation. It needs to establish closed-loop actions or make corrections as soon as errors are seen to keep operations going optimally. 

Given the fast-paced nature of field operations and challenging environments for high-speed communication, the idea of making decisions in real-time will accelerate in these industries, leading to the adoption of edge intelligence or the ability to provide near-real-time insights from big data analysis.

Reinforcement Learning to Foolproof Operations

A combination of the field operator expertise and supervised and unsupervised learning allowed AI models to reach acceptable accuracy levels in predictive and prescriptive analytics. Organizations are set to move toward reinforcement learning that relies on decisions made based on experience. In this approach, the AI systems interact with the environment to learn and drive decisions toward a goal that rewards actions taken. Without specifying all asset failure scenarios, the algorithm will repeatedly learn by exploring all possible options.

The Bottom Line

Upon scrutinizing each trend carefully, it is evident that AI, as a resource, will shift toward automating a majority of human-driven tasks, albeit faster. However, AI in isolation wouldn’t be as effective as newer advancements would be required in big data, neural networking, and more.
Still, research concerning AI is a dynamic process, and we might need newer developments in 2021 to reshape and reiterate our focus on the trends. Then again, that is a discussion for another day.