Since the beginning of the 2010s, artificial intelligence (AI) has been a torchbearer of the digital transformation we are witnessing and benefitting from today. The year 2021 brought many significant changes and research breakthroughs in AI viz., intelligence edge and cloud, decision intelligence, creative AI, and more were the biggest AI trends. In this year, AI also opened new avenues in new tech domains like AI-based NFT art, augmented reality, metaverse, and more. While these AI trends and the latest tech applications will continue to scale in 2022, there are some areas where AI technologies will lead to wide-range adoption. Let’s dive into top AI technology trends of 2022 that are going to revamp the tech world.
The following list focuses on the nebular yet promising technologies in the AI-backed industry.
iNFT
As the Non-fungible tokens or NFT craze is taking a front seat in ushering in the new crypto age, a new category of NFTs: the intelligent (or interactive) NFT or iNFT is gaining traction. The trend kick-started when in June of this year, the artist Robert Alice teamed with Alethea.AI to create the world’s first iNFT, which was dubbed ‘Alice.’Â
Alice had appeared in a Twitter live video in which it answered real-time queries from viewers; however many of its responses were just “I don’t know” or “I’m sorry.”
An iNFT is a smart NFT with a GPT-3 prompt built-in as part of its immutable smart contract. The iNFT created is not only perceptibly intelligent but also interactive and animated, thanks to carefully prepared prompts maintained at the smart contract layer. The hard-coded prompts invoke a cutting-edge Transformer Language model to enable generative possibilities made feasible only by recent advances in few-shot and single-shot learning. Â
The inbuilt intelligence and self-learning abilities of iNFTs set them apart from general NFTs. The incorporation of GPT-X into the software architecture opens up a world of possibilities in an interactive discussion. Its self-learning capability allows it to provide new types of intelligence to both the creator and the owner of the iNFT.
Furthermore, because iNFTs are decentralized structures, they may be utilized by anybody and are unaffected by censorship.
This year, the worldwide market for NFT sales volume surged 182 times in the first half of 2021 compared to the same period in 2020, reaching a startling value of US$2.5 billion, as predicted.
An illustration of their rising popularity is when Visa acquired a “CryptoPunk” – one of the hundreds of NFT-based digital avatars – for approximately US$150,000 in the cryptocurrency Ethereum in August 2021. Meanwhile, iNFT is also starting to see wide adoption in tandem in the NFT Marketplace. For instance, The Revenants, another of the first-ever iNFTs collections, shattered OpenSea records for a collection drop, garnering nearly US$10 million in a week and rocketing into the Top 10 collections on OpenSea in the previous seven days.
There is also a possibility of Instagram and Snapchat introducing iNFT as AR filters, while brands will boost product recommendations.
AI in Metaverse
The metaverse is a virtual immersive digital ecosystem made up of separate but interconnected networks that will communicate through yet-to-be-determined protocols. According to Gartner, it allows for the creation of decentralized, collaborative, and interoperable digital elements that interact with real-time, geographically oriented, and indexed content in the actual world, thereby creating immersive experiences for people.
The metaverse is the internet’s next evolutionary step, however, it is still in its early stages of development. The move to the metaverse is expected to be accelerated after Mark Zuckerberg announced about combining virtual reality technology with the social network of Meta. At present many firms are vying for dominating certain aspects of the metaverse, for example, Roblox. Even artificial intelligence will be used to enable, populate, and sustain the metaverse. This also means that the use of AI in the metaverse will be one of the leading AI trends of 2022.
For instance, Microsoft will incorporate Mesh, a virtual experience collaboration platform, into Microsoft Teams next year. Mesh builds on existing Teams features like Together mode and Presenter view to make remote and hybrid meetings more collaborative and immersive by letting participants know they’re in the same virtual space. Mesh will use Microsoft’s mixed reality technology and HoloLens headgear for virtual meetings, conferences, and video interactions in which Teams members may engage as avatars.
It is speculated that the need for huge advancements in processing power, network performance, and AI capabilities can imply metaverse will not be fully developed until the late 2030s or early 2040s. But for 2022, AI can help build virtual avatars, develop games, and enforce human-computer interaction (HCI) in the metaverse.
No code and Low Code
With data science and AI applications increasing every year, there will be a surge in jobs in this sector. However, having employees proficient in coding is not always possible for companies. In other words, one of the greatest roadblocks to effective and proper AI deployment is the scarcity of professionals in the field. With no-code and low-code solutions, you might seek to overcome the barrier, merely by providing usable interfaces. Low-code and no-code software development tools focus on visual aspects to construct software, such as dragging and dropping.
As a result, no-code and low code interfaces will grow more popular since a lack of programming experience or a thorough understanding of statistics and data structures will no longer be a barrier in 2022. By combining multiple pre-made modules and providing them with appropriate data, these AI systems would allow us to construct better products.
Recently, OpenAI, a research group founded by Elon Musk, released Codex, a programming model that can produce code from natural, spoken human language. At re:Invent 2021, AWS teased the launch of Amazon SageMaker Canvas as a no-code machine learning platform, stating that it enables business analysts to create machine learning models for predictions without understanding how to code or having prior machine learning knowledge. With its straightforward graphical user interface, SageMaker Canvas supports multiple problem types such as binary classification, multi-class classification, numerical regression, and time series forecasting.
Though code-based software is unlikely to go away anytime soon, low-code and no-code solutions can significantly reduce the time it takes to develop an app or program. As this technology evolves in 2022 and converges with the capabilities of cloud infrastructure, developers’ creativity and imagination will not depend on having strong coding skills. No doubt, with rising reliance on no-code and low-code software, the coming year will usher in a new market for this AI technology trend.
Hyperparameter Language Models
Since the announcement of GPT-3 last year, tech behemoths are working on building new AI language models that surpass the previous models in terms of hyperparameters and efficiency. This year, Microsoft and NVIDIA announced Megatron-Turing Natural Language Generation (MT-NLG), the world’s largest and most powerful monolithic transformer language model. Other leading players like OpenAI concentrated on enhancing the factual accuracy of GPT-3 Language Models, while DeepMind built a model dubbed Gopher with 280 billion parameters to explore the limits of massive language models.
These billions of language-based hyperparameters are allowing data scientists to create models that fully grasp the language and can generate human-level articles, reports, and translations. They can even write programming, create recipes, and social media content too.
We can anticipate bigger and better language generation models in 2022. Also, announcements of such models will be another awaited AI technology trend that will make headlines like GPT-3. Simultaneously, experts are voicing their concerns about the ethical and social dangers linked to such models that use social media and other open datasets for training, thereby accidental generation of malicious content. To minimize this, extensive research will also be carried out to ensure larger hyperparameter language models produce qualitative results.
ESG risks Free AI
Apart from AI apocalypse scenarios narratives by movies, there are genuine reasons why the expanding use of AI in many sectors of corporate, institutional, and personal activity is attracting the attention of authorities, concerned groups, and watchful citizens throughout the world. With AI being employed in industries such as law enforcement, healthcare, and recruiting, the availability of biased data or biased output might jeopardize confidence in a better AI-powered future.
The goal is to keep AI biases to a minimum so that it doesn’t replicate human bias. At the same time, there is a clarion call to limit the AI system’s carbon footprint and pressure on depleting semiconductor materials. On the other hand, supply networks and company operations are also strained by climate change and extreme weather occurrences. As these constraints intensify in 2022, AI will play a critical role in assisting organizations in meeting sustainability goals through enhanced productivity, data collecting, and carbon accounting, as well as increased supply chain robustness.
Besides, there is an urgent need to have conversations around ethical AI to develop reliable, transparent, and trustworthy AI systems, which also offer users improved levels of explainability for the decisions it makes.
This year, in a historic move, UNESCO has released a worldwide standard on artificial intelligence (AI) ethics, which is likely to be adopted by over 200 member countries. China has also developed its AI ethical standards, emphasizing user rights and fitting with its goal of becoming the world’s AI leader by 2030.
Even European Parliament’s ban on policing and biometric mass monitoring is also another step made to ensure better use of AI. Even the United States is not behind; in a first-of-its-kind project, the White House’s scientific advisors have suggested an AI “Bill of Rights” to limit the scope of artificial intelligence (AI) harms.
There is a huge possibility that all these new laws and regulations will ensure environmental, social and governance (ESG) risks free AI technologies in 2022.
Apart from the ones listed above, AI technologies like neuro-symbolic networks, Quantum AI, Augmented Intelligence will go mainstream in 2022.
