The outbreak of COVID-19 has hastened the implementation of numerous technological innovations, of which Artificial Intelligence (AI) stands out as a compelling instance. Among various sectors, healthcare witnessed the most extensive investment in AI, and it is predicted that the AI market and revenue will experience a rise of 21.3% prior to 2023.
The proliferation could be linked to myriad factors. Companies of diverse sizes and domains are acknowledging the ability of Artificial Intelligence (AI) to confer a competitive edge by enhancing productivity and efficiency. The investment in this field could be interpreted as a sign of key trends that are expected to prevail in the upcoming year, along with the creation of novel applications.
Outlined below are the top five.
Indicators of Multimodal AI
Numerous critics of AI highlight the flaws in the training process as proof that the technology could never achieve its complete potential. As a result, AI consortiums are examining alternatives to conventional training models that have constraints in their ambit. One of these substitutes is multimodal artificial intelligence (AI), which encompasses correlating the output with various data sources.
The amalgamation of visual and auditory AI can move machine learning algorithms closer to human perceptual capabilities. Multimodal AI integrates data from various sources to decode and act on an object. Google’s Multitask Unified Model (MUM) stands as an instance of such a model that leverages contextual information from 75 different languages to amplify search results, rather than depending solely on singular keywords in a single language.
The objective of Multimodal AI is evident but intricate: to educate computers so that they learn to become more skilled by fusing data from diverse sources. As we progress towards 2023, these models are expected to evolve into advanced and effective structures, but their widespread implementation is still distant.
Standard for Responsible AI
The notion of constructing Artificial Intelligence (AI) algorithms with uprightness has been deliberated before, but mostly in a conceptual framework. Fortunately, an increasing number of scholars and supporters are labouring to guarantee the establishment of comprehensive norms and regulations for the formation of ethical AI algorithms, given that an escalating number of teams are fabricating AI-enabled solutions.
By the conclusion of 2023, ethical deliberations are anticipated to become the norm for AI development teams. This trend can be attributed to the proliferation of teams dedicated to ethical engineering in established and nimble tech companies.
It is conspicuous that an expanding number of regulatory frameworks are emerging which AI developers must comply with. Instances consist of the New York Artificial Intelligence Solution Audit Law and the proposed Artificial Intelligence Act in the European Union. Although neither of these frameworks is impeccable, they do manifest that advancements are being made in the right direction.
AI-Enabled Development Boosts Efficiency.
The year 2023 witnessed a deep-rooted influence of Artificial Intelligence (AI) on coders. Despite its shortcomings, the release of Github Copilot elicited immense astonishment owing to its ability to facilitate pair programming. Copilot is not the solitary AI-based alternative that development teams have at their disposal; Amazon AWS, Salesforce, and other providers are developing similar products.
The extensive abundance of unbarred source code, permitting integration of AI solutions into several frameworks and development platforms, is expected to steer these various initiatives towards a tipping point by 2023. Moreover, mature AI algorithms that can convert code to distinctive languages are already at our disposal, although they have not yet achieved universal employment.
Meta’s TransCoder, which was previously developed by Facebook, is one of the most notable self-supervised neural transcompiler systems. This process employs deep learning to proficiently interpret C++, Java, and Python 3 programming languages. As we move ahead, we can anticipate that this and comparable approaches will become the norm.
Pre-built AI Solutions Gaining Popularity
It has become noticeably frequent to observe that prominent software companies such as Amazon, Google and Microsoft proffer all-inclusive solutions for enterprises. These corporations have been furnishing AI-based solutions for a substantial amount of time. However, it is plausible that by 2023, a growing number of companies will implement these solutions in both software and hardware forms.
It is expected that businesses will increasingly employ AI-empowered customer service solutions such as Google Contact Center AI and Amazon Connect. These technologies employ machine learning to administer cutting-edge automated assistance, enhancing customer engagements with extremely efficient bots.
The employment of tools like Azure Percept and AWS Panorama will become increasingly ubiquitous in corporate environments. Azure Percept is a potent toolkit for edge computing that encompasses AI capabilities such as computer vision and natural language processing. Meanwhile, AWS Panorama utilizes cloud-based computer vision inference to devise novel models for edge deployment. Both are instances of readily available AI technology that will have a substantial impact on businesses in 2023.
The Change in Approach from Supervised to Reinforcement Learning
It is arduous to predict with complete conviction whether or not this will occur by 2023, however, it is not out of the question. Reinforcement learning is garnering growing focus from research teams as a viable option to supervised learning. Therefore, researchers are more prone to experimenting with alternative approaches to algorithm training rather than solely relying on the collection and refining of data.
Reinforcement Learning sets itself apart from traditional techniques of algorithm development as it does not employ pre-existing data. Instead, the aim is to give the algorithm an objective and permit it to independently ascertain the most effective means to accomplish that objective. This process entails the algorithm dabbling with several alternatives until it hits upon the optimal solution.
DeepMind, which is an Alphabet company specializing in artificial intelligence, has demonstrated a firm dedication to this method; their AlphaGo solution, based on reinforcement learning, has delivered remarkable outcomes. As a subsidiary of one of the largest technology corporations worldwide, the company advocates the change in approach that is anticipated to persist through 2023.
There is an expectation that the rate of AI technology adoption will escalate in 2023. Nevertheless, the outcome cannot be confirmed until the year has transpired. AI will continue to advance throughout the upcoming year and has the potential to be the groundbreaking technology that many envision.
