Today, modern artificial intelligence (AI) affects practically every major industry in our world. Fast computer processing, rapid reproduction of connected devices, and robust internet connectivity have steadily increased the presence of AI, and more innovations are on the way. In fact, 1,600 of the 9,100 patents IBM inventors received in 2018 were AI-related. The call to AI innovation will only grow stronger in the coming years, making it crucial for tech research and development (R&D) companies to begin projects now. Easly assists Canadian businesses with SR&ED financing so they can conduct R&D and spark innovation. Here, we offer a list of artificial intelligence trends to watch out for in 2022.
AI Business Trends
AI evolves as its demand changes individual and professional lives. The current market trends suggest end-users want AI that delivers services specific to their business or personal goals. This mindset acts as a primary driving force for new trends in AI.
Small and Wide Data
Small data provides relevant insights into business problems, while wide data encourages the analysis and synergy of multiple data sources. Companies favour small and wide data over big data as it produces richer analytics and situational awareness for AI when tackling business problems. Experts believe that 70% of organizations will be concentrated on small and wide data by 2025, emphasizing how AI needs more context for the data it collects.
AI Platform Operation
The need to leverage AI for businesses has made Al platform implementation critical in recent years. By transforming projects from concept to production, companies can rely on AI to remedy enterprise-wide issues. So far, automation platforms and AI orchestration have amplified company adoption of AI through governance, reusability, and scalability.
Organized Resource Use
Due to the numerous computer resources, data, and models associated with AI, businesses must utilize the technology with premium efficiency. Composite and generative AI, multi-experience, and transformers provide solutions to an array of business problems with increased effectiveness, making them popular in the AI market.
As AI technology becomes more modern, so too must its ethics. Without such features, AI devices will always adhere to the biases in their data. This flaw can lead AI to make incorrect decisions. Additionally, more AI stakeholders are looking for enhanced transparency and fairness in technology than before. Responsible AI answers this dilemma as it helps develop trust in the technology while also encouraging regulatory compliance.
AI models allowed health researchers to examine vast amounts of data about the coronavirus quickly, leading to the fast production of vaccines. Moving forward, AI may entirely alter the way scientists create vaccines. Artificial intelligence trends are growing in the healthcare field overall as the technology can quickly analyze big patient data sets and allow healthcare providers to optimize services at lower costs.
One of the most pioneering developments in AI is teaching robots to learn by observing human action. A robot at the company Nvidia can perform tasks in a real-world environment by watching how human employees conduct their work. This trend expresses a more hands-off approach to AI training.
Machine Learning Trends
While there are numerous branches of artificial intelligence, one noteworthy branch is machine learning (ML). This technology creates algorithms to help machines comprehend data and make decisions faster than people. ML is tied to software testing automation, making it crucial to the IT industry. Tech giants like Apple, Facebook, and Google have incorporated ML into their processes, and analysts believe it will increase significantly until 2024, with the most growth in 2022 and 2023. There are numerous artificial intelligence trends to monitor in the ML landscape.
ML and the Internet of Things (IoT)
IoT connectivity allows multiple devices to join across an Internet network while 5G transfers and receives information quickly. As the number of connected devices and shared information increases each year, more fields require 5G capabilities for connection. Machine learning enhances IoT devices by making them more intelligent and secure. Gartner analysts estimate over 80% of IoT projects will implement ML technology by 2022, indicating tech professionals highly anticipate the integration of these two technologies.
Automated machine learning helps subject matter experts create efficient models for increased productivity. Conveniently, AutoML does not require extensive knowledge of programming and ensures that training does not affect the quality of work.
Small enough to fit in your pocket, TinyML is machine learning technology that’s shrunken down to exist on compact hardware. It acts as a bridge between intelligent devices and AI.
Using machine learning, tech professionals can automate cybersecurity efforts. They form anti-virus models that identify various kinds of threats and defend against cybercrime, including hacking, malware, and code difference.
Finance AI Innovation with Easly
With the countless artificial intelligence trends on the horizon, ensure your company has the funding it needs to stay on top of R&D efforts. At Easly, we help Canadian businesses finance their innovative projects with SR&ED tax credits and grants through our Capital-as-a-Service platform.
To learn more about SR&ED financing for your AI research and development, contact us today.