We’ve witnessed a huge shift in how Artificial Intelligence (AI) is becoming a crucial component of many firms’ business strategy over the past several years. Machine Learning (ML) and Artificial Intelligence has accelerated the journey of digital transformation, and the pandemic prompted significant technical innovation. In 2022 and beyond, it will reach unprecedented heights.
AI has become increasingly integrated into numerous businesses over the last decade. The era has seen significant development in AI and ML based tools, applications, and platforms. Fields as diverse as healthcare, manufacturing, law, banking, retail, real estate, accounting, and digital marketing, among others, have all been touched by these technologies.
These are the main AI trends that we can expect to see in 2022.
AI in cybersecurity
Three main factors have changed the network security infrastructure: the continued rapid growth in technology; the adoption of a remote working culture; and the trend of companies moving their infrastructure to the cloud. This has prompted growing reliance on AI to assist under-resourced security operations analysts in staying ahead of threats as cyberattacks expand in volume and complexity.
Organizations will need to include cybersecurity in their budgets in a smarter manner than many do now. Cyber criminals are continuously creating innovative ways to attack critical infrastructure and exploit vulnerabilities. Humans can no longer safeguard businesses from dangers on such a large scale, which necessitates the implementation of AI based solutions.
AI delivers the threat detection technologies needed to identify breach threats and, as a result, boost security protocols. Furthermore, AI aids in the detection and prioritisation of threats and virus attacks before the system detects them, proving to be the ultimate solution in terms of cybersecurity.
AI-driven vehicles
Autonomous driving promises a future without accidents, speeding tickets and parking problems. It will impact the way town planners look at roads, towns and cities that will be reconfigured to accommodate totally autonomous cars and trucks, planes and boats.
Mobility will ultimately be transformed. But we are not there yet, and there is still a long way to go.
However small steps are being made and cars are getting progressively more connected. For example, cars can self-park or monitor the awareness levels of the driver, making sure he does not fall asleep.
Tesla is one of the most high-profile participants in the race and Elon Musk has never been shy of making ambitious claims. Tesla claims that its cars will display full self-driving capabilities by 2022, although it is unlikely that they would be ready for widespread usage before the end of this year.
Does this mean self-driving cars will never happen? Probably not. But we are seeing a greater degree of collaboration between the big players, particularly around data gathering, which will be extremely important. And big names like Ford, Waymo (Alphabet), and Baidu have all committed to making their datasets public. We’ve also recently seen the establishment of the Autonomous Vehicle Computing Consortium – with members including Arm, Toyota, General Motors, and Nvidia – which aim to foster a more collaborative approach to solving the field’s toughest challenges.
This year we will hopefully witness the first autonomous ship crossing the Atlantic. The Mayflower Autonomous Ship (MAS), powered by IBM and constructed in conjunction with non-profit ProMare, will once again attempt the journey. It was forced to turn back during its original attempt this year.
Those people using these cars in the future will probably reflect on how we thought it was normal that 1.3 million people died in traffic accidents every year, 90% of which were caused by human error. For self-driving cars, 2022 should be a year to remember.
AI in healthcare
In recent years, there has been a lot of discussion about the next wave in AI deployment in the healthcare industry. In fact, combining AI and blockchain yields exciting developments for healthcare professionals. Access to the blockchain allows them to display patient medical records, while AI can assist in decision-making, since its decisions are based on large quantities of data.
Scientists already use AI models and computer vision algorithms in sectors like pandemic detection, vaccine research, drug development, thermal screening, facial identification with masks, and CT scan analysis in the fight against COVID-19.
AI algorithms can detect and assess potential risks and make accurate predictions to stop COVID-19 from spreading. In addition, AI assists in the development of vaccinations by finding critical components that make them effective.
AI helping the Workforce
The fear has always been that machines or robots would someday replace humans, making some jobs outdated or superfluous. However, the reality is that when firms begin to use robots to crunch data and AI to understand and extract useful information from it, it becomes even more important for humans to collaborate with technology.
In some sectors, such as banking, they are facing significant transformation. Currently they are mainly focussed improving the user experience using biometrics such as face recognition, but AI could also be used for fraud detection and decisions in trading of stocks determining which leads to pursue and which to dismiss.
Engineers use AI to detect preventive maintenance, allowing them to treat a machine problem before it occurs. This means that intelligent AI-driven solutions will be available in any profession, allowing workers to work more efficiently.
AI in language models
Language models are AI systems that can generate convincing text or speech, conversing with humans and responding to questions. They will continue to improve in 2022.
The best-known language model is OpenAI’s GPT-3 by OpenAI, which is the biggest and most advanced language model ever created. Yet DeepMind said in December that its new “RETRO” language model can beat others 25 times its size. Furthermore, OpenAI’s GPT-4, will be even more powerful.
Catherine Breslin, a machine learning scientist who used to work on Amazon’s Alexa, thinks Big Tech will race toward even larger language models next year. The objective, of course, is to be able to hold conversations that are indistinguishable from those of a human.
Low-code and no-code AI
Implementing AI technologies can be difficult and expensive. No-code and low-code solutions try to solve this problem by providing simple interfaces that may be used to build progressively complex AI systems in theory. No-code AI systems will allow us to create smart programmes by plugging together different, pre-made modules and feeding them with our own domain-specific data. This process is similar to how web design and users can now design web pages and other interactive systems simply by dragging and dropping graphical pieces together, thanks to no-code UI tools.
Natural language processing and language modelling (see above) technologies show that we may soon be able to use only our voice or written commands. All of this will play a significant role in AI and data technology’s continued “democratisation.”
Content creation and chatbots with generative AI
Modern AI models can generate text, sounds, and images that are nearly indistinguishable from non-synthetic real data in terms of quality.
Instead of only performing regular orders, a chatbot seeks to grasp people’s intentions. The AI-driven chatbot is used by a variety of businesses to enable human-level communication to their clients or consumers. Chatbots can be found in a variety of industries, including healthcare, finance, marketing, travel, and hospitality.
Chatbots powered by AI allow for the automation of administrative processes. In the healthcare industry, for example, they reduce manual labour. Chatbots aid in the scheduling of appointments, the sending of medication reminders, and the provision of responses to patients’ questions.
Such chatbots are used in other domains to deliver targeted messaging, increase customer engagement and assistance, and provide personalised offers to consumers.
AI and Facial Recognition
At the moment, facial recognition looks to be ‘on trend’. It’s moving into many areas of daily life. Both commercial and state organisations use it for a variety of objectives, including tracking terrorists. Face recognition technology is now more widely used, and more governments are preparing to use it to improve their security measures.
Developers are creating deep learning algorithms to ensure this technology goes beyond basic facial recognition and can comprehend images and scenarios. It will also assist supply clients with more customised messaging, making it a noteworthy AI trend for the coming years.
IoT and AI are merging
The distinctions between AI and the Internet of Things (IoT) are becoming increasingly blurred. While each technology has its own merits, when combined, they provide better and more unique opportunities. AI-enabled IoT enables intelligent machines that simulate smart behavior and supports in decision making with little or no human interference.
AI algorithms require data before drawing any conclusions. Thankfully, IoT devices generate a large amount of data that can be mined for useful information. As a result, AI algorithms exploit the data acquired by IoT to generate beneficial outcomes, which are then applied by IoT devices.
IoT systems have become more sophisticated thanks to AI’s capacity to quickly extract insights from data. Over the next few years, more than 80% of enterprise IoT initiatives will use AI in some form, up from 10% currently.
The Future of AI
Because AI solutions are becoming more popular, the future of AI appears to be bright. These AI-powered solutions are making huge strides forward: autonomous vehicles, robots and sensors for predictive analysis in manufacturing, virtual assistants in healthcare, natural language processing for reports from the media, virtual educational tutors, AI assistants, and chatbots that can take the place of humans in customer service are all on the horizon.
Header photo by Vackground on Unsplash