Top 7 AI and Machine Learning trends to watch in 2022
Artificial intelligence and Machine Learning are taking more and more relevance in businesses to make critical decisions, and create innovative products. Let’s face it; AI already exists in our daily routine for every action we do. Think about the lovely conversations with your Siri or Alexa to automatize your home devices, translate from one language to another, set reminders, listen to updated weather forecasts, and, eventually, make coffee for you.
Just imagine the massive impact AI and Machine Learning have on our lives and jobs. As our demands towards technology grow and change, Machine Learning and AI are arranged to surprise us with exciting new trends. According to SEM Rush, for instance, the global AI market is predicted to skyrocket in the next few years, reaching a $190.61 billion market value in 2025. Here are the 7 top trends for AI and Machine Learning in 2022.
As a result of such a high-connected world, hacking and cybercrime may inevitably become more of a problem. Indeed, every connected device to a network can be unavoidably a potential target for dishonest intruders. As networks become more complex, identifying connected devices’ points of failure is getting extremely challenging. For this reason, AI can play a relevant role here. Some of the most significant future AI applications are likely to be employed in cybersecurity. Indeed, AI can investigate network traffic and recognize patterns with nefarious intentions to keep our devices safe.
AI and the Metaverse
The term “metaverse” has recently come to our ears because of Mark Zuckerberg’s ultimate project: Meta. The metaverse is a unified digital environment, where users can work and play together, sharing immersive experiences (created by the users themselves) — like a virtual world. AI will unquestionably be the protagonist of the metaverse since it will help to create multiple online environments or will support humans with tasks to do or be (video)games partners, as it is already happening.
The lack of skilled engineers who can design tools and algorithms constitutes a problem employing AI and Machine Learning-driven technologies. As a result, codeless and low-code solutions aim to overcome such an issue by providing simple interfaces to build complex systems.
Creativity & Language Modelling
Thanks to AI, one can produce art, music, poetry, plays, and even video games. In 2022, new models such as GPT-4 and Google Brain will reshape the edges of content creation. For instance, such models could write headlines (or whole newspaper articles) and newsletters, designing logos and infographics. We usually associate creativity as a typical human skill; this is undeniably coming closer to the concept of what constitutes “real” intelligence for humans.
Language modelling will apply AI too. LM is a process that allows machines to properly understand and communicate with humans. In 2022, GPT-4 will be released by OpenAI, the most advanced (and largest) language model ever created that machines can use to process language. GPT-4 may contain up to 100 trillion parameters, making it 500 times larger than its predecessor GPT-3. This will take a big step closer in holding conversations with machines/software that will be indistinguishable from the human ones.
AI will be the “brain” to drive autonomous cars, boats, and aircraft in the following decade. Tesla states that its vehicles will prove full self-driving capability by 2022. Its competitors Waymo (by Google), Apple, GM, and Ford, are also expected to announce significant projects in the next year(s). In 2022, we are also likely to see the first autonomous ship crossing the Atlantic by the Mayflower Autonomous Ship (MAS), powered by IBM.
Moreover, Mobility as a Service (MaaS) is getting more and more noticed — thanks to the European National Recovery and Resilience Plan. MaaS is more technology than a physical form of transport. It consists of an ecosystem from data (or it is data-driven itself), which employs AI, Machine Learning and Deep Learning technologies.
Let’s move on to the IoT sector. According to Gartner, over 80% of IoT projects in organizations will include AI and ML by 2022. IoT provides a connection to the internet for all devices to react to different situations following the collected data. Therefore, AI and ML must gain insights from data quickly, automatically identify patterns and detect anomalies in smart sensors and devices. Information can be about temperature, pressure, humidity, air quality, sound, speech recognition, and computer vision applications. According to DZone, the major segments that include a confluence of AI and ML are wearables (fitness, health trackers, heart rate monitoring applications, smartwatches), smart home (lights, thermostats, smart TV), smart city (smart energy grids, street lights and mobility) and smart industry (operations, logistics and supply chain).
Forecasting and analysis for business
AI and ML can represent a significant boost in business forecasting and analysis; thousands of matrics can be analyzed in milliseconds to make more accurate predictions and forecasts. As a result, different business sectors are already employing such a feature; e.g. Fintech companies forecast demand for various currencies depending on the market conditions and consumer behaviour in real-time.
To wrap up, Artificial Intelligence and Machine Learning are already part of our daily lives; however, as technology evolves, such solutions will manage more and more aspects of our existence and work. Quoting the billionaire tech entrepreneur Mark Cuban:
“Artificial Intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise, you’re going to be a dinosaur within 3 years”.
As reported above, these are only 7 of the infinite AI and Machine Learning applications trends for 2022. Get ready, technology at its finest is yet to come.