Latest Trends in Artificial Intelligence
Over the past decade, Artificial Intelligence (AI) has meshed into various industries. The era witnessed a dramatic increase in tools, applications, and platforms based on AI and Machine Learning (ML). These technologies have impacted healthcare, manufacturing, law, finance, retail, real estate, accountancy, digital marketing, and several other areas.
Companies are investing in AI research to find out how they can bring AI closer to humans. By 2025 AI software revenues alone will reach above $100 billion globally (Figure 1). This means that we will continue seeing the advancement of AI and Machine Learning (ML)-related technology in foreseeable future. AI changes notably fast, so you'll need to go out of your way to keep up with the latest trends if you want to stay as informed as possible. Let's take a look at everything you need to know about the latest AI trends.
Figure 1. Annual AI Software Revenue (Source: Tractica)
1. Intelligent Process Automation
In the latest technology trend, organisations are looking for intelligent automation tools to solve business challenges and increase productivity, efficiency, and accuracy, benefiting the organisation. One of the successive waves, Intelligent Process Automation, or IPA, brings together Robotic Process Automation (RPA) and Artificial Intelligence (AI) technologies to empower rapid end-to-end business process automation and accelerate digital transformation. In RPA, computer software 'robots' handle repetitive, rule-based digital tasks which are driven by structured data. However, many business processes now are fed by or generate large amounts of unstructured and real-time data. IPA makes it possible to automate processes with machine learning and analytic capabilities and cognitive technologies, like computer vision, Natural Language Processing (NLP), and fuzzy logic. The adoption of IPA is expected to grow in the coming days, with large-scale growth expected across several industries.
2. A Shift Toward Cybersecurity
With data becoming more precious than ever before, there's no shortage of cyber criminals out there looking for new ways to compromise it. One of the downsides of novice-level AI is that hackers can manipulate them to access the sensitive information. So, a significant trend in AI is developing technology to recognise and report common types of attacks. Anti-virus software is also being developed by using AI in the same manner as this technology can help prevent a malware threat from having devastating consequences. When it comes to businesses, AI-powered cybersecurity tools also can gather data from a company's own communications networks, digital activity, transactional systems, and websites, as well as other external public sources. These tools then run algorithms to identify patterns and detect or predict threatening activity, potential data breaches, etc. This is a trend we can expect to continuously see in the future as criminals constantly create new malware and data acquisition methods.
3. AI for Personalised Services
As AI becomes more powerful and efficient at researching a particular market and demographic, acquiring consumer data is becoming more accessible than ever. The biggest AI trend in marketing is the increasing focus on providing personalised services. One of the most common ways that AI can do so is through analysing the online activity of individuals who search for specific keywords. This level of personalisation is virtually guaranteed to provide a better experience for customers, which will directly increase the revenue of companies that take advantage of it. As machine learning becomes more adept at understanding what people want in specific instances, AI will become less of a sales tool and more of a digital friend.
4. Automated AI Development
In coming years, expect to see significant innovations in the area of 'AI for AI': using AI to help automate the steps and processes involved in the life cycle of creating, deploying, managing, and operating AI models. At a certain level, AI can develop its algorithms to solve problems, increase efficiency, and provide humans with useful research data.
Using automated AI will allow even non-experts to use AI algorithms and techniques. One example is Google's AutoML, a tool that simplifies creating machine learning models and makes the technology accessible to a wider audience. These tools can create as much customisation as required without knowing the complex workflow of Machine Learning in detail. Although this type of development is in infancy, automated AI is renowned for growing exponentially and is a major AI trend.
5. Autonomous Vehicles
With companies like Samsung, Nvidia, Volkswagen, Uber, and Google's Waymo, the scope of autonomous driving has increased many folds. Everyone knows AI's functionality into autonomous vehicles, and to tap such immense potential, car, and tech companies are infusing billions of dollars in this domain. The process is driven by the economic and social benefits involved. Car manufacturers hope that autonomous driving technology will sway consumers' minds. Supporters believe that self-driving car technology will reduce traffic deaths and be a safe alternative to drive.
6. Incorporating Facial Recognition
Facial recognition appears to be en vogue at the moment. It is popping up in many aspects of our lives and is being adopted by private and public organisations for various purposes, including surveillance. More countries are readying themselves to incorporate facial recognition technology and enhance their security measures. Deep learning algorithms are being set to ensure that this technology goes beyond regular facial recognition and more understanding images and scenarios. It will also help provide more personalised communications to customers, making it a notable AI trend for coming years.
7. Convergence of IoT and AI
The lines between AI and IoT are increasingly blurring. While both technologies have independent qualities, used together, they are opening up better and more unique opportunities. The Internet of Things (IoT) devices create a lot of data that needs to be mined for actionable insights. On the other hand, Artificial Intelligence algorithms require the data before making any conclusions. So the data collected by IoT is being used by AI algorithms to create valuable results that are further implemented by the IoT devices. AI's ability to rapidly glean insights from data makes IoT systems more intelligent. In upcoming years more than 80% of enterprise IoT projects will incorporate AI in some form, up from just 10% today.
8. AI in Healthcare
The contributions that AI can import to the healthcare industry are working in groundbreaking ways, allowing people worldwide to receive safer and more efficient care and making it easier to detect, prevent, and cure diseases. Also, AI's ability to acquire data in real-time from electronic health records, emergency department admissions, equipment utilisation, staffing levels, etc. – and to interpret and analyse it in meaningful ways enables a wide range of efficiency and care-enhancing capabilities in hospital administration. Drug discoveries are another field where AI is acerbating.
AI is playing an essential role in helping healthcare professionals respond to the coronavirus (COVID-19) outbreak. AI is being used to distinguish COVID patients and essential hot spots. COVID vaccine drug discovery is being repurposed and speeded up using AI techniques. Researchers have developed AI-based thermal cameras and smartphone apps for estimating the temperature of people and assembling data for healthcare organisations. Intelligent robots are being deployed to implement "contactless delivery" for isolated individuals, helping medical staff ensure that the key areas stay disinfected and safe for use.
9. Augmented Intelligence
For those who may still be worried about AI cannibalising their jobs, the rise of AI should be a refreshing trend. It brings together the best capabilities of both humans and technology, giving organisations the ability to improve their workforce's efficiency and performance. By 2023, Gartner predicts that 40% of infrastructure and operations teams in large enterprises will use AI-augmented automation, resulting in higher productivity. The healthcare, retail, and travel industries have already created uses of Augmented Reality. Therefore, following this AI trend, there will be an increase in the number of augmented reality apps.
10. Explainable AI
Despite becoming so ubiquitous, AI has suffered from trust issues. Much of what machine learning accomplishes becomes unknowable at various points of the process and appears as a black box. It's often impossible to explain how the AI came to an inevitable conclusion. Explainable AI is designed to simplify and visualise how ML networks make decisions. There is a more significant push for deploying AI in a transparent and clearly defined manner. While companies will make efforts to understand how AI models and algorithms work? AI/ML software providers will make sophisticated ML solutions more explainable to users.
11. Ethical AI
Rising demand for ethical AI is at the top of the list of emerging technology trends. In the past, organisations that adopted Machine Learning and other Artificial Intelligence technologies were not much preoccupied with their ethical impact. Today, however, values-based consumers and employees expect companies to adopt AI responsibly. Over the next few years, firms will deliberately choose to do business with partners that commit to data ethics and adopt data handling practices that reflect their values and customers' values.
More than any other technological future trend, AI future trends promise many possibilities. There are compelling developments; you can't ignore the existence of intelligence demonstrated by machines. If you are excited to quick start or expand your business solution in the field of AI, the following technology offerings can be the right fit for you:
BeagleBone AI is one of the quickest vehicles to embedded AI at the edge. This super flexible and fast AI is the end product of multiple years' research in open hardware single-board Linux computers. You can use it to automate your shop floor, home, office, or lab. The BeagleBone AI draws its strength from the 1.5GHz, dual-core Cortex-A15 Texas Instruments Sitara AM5729 and embedded-vision-engine (EVE) neural processing cores with the AI capabilities of the SoC.
Avnet's Ultra96-V2 is an easy-to-use platform based on the integrated Dual-core Arm Cortex-R5F real-time, multiprocessing system with programmable logic Xilinx Zynq UltraScale+ MPSoC. This fine balance between performance and power is accomplished using programmable logic to accelerate the ML function.
The Raspberry Pi 4 Model B is the latest addition to the popular Raspberry Pi range of computers. It offers a significant increase in processor speed, rich multimedia performance, memory, and improved connectivity compared to its predecessor Raspberry Pi 3 Model B+, a better fit to run your AI models.
Arduino Portenta H7 - Program it with high-level languages and AI while performing low-latency operations on its customizable hardware. Portenta can easily run processes created with TensorFlow™ Lite, you could have one of the cores computing a computer vision algorithm on the fly, while the other could be making low-level operations like controlling a motor, or acting as a user interface.
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