Artificial Intelligence Trends That Will Dominate In 2022
In 2022, businesses will be using artificial intelligence (AI) in more innovative ways than ever before. Some of the most popular ways that AI will be used in businesses include: Chatbots will be used to communicate with customers. AI will be used to analyze data and make decisions. Robotics will be used to automate tasks. AI will be used to create new products and services. Virtual assistants will be used to manage tasks. AI will be used to improve customer service. Predictive analytics will be used to make decisions.
The following are some major AI trends to watch out for in 2022:
1. Augmented Reality (AR) – AR is being used to provide customers with enhanced visual experiences. It allows users to interact with digital objects using their smartphones.
2. Big Data Analytics – The big data analytics process involves the collection, storage, manipulation, analysis, and interpretation of massive sets of structured and unstructured data from diverse sources such as social media, mobile apps, wearable devices, IoT sensors, and other electronic systems.
3. Virtual and Mixed Reality – Virtual reality is an online environment which projects computer-generated imagery on a headset or glasses to create immersive user experiences. While mixed reality combines real world elements with virtual ones.
4. Human Performance Management (HPM) – HPM refers to the use of technology such as robots, cognitive computing, machine learning, and cloud computing to help employees perform better at work.
5. Cognitive Conversational Interfaces – Cognitive conversational interfaces (CCI) allow users to communicate with computers without using conventional input methods such as keyboards, mice, touch screens, etc. CCIs take the form of speech recognition assistants, chatbots, intelligent personal assistants, and other forms of advanced natural language processing.
6. Autonomous Vehicles – Autonomous vehicles are self-driving cars that do not require drivers’ supervision once they have been taken off the road. These vehicles can drive on highways and through city streets without assistance from a driver or any human behind the wheel.
7. Cybersecurity Solutions – Cybersecurity solutions are designed to prevent cybercrime and ensure that sensitive data remains secure. They also protect organizations against malicious attacks.
8. Internet of Things (IoT) Connectivity – IoT connectivity enables smart homes, smart cities, connected vehicles, industrial automation, and smart buildings to exchange information among each other.
9. Smart Cities – As per the report by McKinsey, there were 2.9 billion people living in urban areas around the globe in 2014, compared to 1.6 billion in 2004. By 2030, this number is projected to grow to 3.1 billion. These people generate more than 70 percent of all greenhouse gas emissions and over 80 percent of global water usage. As a result, smart cities produce a solution—smart technologies that utilize the internet to provide citizens with quality services while reducing their dependence on traditional energy sources.
10. Artificial Intelligence Market Forecast by Solution Type: – Software & Services: Software and services segment accounted for USD 3.06 billion in 2016 and is forecasted to rise to USD 4.48 billion in 2022, growing at a CAGR of 5.6% during the forecast period. In 2016, the market was dominated by the adoption of AI tools in customer support applications, email spam filtering, fraud detection systems, and image classification. However, the software segment accounted for a larger share of the market owing to its broad application scope across different sectors.
The term hyper automation refers to the automation of processes that were once performed manually. For example, if you had to manually type out all your emails, then this would be considered hyper automation. As we move into the future, it is predicted that many jobs will be replaced by machines. It’s important to understand what types of jobs could potentially be automated so that you can prepare yourself for the future.
According to a recent report published by Oxford Economics, 47 percent of total employment growth from 2011-2021 will be created by new jobs related to robotics, artificial intelligence, and machine learning. This means half of the job growth in the coming decade will be created by these three-emerging tech-related fields. In fact, the Boston Consulting Group states that more than 50 percent of current manufacturing positions will be eliminated within 15-25 years if no action is taken. This means that the jobs that are currently held by humans won’t exist much longer.
As technology continues to evolve, many jobs will eventually be lost. While some of these losses may not affect you directly, it is critical to stay informed about where our society is heading to ensure that you have the skills necessary to find new opportunities as well as adapt to any future changes. It’s clear that the use of technology has become an essential part of our lives. We have gone through multiple generations of computers, smartphones, tablets, apps, and more, but each step forward brings with it the challenge of figuring out which one should be used.
One thing is for sure: we live in a digital world now. From social media platforms like Facebook and Twitter, to ecommerce websites such as Amazon or Etsy, to online games like Candy Crush Saga, we are constantly using devices that process data digitally. When talking about “artificial intelligence,” most people think of robots. But while robots are certainly becoming smarter every day, they don’t embody true artificial intelligence yet. We still rely on them quite heavily today, particularly when it comes to doing menial tasks. However, the field of artificial intelligence is continuing to advance rapidly.
The future of AI is quantum computing. While we don’t know exactly what this means yet, it could mean that computers will be able to perform tasks at speeds far beyond our current capabilities.
We already see evidence of this kind of technology today. Google Deepmind developed AlphaGo, which beat human Go champion Lee Sedol straight down the middle. IBM Watson came close to beating Jeopardy! champions Ken Jennings and Brad Rutter recently.
At present, there is not enough hardware available to create a fully functioning quantum computer. However, advancements are being made regularly. Quantum computing experts predict that we’ll soon have quantum computers powerful enough to simulate problems that even the best classical supercomputers couldn’t solve. By 2027, IBM predicts that quantum computers will be as fast as our own brains. If IBM’s prediction proves accurate, quantum computing will change the way we approach issues. It could allow us to understand complex systems better. For example, it might give scientists insight into how diseases work, improve drug discovery, and help us understand financial markets.
The Future of Artificial Intelligence in the Workplace
Artificial intelligence isn’t going anywhere anytime soon. While the future looks bright, the number of jobs that could potentially be lost soon is staggering. According to reports, 1.8 million workers will lose their jobs to automation by 2020. And over 10% of current occupations could vanish altogether.
Therefore, it’s so important to stay up to date with the latest developments in the AI field. Your skill set needs to be flexible enough to accommodate the changing landscape. You must also embrace emerging technologies quickly, or you risk falling behind your competitors.
But with all these modern technologies on the horizon, it can get overwhelming trying to keep track of everything.
1. Data Management – To use AI effectively, organizations need to ensure that they collect, store, analyze, and share relevant data efficiently.
2. Natural Language Processing – This includes tools used to interpret written text and spoken language. There will be an increased demand for natural language processing skills, including those related to speech recognition.
3. Machine Learning – The ability to teach machines new skills is called machine learning. As more companies implement AI, there’s a good chance that you’ll encounter more programs that require machine learning skills.
4. Cognitive Computing – This refers to applications designed specifically for humans. Cognitive computing often involves reasoning, memory, problem-solving, planning, decision-making, and creativity. Examples of cognitive computing include Siri, Cortana, Alexa, and other similar apps on smartphones.
5. Augmented Reality – This refers to virtual digital experiences that augment real-world scenarios. This includes games, mobile apps, movies, television shows, and advertisements.
6. Robotics. Robots are increasingly becoming more commonplace in every industry. Companies like Amazon, FedEx, General Motors, and Walmart are investing heavily in robotics and autonomous vehicles. It’s estimated that robots will account for 40% of employment within the next decade.
7. Cybersecurity – Advanced cyber-attacks and threats continue to grow rapidly. To protect against them, organizations should develop cybersecurity strategies and establish policies to prevent malicious hacking activity.
8. Automation – Machines are already replacing many human jobs and processes today. Technologies such as automated inventory management, software development, and customer service have been widely adopted. By 2035, it’s predicted that approximately 35% of U.S. jobs may be replaced by automation.
9. Biometrics –This refers to individual characteristics or traits that are unique to each person. Biometric information includes things like fingerprints, eye scans, voice patterns, hand geometry, iris scans, and even signatures.
10. Humanoid Robots – They look like humans and perform tasks just like people do. Some examples include the Sony Alpha Robot and Jibo.
11. Quantum Computers – This is a hypothetical type of computer that uses tiny amounts of energy and potentially superposition states to run algorithms much faster than traditional computers. IBM has developed quantum computing hardware.
12. 3D Printing – 3D printing is one area where we see rapid growth potential in the coming years. Companies like Consumer Physics show how this technology could be used to create working devices, cars, and houses.
13. Nanotechnology – Nanoscience deals with objects that are constructed from atoms and molecules so tiny that they appear invisible. One day, nanoparticles might help diagnose diseases, detect impurities, control pollution, and build stronger materials.
14. Wearables – Wearable tech monitors health metrics such as heart rate, breathing, stress levels, and sleep cycles. If connected to the Internet, it can communicate results to your doctor or coach.
15. Brain Computer Interfaces – We use our brains to send messages to electronic devices through BCIs. For example, you would think “I wish to go home” instead of typing out the words using an onscreen keyboard. Or when you want your phone to ring, you imagine a visual image of a telephone ringing.
16. Gene Sequencing – Your genes tell your body which body functions it needs to function properly. Scientists are developing advanced technologies to sequence ever longer strands of DNA. Eventually, scientists foresee having complete human genome sequences from inception to death.
17. Virtual Reality – The term VR implies the experience of reality. This technology creates realistic images of places or scenes that the viewer does not actually visit. This gives rise to entertainment, gaming, education, and training opportunities.
18. Augmented Reality – AR enhances what we see with digital information overlaid on top of our physical world. In other words, it brings the virtual into our real lives
19. Autonomous Vehicles – AVs are fully autonomous vehicles without human passengers. Uber is among companies currently testing these new types of self-driving cars. Other applications include delivery vehicles, police patrol, fire trucks, and mail/package delivery vehicles.
20. Real Estate – Property records keep track of who owns what property. That data is available online, increasing transparency between buyers and sellers.
The Domain of Creativity In AI
The most common way to implement AI in creative fields is through machine vision systems. These systems analyze images and videos to identify objects, people, and scenes. They then provide suggestions to artists based on what they see. For example, if an artist sees a picture of a dog, the system might suggest that he draw a dog. If the artist has never drawn dogs before, it may take some practice to produce a convincing result. However, once the artist gets the hang of drawing a dog, his artwork should look much better than it did when he first started out.
Another area of creativity that is seeing increasing interest in AI is generative art. Through generative art, machines create something completely novel that looks like a human-made creation but isn’t. To do this, the machine must begin with a basic structure (e.g., a box shape), then add details that make it unique (e.g., leaves). It does this by iteratively sampling random values to determine where to place elements on the canvas. Generative art is often very impressive because it requires artistic skills combined with a strong understanding of statistics and probability. Some popular generative art programs include: * Adobe Illustrator uses a Markov chain model to sample shapes and colors from an original image. PaintCode uses a particle system to simulate paint strokes. Blender uses a combination of physical simulation and sampling to create 3D models.
In the early days of AI research, the field focused more on problem-solving (i.e., solving practical problems). Today, researchers also focus on creativity. Why? Because some issues are too complex for computers to solve effectively. Instead, we need to rely on intuition, inspiration, and imagination—all areas better suited to human ingenuity.
Creativity is a broad concept. According to MIT’s definition, creativity involves:
1. Generating ideas
2. Exploring those ideas
3. Expressing those ideas
4. Sharing and collaborating
When we talk about AI, we typically refer to automated machines. However, AI encompasses all forms of technology. So, we should include creativity within the scope of AI—because automation alone doesn’t produce originality.
Here are three ways that AI can enhance creativity:
1. AI in healthcare – Healthcare systems suffer from shortages of doctors and nurses, long wait times, poor communication, inconsistent quality care, and overuse of services. Using AI, medical teams could help prevent problems before they arise, provide better diagnosis, make accurate predictions, and improve treatment effectiveness.
2. Optimization – An algorithm finds optimal solutions to existing concerns. This approach was behind Google’s DeepMind beating the world champion at Go.
3. Synthesis – Human designers combine elements of various concepts to create something entirely new.
AI will continue to improve over time. Within a decade, AI may surpass human performance. But even if it never achieves human-level intelligence, it will still be able to tackle some extremely hard issues.
Cancer Research using Artificial Intelligence is being used to help identify cancer biomarkers, especially in lung cancer. By analyzing molecular structures, AI can quickly analyze hundreds of thousands of molecules in a short amount of time. Once these molecules are analyzed, they are compared to previous research studies to discover commonalities. This helps biologists gain insight into how tumors form and spread. As a result, they can design treatments that target cancer biomarkers.
We can use AI to detect cancerous cells when they appear in blood samples. AI analyzes blood samples from patients, looking for patterns associated with cancer. If AI detects signs of cancer, then doctors can perform further tests. With proper treatment, cancer can be cured up to 70 percent of the time. Without AI, physicians could miss the detection of cancer in blood samples because the disease is so rare. Artificial Intelligence will soon be able to help doctors diagnose diseases like diabetes. Diabetes can cause blurry vision, leg pain, fatigue, and infections. Most people don’t realize that diabetes causes over four hundred deaths each day.
One reason AI is useful in healthcare is because it can predict future health outcomes. Predictive analytics can make predictions based on past data. These algorithms can be programmed to look for trends and patterns. When combined with other technologies, such as cloud computing and wearable devices, predictive analytics allows doctors to monitor their patients remotely. As AI improves, doctors will be able to develop new methods to prevent disease. Doctors already use AI to track heart conditions. The goal is to prevent heart attacks by identifying risk factors before patients experience symptoms. In addition, AI can be used to screen diabetes, hypertension, high cholesterol, kidney disease, obesity, sleep apnea, pregnancy, and depression.
Using AI for Advertising
As artificial intelligence (AI) continues to evolve, businesses are increasingly looking to use it for advertising purposes. AI can help identify and target potential customers with greater precision and accuracy than traditional advertising methods. Additionally, AI can help businesses learn more about their customers’ preferences and behaviors, which can lead to better marketing strategies. While there are some concerns about the use of AI in advertising (such as privacy concerns and the potential for AI to be used to manipulate people’s opinions), the potential benefits of using AI for advertising are vast.
For example, a company called DeepMind, an AI startup backed by Google parent Alphabet Inc., uses AI techniques to provide automated video captioning services. Its AI system automatically generates captions for videos taken at sporting events. According to DeepMind cofounder Mustafa Suleyman, “this is the first time ever we’ve brought together machine learning, natural language processing, and computer vision to produce an excellent product.”
AI can also help companies understand what users want and need by analyzing online content. Some examples include:
Understanding user behavior through tracking: Companies can use AI to see where visitors spend most of their time on websites within a certain timeframe. They can then use the information to determine whether changes should be made to improve website performance. By understanding how users interact with a website, companies can increase engagement rates, generate leads, and drive sales.
Optimizing site search results: A variety of technologies, including AI, can be used to optimize sites for search engine listings. For instance, a tool called RankBrain was developed by Google. It works by examining millions of web pages and using those pages to train itself. As a result, RankBrain can identify text written within a page, even if the text isn’t part of any search query. This makes RankBrain ideal for optimizing both general and specialized searches. Another tool, Watson, is being used by Microsoft Bing to analyze images posted on social media platforms. This is especially important for small businesses because they don’t necessarily have the resources to hire full-time employees to monitor these platforms.
Personalization: Many websites offer personalized features such as news feeds and recommendations based on past browsing activity. This personalization is generated by reading each visitor’s profile data, including interests, demographics, and location. AI can make this personalization far more accurate and relevant to individual users’ needs.
AI for Workforce Augmentation
According to a study by PwC, workforce augmentation will be the key to success for companies in the artificial intelligence (AI) era. The study found that AI will enable organizations to increase their productivity by up to 38 percent. As a result, companies will need to invest in training and reskilling their employees to leverage the full potential of AI. The study also found that AI will create over 2 million jobs in the next five years. However, many of these jobs will be in new, previously unknown fields. Organizations will need to be proactive in identifying the new skill sets required for these jobs and in reskilling their employees.
The report identified four major categories of AI applications that could revolutionize business processes. These categories were:
- Process automation
- Data analytics
- Product customization
- Human-like conversational agents
The top three types of activities that organizations can automate with AI technology are:
- Document management
- Customer service/chatbots
- Sales forecasting
To date, there has been quick progress in automating routine human tasks. However, many professionals in healthcare, finance, law, education, and other industries lack experience with AI tools. To address this gap, many companies are partnering with universities and research institutions to develop AI programs that focus on specific areas of expertise. For example, Stanford University recently announced plans to begin offering graduate degrees in artificial intelligence.
There are several methods to apply AI to workforce augmentation. One approach is to automate existing manual tasks. For example, an organization may choose to replace its traditional call center with a chatbot that offers customer support. Another option would be to provide a self-service feature within an e-commerce platform where customers can request certain products without requiring assistance from sales staff.
Another way to automate workforce augmentation is by applying AI to build new knowledge into existing systems. For example, a team at MIT created a chatbot that helps students manage coursework assignments. By incorporating AI into student assessment systems, the researchers were able to reduce workloads, ensure consistency across classes, and minimize errors.
As AI becomes more powerful, it will also become easier for both individuals and businesses to incorporate AI into every aspect of their daily lives. There have already been numerous examples of how AI is being applied to various aspects of society. For instance, millions of people currently use Facebook’s automatic photo captioning tool to generate captions for uploaded images. In addition, Google DeepMind developed an application called AlphaGo that was designed to play Go matches against professional players. Google DeepMind used AI to learn how to analyze game patterns and react accordingly. With continued development, everyday people could eventually use these kinds of applications to simplify common tasks such as writing a resume or preparing a presentation.
The rise of AI means that we’ll see a greater focus on personalized content. For example, if you search for the ‘best hotels in London’, you’ll receive a list of results based on what you’ve searched for before. But if you ask Google to recommend a hotel for you, it might suggest one based on your location, interests, and previous searches. This type of personalization is only possible because of advanced algorithms that crunch enormous amounts of information. Because of this, personalized content will become more common over time.
Businesses will also benefit from increased personalization. If you want to reach someone at a certain company, you could write them a message using the email address associated with their LinkedIn profile. Or you could tweet a question to @ on Twitter. These methods may reach your target audience, but not necessarily the right person. AI enables organizations to automate this process, which makes it easier to get responses from people who matter most within an organization.
AI is for big data analysis. Big data refers to massive sets of data that are too large or complex for traditional database management systems. Data mining allows companies to analyze huge volumes of data to identify patterns or trends that can lead to insights for better decision-making. In addition to helping companies make decisions, the ability to mine data for meaningful insights helps them build strong customer relationships. AI has been used to predict customer behavior and preferences. Companies like Netflix have used data analytics to determine what movies customers will enjoy watching next. And Amazon uses predictive algorithms to create recommendations of products that shoppers might purchase. With AI, businesses can learn about their clients’ buying habits and find out their likes and dislikes.
AI is for deep learning. Deep learning is the practice of using artificial neural networks (ANNs) to train computers to recognize images, sounds, text, etc., so they can accomplish tasks without being explicitly programmed. ANNs were first developed in the 1950s, but after decades of research and development, they continue to evolve. Today, AI is revolutionizing healthcare. As we mentioned in our earlier paragraph, it can identify objects in photos, recognize spoken words, translate speech into text, determine where a photo was taken, and even detect skin cancer. In 2017 alone, researchers published papers describing advances in AI that range from self-driving cars to facial recognition software that identifies criminals. We can expect this trend to accelerate as researchers develop new tools and techniques for integrating AI into everyday life.
Natural Language Processing (NLP) is essential when dealing with human language. It involves analyzing the structure of written or spoken natural language to discover meaning. NLP is sometimes confused with machine translation, which attempts to convert one language into another, but there’s a key difference between the two: Machine translation produces a literal rendering of the source language while NLP requires contextually relevant output.
NLP is widely used in business applications to process unstructured data. Ecommerce sites such as AliExpress and eBay provide Real-time NLP services that enable users to complete transactions with ease. Similarly, healthcare providers can use NLP to detect medical conditions in patients’ records.
NLP is also used extensively in chatbots and smart assistants. Siri, Alexa, Cortana, and other virtual assistants use NLP to interact with humans. Chatbot technology has been around since the 1970s, but only recently have advancements in computational power made it possible to deploy sophisticated chatbots that are personalized for each customer.
Artificial Intelligence of Things AIoT will lay its Roots
The IoT market has grown from $1 trillion in 2016 to $20 trillion by 2020. In addition to this, it is estimated that the number of connected devices will grow from 50 billion in 2016 to 20 billion in 2020. As a result of this growth, the demand for AI solutions will rise exponentially. According to Gartner, the top three use cases for AI include increasing efficiency in operations, improving performance and reducing costs. For example, a business may use AI to analyze raw data and then use this information to make decisions regarding product supply and pricing strategies. This would allow companies to increase profit margins while providing better service to customers. Another area where AI is being implemented is cloud computing. Today, many AI-based application models rely on a serverless architecture. Cloud-enabled servers can support multiple workloads with minimal resource requirements. In addition to cloud computing, AI is also being employed to optimize data centers and network infrastructure. At present, we see an increased interest in AI-driven edge processing due to cost considerations. Edge computing refers to deploying computing resources at the point of collection or generation. This reduces latency and improves user experience.
In summary, AI is not just about building intelligent machines and replacing people. Rather, it is about harnessing the potential of artificial intelligence to solve real world problems using existing technologies like sensors, cameras, and computers. Over the next few years, we will see a lot of diverse types of artificial intelligence emerge. Some will require enormous amounts of time and money to build, while others will come online instantly. Regardless of the type of AI, these innovations will change how we live and work forever.
AI Investment is Skyrocketing
The market is growing at a rate of 20% per year, and it has already surpassed venture capital funding levels. Companies like Google, Facebook, Amazon, Microsoft, and IBM have all made significant investments in AI development. Other players in the industry are also investing heavily: Apple, Samsung, Tencent, Huawei, Baidu, Alibaba, JD.com, and Xiaomi are among those who have invested over $2 billion in AI research. Although some individuals claim they don’t need any AI tech right now, the truth is that every company needs to start developing their own AI solutions. There are two main reasons why you should invest in AI today: It will become essential to your products and services within five years. You must keep up with the advances in the field if you want to stay relevant.
What does this mean? If you’re a marketing professional, there’s no doubt that you’ll be seeing increased brands incorporating Artificial Intelligence into their advertising campaigns. From targeting specific audiences based on location to understanding what consumers are saying about certain products, AI technology allows marketers to create highly personalized digital experiences. But even if you aren’t a marketer, chances are you still interact with brands through social media channels, emails, websites, and other forms of content creation. And as more content gets created around AI, there will undoubtedly be more opportunities for you to engage with distinct brands and promote their messaging.
Trend Exploring AI and Web
The report states that the market size for AI and web applications is expected to grow at a CAGR of 22% from 2018 to 2022. The growth of this market is driven by factors such as increasing adoption of AI and web technologies across different verticals, growing demand for cloud computing services, and rising investments in R&D activities. These trends indicate that organizations are adopting new ways of doing things to achieve operational efficiencies. They are also leveraging software-as-a-service (SaaS) and platform-as-a-services (PaaS) to automate and streamline key functions of their IT systems.
These initiatives help enterprises to reduce costs and enhance security by enabling faster access to enterprise data. Moreover, these initiatives help organizations adopt SaaS and PaaS effectively so that they can manage their entire IT infrastructure. To further help them drive digital transformation, they are integrating AI and web technologies into their current practices.
As discussed earlier, one of the major driving forces behind the AI and web apps market is the increased adoption of AI and web technology across various industries. Organizations are embracing AI and the web to automate their business processes and make smarter decisions. For instance, SAP, an international provider of enterprise software solutions, implemented its AI-based customer service analytics solution to deliver a better customer experience. This solution helps customers receive a response within 30 minutes of receiving a request, compared to the average time of 8 hours. This initiative helped the company save 16 million man-hours each month and reduced the number of telephone calls by 60%. It also generated revenue and profit for the company. The solution was tested by 50,000 callers and received positive feedback.
As another example, Accenture used AI and web technology to provide customized recommendations to clients. Their recommendation engine analyzed millions of data points related to client’s interactions with Accenture and then provided insights to the clients. In addition, many companies have started offering AI-powered chatbots to assist customers. For example, Amazon uses an AI-enabled chatbot to answer shared questions like “Where should I buy my holiday gifts?” Amazon has trained its bots to understand user intent and respond accordingly. Users simply need to ask and get the right information back in return.
Augmented Data Analytics Using AI
Augmented data analytics is the process of augmenting the data analytics process with artificial intelligence to improve the accuracy and efficiency of the overall process. Augmented data analytics is a new field, but it has already shown a great deal of promise in terms of its ability to improve the accuracy and efficiency of data analytics. AI-based tools help analysts generate models without having to write all the code themselves. In fact, there are now so many available AI tools that it is becoming easier than ever before to combine several types of data sources and create actionable insights.
AI tools can even reduce analyst workload by taking over some basic analytical steps, such as feature extraction and model building. Once built, these models can then be deployed into production environments quickly and easily because they are highly flexible and scalable. For instance, IBM Watson Health provides health diagnostic and treatment advice to doctors at hospitals through its suite of applications. Watson Health analyzes patient records to identify symptoms and recommends treatments based on clinical evidence. In 2017, Watson Health’s app gained FDA clearance to diagnose pneumonia, skin infections, urinary tract infection, and sinusitis. Moreover, IBM has developed a system called Watson Text Analytics Platform that helps users analyze text documents. It can read the content of emails, news articles, web pages, social media posts, and plain text files, understand what it reads, and answer queries about that information. For example, in 2016, Watson Text Analytics was used to assist law enforcement agencies in solving cases involving missing persons. They examined millions of pages of public record requests, court filings, police reports, newspapers, and other online databases to search for clues. The platform successfully identified the location of one of the missing people and returned relevant information in just 24 hours.
Other examples include:
An Artificial Intelligence tool, called DeepMaster, from EMC Corporation, uses AI algorithms to help IT professionals troubleshoot issues related to server failures. The DeepMaster application monitors servers running Windows Server 2008 R2 operating systems and learns how to interpret and react when something goes wrong. It then creates alerts, recommends fixes, and notifies admins when an issue needs attention.
The future of AI is bright, but it’s important to understand what we don’t know yet. There are still many unanswered questions regarding the impact of AI on society and our environment. Some questions you should ask are:
Where do you fit in when it comes to AI?
To understand where you fall in terms of the role of AI, consider the following questions:
- Do you currently utilize AI or plan to implement AI soon?
- Are you part of a team that uses AI to drive decision-making?
- Do you find yourself managing the output of AI systems?
- Are you responsible for implementing AI features in new products or services?
If you answered “yes” to any of the above questions, you need to take a step back and evaluate whether the role of an AI engineer is something you would enjoy doing. On the other hand, if you were consistently answering “no”, then you might benefit from exploring how AI could potentially impact the roles you play. As AI becomes increasingly integrated into our lives, it’s essential that we continue to ask tough questions about its potential impacts and ensure that they are well understood before we allow it to affect us.