What Is Artificial Intelligence and Why It Matters?
Artificial Intelligence or AI is what facilitates machines to learn from experiences, adapt to new inputs, and carry out tasks just like humans. From computers playing chess to self-driving cars, all are the most common examples of AI in our everyday lives, and these depend on deep learning and natural language processing massively. We can train computers using these technologies to perform specific tasks via data processing and pattern recognition successfully.
The History of Artificial Intelligence
The term ‘Artificial Intelligence’ originated back in 1956, but it has become more popular now than ever, and the credit goes to increased volumes of data, advanced algorithms, and upgrades in computing power and data storage.
In the 1950s, the initial AI research analyzed subjects such as symbolic methods and problem-solving. During the 1960s, the United States Department of Defense liked this idea and started training computers to imitate basic human reasoning. And in 2003, the Defense Advanced Research Projects Agency (DARPA) created smart personal assistants long before Cortana, Siri, or Alexa became a thing.
Now, this early work set the scene for automation and formal reasoning that we see in the modern-day computers, including DSS (decision support systems) and intelligent search systems to enhance and elevate human capabilities.
While sci-fi movies and novels often portray artificial intelligence as human-like robots taking over the world, in reality, the current development of AI technologies is not that terrifying or smart, yet. Sure, AI has grown to provide a lot of benefits to almost every industry, including healthcare, finance, marketing, retail, and so on.
Importance of Artificial Intelligence
- Artificial intelligence automates repetitive learning and discovery by using data, but it’s nothing like hardware-driven robotic automation. Rather than automating manual tasks, AI carries out continuous, high-volume, and computerized chores accurately, without wearing out. However, for this kind of automation, human analysis still plays a crucial role in preparing the system and asking the correct questions.
- AI augments brilliance and perception to existing products. Mostly, AI isn’t sold as a separate application. Instead, the products that we already use are enhanced with AI powers, just like Siri was integrated into the new generation of Apple products as a feature. Automation, smart machines, robots, and communication platforms can be merged with large volumes of data to enhance numerous technologies at homes and offices, from security intelligence to financial analysis.
- AI adjusts using advanced learning algorithms to allow the data to carry out programming. AI processes data to identify patterns and regularities so that the algorithm gains a skill. So now, the algorithm either becomes a classifier or a predictor. Therefore, just like the algorithm can educate itself to play chess, it can also educate itself on what product recommendation to give next online, and adjust to new data.
- AI examines more and in-depth data through semantic networks containing numerous hidden layers. Developing a fraud detection software that has five hidden layers was next to impossible just a couple of years ago. But with this unbelievable computer power and big data, all these are a thing of the past now. Deep learning models learn from data directly; therefore, you will need large amounts of data to train them. The more data you feed it, the more error-free it will become.
- AI attains unbelievable accuracy using deep neural networks – which was almost impossible earlier. For instance, our communications with Alexa or Siri, Google search, Google Photos, etc. all of them are based on deep learning. The more we use them, the more accurate they become. In the healthcare sector, cancer can be detected on MRIs just as accurately as an expert radiologist, using deep learning techniques such as image classification and object recognition.
- AI takes full advantage of data. With self-learning algorithms, it is logical to say the data is intellectual property. The answers are present in the data; all you need is to implement AI to extract them. Since the data is now more important than ever, this can lead to a competitive advantage. If you possess the best data and even if every other competitor is employing the same techniques as you, ultimately, the best data is going to win.
How Is Artificial Intelligence Being Used Today?
AI is a game-changing asset for every company and sector. Almost every industry is experiencing a surge in demand for AI capabilities, especially QA (question answering) systems that can be implemented for assistance. Other uses of AI are as follows:
- Healthcare
AI software can give personalized X-ray readings and medicine. Moreover, healthcare assistants can be personal life coaches reminding us to take our medications on time, exercise, eat healthily, go for a walk, etc.
- Retail
AI facilitates online shopping in virtual stores. They can offer personalized suggestions and discuss buying options with the customer. AI will also help in improving stock management and website layout technologies.
- Manufacturing
With the adoption of AI, companies are able to make prompt data-driven decisions. They are able to minimize their operational costs, optimize their manufacturing processes, and improve their ways of serving the consumers.
- Banking
AI improves the speed, accuracy, and success of human efforts. Financial institutions can use AI techniques to find out which transactions are most probably deceitful, acquire precise credit scores faster, and automate data management tasks that consume a lot of time and effort when done manually.
Challenges of Using Artificial Intelligence
There is no doubt that the adoption of artificial intelligence will be a turning point for every industry, but we need to realize its limits.
The main restriction of artificial intelligence is that it learns from data, and there’s no other alternative to incorporating knowledge. Meaning, any errors in the data will show in the results. And any extra layers of evaluation or prediction will have to be integrated individually.
The modern-day AI systems are designed to perform a specific task. A system that plays chess cannot play poker or solitaire. A system that gives you legal advice cannot drive your car. Even a system that detects healthcare fraud cannot detect a tax fraud precisely.
In a nutshell, these AI systems are very specialized and trained to carry out clearly defined tasks.
Conclusion
Today’s AI systems focus on performing the task they specialize in, that means they are far, far away from behaving like humans.
Similarly, they are self-learning systems, not self-governing systems. The AI technologies that we see in Hollywood movies and shows are nothing but science fiction meant for entertainment. We need to separate hype from reality.
Although computers that can analyze complex data for learning and accomplishing certain tasks are becoming increasingly common across various industries.
In essence, the goal of AI is to enhance human capabilities. It will provide human-like interactions with AI-based software and offer support in making data-driven decisions for certain tasks, but it is not at all a replacement for humans and won’t be in the near future.