When I am bored, I, like many others, turn to Siri and ask, “Hey Siri, what is the weather like today?”, “Hey Siri, tell me a joke,” “Hey Siri, what is 1210 x 1220?,” or “Hey Siri, are you sure you are not going to take over the world?”
Virtual assistants like Siri and Alexa have become a normal aspect of our lives. Both are examples of Artificial Intelligence (AI) driven technology, which provide voice-activated services including setting reminders, answering questions, and controlling smart home devices.
Although the emergence of AI may seem recent with the introduction of Chat Generative Pre-trained Transformer (ChatGPT) — a large language model-based AI chatbot developed by OpenAI capable of creating humanlike conversational dialogue — and its ability to create videos, images, and to change voices, AI’s development has been in the works since the dawn of computers. Alan Turing — who is known as the father of modern computers — imagined a future where machines could think and learn, and in his 1950 paper Computing Machinery and Intelligence, Turing was interested in the question of whether machines can think. We can think of this part of Turing’s work as the first step of the AI journey. Additionally, John McCarthy-one of the founding fathers of AI, believed that it is the science and engineering of making intelligent machines, however he believed that AI does not have to confine itself to methods that are biologically observable.
So, what exactly is AI?
At its core, AI refers to the development of computer systems capable of performing tasks that typically require human intelligence. These tasks encompass a wide range of activities, from understanding natural language and recognizing patterns in data, to making decisions and learning from experience. The significance of AI in the modern world cannot be overstated. It has become an integral part of our daily lives, revolutionizing numerous industries and sectors.
AI has made significant strides in Natural Language Processing (NLP). Chatbots, like those essential in customer service, are powered by AI, allowing them to understand and respond to human language. Sentiment analysis is used to gauge public opinion, with applications in social media monitoring and market research. Translation services, like Google Translate, employ AI for real-time language translation. Text summarization tools, such as GPT-based models, can automatically generate concise summaries of lengthy documents. AI-based personal assistants like Siri, Alexa, and Google Home also use NLP to understand and respond to spoken language.
Subsequently, AI-driven image recognition is widely used in fields like healthcare for diagnosing medical images (such as X-rays and MRIs). In e-commerce, AI is employed for visual search, enabling users to find products by uploading images on the internet. Content moderation on social media platforms relies on AI to identify and remove inappropriate content. Self-driving cars, developed by companies like Tesla and Waymo utilize AI to navigate and make real-time decisions on the road, enhancing safety and convenience. Drones equipped with AI can be used for surveillance, agriculture, and rescue missions. It is also used in autonomous drones and underwater vehicles for environmental monitoring, exploring remote areas, and underwater research.
AI algorithms are responsible for our media preferences, as they are used to enhance online streaming networks such as Netflix, who employ AI algorithms to suggest movies and TV shows based on a user’s viewing history. Amazon uses recommendation systems to suggest products to customers based on their purchase history and browsing behavior. Spotify uses AI to curate personalized music based on a user’s listening habits. Even in manufacturing, AI has become essential, as AI-powered systems can perform real-time quality control by detecting defects in products. They make necessary adjustments which ensure better quality of the products. AI-driven predictive analytics help businesses forecast demand, manage inventory more effectively, and improve resource allocation, resulting in increased profitability.
In the medical field, AI could be used to increase efficiency in healthcare diagnoses. AI-powered predictive models analyze patient data and can identify patterns that may indicate the onset of diseases, allowing for earlier intervention and prevention. A published study in the leading cancer journal, Annals of Oncology, found that AI recognized skin cancer better than experienced doctors. American, German, and French researchers used deep learning on more than 100,000 images to identify skin cancer. Comparing the results of AI to those of 58 international dermatologists, they found AI did better. Furthermore, the drug discovery process is time-consuming and labor-intensive. It spans many steps, from target identification to clinical trials. AI has the potential to streamline the drug discovery process, reduce the time and costs involved, and lead to more effective and efficient treatments.
AI has developed considerably over the past few decades and is now capable of things that would have been thought possible only in a fictional dystopian world. However, we are still far from the developed stage of AI, so what we possess today is nothing close to the final product.
