What AI actually is

Artificial intelligence (AI) has gained significant interest in various sectors, with even Oprah Winfrey hosting a TV special on the subject, indicating its widespread impact and relevance in today’s world.

AI has become ubiquitous, influencing our lives in different capacities, whether through usage, development, governance, or interaction.

While the technical intricacies of AI may not be essential for most individuals, understanding its capabilities and implications is becoming increasingly crucial.

Through discussions with leaders in business, government, and the arts, a notable observation is the necessity for genuine AI fluency, highlighting the significance of comprehending AI’s functionalities.

AI surpasses mere chatbot applications. To elucidate its essence, a framework termed the “capabilities stack” has been devised to elucidate the diverse range of functionalities AI offers.

AI systems are categorized into seven fundamental capabilities, each building upon the preceding ones in the stack, including recognition, classification, prediction, recommendation, automation, generation, and interaction.

Recognition

At its core, contemporary AI in consumer products focuses on identifying patterns from extensive datasets, enabling the system to perform tasks based on learned patterns rather than explicit programming.

Pattern recognition finds practical application in various scenarios, such as facial recognition in phones and security systems, quality control in manufacturing, and healthcare diagnostics in medical imaging.

Classification

Following pattern recognition, AI systems can be trained to detect and categorize subtle variations, as seen in features like photo organization in apps and spam detection in communication services.

Noteworthy applications include the use of AI to classify extensive audio recordings for language preservation efforts, exemplified by Te Hiku’s project in New Zealand for revitalizing Te Reo Māori.

Prediction

AI’s predictive capabilities leverage historical data to anticipate future outcomes, as demonstrated by its applications in flight scheduling, budget forecasting, and demand prediction in e-commerce.

For instance, airlines utilize AI to predict flight delays, whereas Amazon optimizes delivery routes through predictive analytics to enhance service efficiency.

Recommendation

Based on predictive insights, AI systems offer recommendations for optimal actions, shaping user experiences across various domains such as event safety, social media engagement, and personalized content delivery.

Recommendation systems powered by AI are instrumental in enhancing safety measures, content personalization, and product suggestions tailored to user preferences.

Automation

Transitioning from prediction and recommendation, automation plays a pivotal role in AI applications, exemplified by instances like wildlife protection, energy management, and public transport optimization.

Automated systems driven by AI technology contribute to diverse sectors, from wildlife conservation to energy efficiency and urban transportation management.

Generation

Encapsulating the ability to create new patterns based on existing data, AI generation capabilities extend to various media types, including images, texts, and videos, with implications for creative content generation and data synthesis.

Tools like Runway and ElevenLabs enable users to generate diverse content formats, although concerns like deepfake implications underscore the dual nature of such advancements.

Interaction

Advancements in generative AI enable human-like interactions through virtual assistants, digital companions, and interactive bots, reshaping diverse sectors such as customer service, entertainment, and social media engagement.

Interactive AI technologies are paving the way for immersive user experiences, ranging from virtual assistants aiding in productivity tasks to digital companions offering entertainment and assistance in various contexts.

It is essential to recognize that AI encompasses more than conversational interfaces, with its impact extending beyond surface-level applications to significantly enhance various aspects of everyday processes.

Sandra Peter, Director of Sydney Executive Plus, University of Sydney and Kai Riemer, Professor of Information Technology and Organisation, University of Sydney

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Source: MyBroadband