From Image Recognition to Chatbots and Beyond
Artificial Intelligence (AI) has transitioned from a futuristic concept to a transformative reality that has revolutionised various aspects of technology. We have seen it grow in what seems to be months, but the reality is that we need to understand the origins of AI and explore its remarkable evolution through key milestones in image, chat, video, and sound recognition, to properly project how it could participate in the industry day-to-day.
The roots of AI can be traced back to the 1950s when pioneers like Alan Turing and John McCarthy laid the foundation for computer science as we know it today. However, it was not until the convergence of powerful computing systems and the accumulation of massive datasets that AI truly flourished in different fields. The revolution is still happening, and we need to get ready for it to not be left behind.
We hope to see AI integrated in every aspect, in different proportions. For companies, for example, the best strategy is to evaluate the current skills, and to identify which additional areas have room for improvement and if AI is the best tool to sort it out and, as stated by Peter van der Made, Forbes Councils Member: “Failing to act inevitably means falling behind”.
Either way, according to McKinsey, along with sales, the Advertising industry is where AIwill have the most financial impact, either by brand’s using it to leverage its properties and consumer experience or by communities demanding or shifting their habits towards the satisfaction of using AI. But, as everything, we need to start in the beginning to know where we are heading. Let’s go deep dive into this:
The evolution of AI and its impact in the advertising industry
Everything started at the “image” state, in 2012 when AlexNet won the ImageNet challenge with a 16.4% overall error rate. The ImageNet challenge is a collection of 1.4 million images in 1000 categories (dogs, cars, plants..) and the challenge is to properly classify them by different inputs or similarities.
Here is where the neural network (internal engine of all artificial intelligence technologies) was finally working correctly. This is supposed to resemble human brain functions in terms of connecting ideas by patterns (basically how languages works); although it cannot replicate human’s awareness, imagination, inventiveness or creativity, dynamism or anything that makes us human; there is just computation, they identify patterns and follow them.
In today’s advertising landscape, where personalization plays a pivotal role, the significance of AI-generated images cannot be overstated. With the aid of machine learning platforms, AI has the capability to produce custom visuals that resonate with each individual’s distinct preferences. This heightened relevance not only enhances engagement but also drives conversions, making AI-generated images a powerful tool in the quest for effective advertising.
Now, talking about rule-based chatbot systems, the world of conversational AI advanced with the introduction of machine learning and natural language processing (NLP) techniques. These developments revolutionised chatbot capabilities, enabling them to have more human-like conversations. Today, AI-powered chatbots can understand the meaning behind users’ messages and provide personalised responses. Big players like Google, Microsoft, and Facebook have played a major role in enhancing chatbot technology by leveraging machine learning algorithms and neural networks. As a result, chatbots have become increasingly intelligent and effective in delivering a more engaging and tailored user experience.
In particular, this is being a key usage for brands in terms of personalisation of the experience of their users, since they can integrate chatbots into their online platforms and help each user in a unique way, since the AI will learn and follow the pattern of each user (easier said than done, of course). It requires a lot, actually, according to Statista, Investment in artificial intelligence reached $93.5 billion in 2021, and it’s still going up.
AI’s capabilities extend far beyond chatbots. It has also made significant strides in understanding and analysing videos and audio. Through the use of deep learning architectures and the analysis of vast video and audio datasets, AI systems can now identify objects, actions, and even emotions in visual and auditory content. This breakthrough has paved the way for various applications, including video surveillance, content moderation, speech recognition, and sentiment analysis. Research institutions and tech companies are continuously investing in the advancement of video and sound recognition technologies to unleash their full potential. Moreover, this progress has been game-changing for content creators, as they can now produce unique and engaging content without having to leave their homes.
The obsession with AI among Gen Z and Gen Alpha
Artificial Intelligence has become an object of fascination among the younger generations, particularly Gen Z and Gen Alpha, who have grown up in a digitally infused world. They are captivated by AI’s ability to simplify tasks, deliver personalised experiences, and provide insights based on vast amounts of data. Gen Z and Gen Alpha users are drawn to AI-driven platforms and services that seamlessly integrate into their digital lives, empowering them with convenience, efficiency, and a sense of empowerment. The continuous evolution of AI and its potential to reshape industries further fuels their curiosity and enthusiasm.
The evolution of artificial intelligence has traversed significant milestones, from the origins of image recognition to the development of sophisticated chatbots and the analysis of video and sound, and these advancements have profoundly impacted our lives, offering unprecedented capabilities and opportunities. As Gen Z and Gen Alpha users embrace AI-driven technologies, their obsession with artificial intelligence arises from a desire for seamless integration, personalised experiences, and the promise of a future where AI plays a central role in addressing societal challenges and shaping the marketing strategies not tomorrow, but today.
