It’s a very exciting time to be a technologist. My own IT career has experienced massive transformation all the way from mainframes, client servers, enterprise apps, and the internet, to the cloud and AI. In today’s digital economy, technology leaders are the bridge between business agendas and leadership strategies. These tech leaders are uniquely positioned to challenge the status quo by setting the direction for an enterprise, which is driven largely by innovation in technology. For the past few months, every such leader is trying their best to realign an organisation’s technology strategy with generative AI.
Let’s look at what generative AI is, how it is different from traditional AI, why it’s gaining popularity now, and what open-source technologies are available to take advantage of this new bleeding-edge innovation. But before jumping into what generative AI is, it’s important to give a quick look at what AI truly is and how it has evolved over the years.
Brief history of AI
It was way back in 1950 that Alan Turing questioned whether machines can think. That single thought has led to the development of autonomous driving cars, self-healing applications, and much more. In the quest for developing a smart world that’s highly productive, the role of AI has been significant, especially in the past two decades. Traditional AI evolved into generative AI when generative adversarial network (GAN) algorithms were developed to create convincingly authentic images, videos, and audio of real people.
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