The next wave of AI
Tools like ChatGPT have shown us what AI can do, but they only scratch the surface. The next wave of AI will not just generate cool content but will fundamentally change industries, making them smarter, more efficient, and more ethical
You can’t turn a corner without hearing about artificial intelligence (AI), particularly generative AI tools like ChatGPT, Dall-E and many others. Whether creating content, writing code or answering homework questions, ChatGPT has captured everyone’s attention. But, if you think that’s the peak of AI’s potential, think again. This year has brought a wave of new AI technologies quietly shaping the future. According to the Consultancy Firm Gartner, we’re in the middle of a massive shift.
While generative AI is riding high, it’s not the only thing making waves. Other AI technologies are emerging, ready to make an even more significant impact on industries, businesses, and our everyday lives.
If you’re wondering why there is so much excitement around AI right now, you need to realise that AI is more than just a tech trend – it’s changing the way we work, learn, and interact. From improving customer service with chatbots to diagnosing diseases in healthcare, AI makes life easier, faster, and in some cases, safer.
Generative AI, like ChatGPT, has been great at creating content quickly, but the excitement around it also raises questions about its limits. For example, while it can write essays, answer questions, or even make jokes, it sometimes struggles with more complex reasoning tasks.
This leads to what Gartner calls the “Peak of Inflated Expectations” – a stage where the hype is massive, but real-world results haven’t entirely caught up.
We’re seeing that right now with generative AI. It’s fascinating, but it’s not the whole story.
Beyond the usual hype, there’s much more than meets the eye. Take something like synthetic data. AI needs loads of information to learn and improve, but sometimes, this data can’t be shared because it’s private.
For example, hospitals have strict rules about sharing patient data, so how can AI learn to spot diseases without seeing real medical records? Synthetic data is the answer. It creates fake but realistic data that AI can use to learn without breaking any privacy laws.
Think of it like making a training video for a worker without using real customer information. This allows AI to learn and improve without the risks of handling sensitive data.
Another compelling development is the rise of foundational models. These robust systems, far more powerful than ChatGPT, are being deployed across various industries to make critical decisions and solve significant problems.
For instance, banks are leveraging these models to detect fraudulent transactions in real-time, while scientists are using them to predict weather patterns with unprecedented accuracy.
Unlike generative AI, which is primarily focused on text and image generation, foundational models are empowering businesses to make smarter decisions that can save time, money, and even lives.
On the other hand, we have a growing army of AI tools designed to run in the background, silently improving how companies and even governments operate. These are called operational AI systems.
While you might not see them at work, they help manage everything from supply chains to customer service departments, making sure things run smoothly. Imagine a supermarket using AI to predict which products will sell out first based on the weather forecast.
It can order more of those products automatically, so the shelves are always stocked without human intervention. This is the future of AI – working quietly behind the scenes to improve our daily experiences.
One of the most intriguing concepts in the Hype Cycle is AI TRiSM, which stands for AI Trust, Risk, and Security Management.
As AI assumes more responsibilities, from driving our cars to analyzing our personal data, the need to ensure the safety and reliability of these systems becomes increasingly critical. AI TRiSM is about instilling trust in AI systems, ensuring that their decisions are fair, transparent, and secure.
For instance, in the context of hiring decisions, AI TRiSM guarantees that AI doesn’t discriminate against any particular group.
It’s about ensuring that as AI takes on more pivotal roles, it does so in a manner that benefits everyone.
We’re also seeing exciting developments in the education space with tools like AI makers and teaching kits. These are designed to help non-experts – including students and everyday people – understand how AI works.
Imagine being able to build your own simple AI at school, learning how these systems think and make decisions. This kind of hands-on education can prepare the next generation to not only use AI but also shape its future development.
It’s no longer just about scientists in labs; AI is becoming something we can all get involved in, regardless of our background.
So, what’s next? While the current AI craze focuses on flashy technologies like ChatGPT, the real game-changers are still developing quietly, and AI’s journey is just beginning.
Tools like ChatGPT have shown us what AI can do, but they only scratch the surface. The next wave of AI will not just generate cool content but will fundamentally change industries, making them smarter, more efficient, and more ethical.
We’ll see AI managing everything from the energy grid to our healthcare systems, creating a world where technology works for us behind the scenes, making life smoother and more connected.
So, while the buzz around ChatGPT may fade, the real impact of AI on our world is only just beginning – and it will be bigger than we ever imagined.