AI Predictions for The Future: What’s Next?
For the past couple of years, we’ve tried our hand at predicting what’s next in the world of AI.
It’s a bit like trying to forecast the weather in a tornado—things change fast!
But hey, we’ve done pretty well so far, so we’re giving it another go.
How Did We Do Last Year?
Back in 2024, we made some bold predictions, and guess what?
We pretty much nailed it. Here’s what we got right:
Customised Chatbots (a.k.a. AI Agents)
We predicted that chatbots would get way smarter and more interactive.
Turns out, we were talking about what everyone now calls AI agents—those helpful digital assistants that can handle complex tasks and make your life easier.
And yes, they’re everywhere now!
Generative Video
We said AI would get really good at making videos, and wow, were we spot on.
Companies like OpenAI and Google DeepMind have launched super impressive AI video creators—Sora and Veo—that can turn text descriptions into stunning visuals in seconds.
Smarter Robots
We guessed that robots would become more versatile, thanks to AI improvements.
And here we are—robots are now tackling all sorts of tasks, from helping in warehouses to assisting with household chores.
AI Election Disinformation (Oops, We Were Wrong)
Last year, we thought AI-generated fake political content would flood our social media feeds. Thankfully, it wasn’t as bad as we expected—phew! But let’s not get too comfortable just yet.
AI is making it easier than ever to create fake but convincing content designed to mislead voters. With just a few clicks, anyone can generate fake news, speeches, or even deepfake videos that look incredibly real. This isn’t just a problem for tech-savvy countries; regions with lower literacy levels are especially at risk because people might struggle to tell what’s real and what’s not.
And here’s the kicker—it’s not just a local problem; it’s a global one. From major economies to developing regions, AI-generated election disinformation could shake up trust in democratic processes everywhere.
In short, AI has made spreading misinformation faster, easier, and more widespread than ever before. So while we dodged a bullet last year, the battle against fake news is far from over.
We’ve seen AI evolve at lightning speed, and it’s only getting started. While some trends are obvious—like AI assistants becoming more efficient and models getting smaller and faster—there’s more brewing beneath the surface.
So, what should we expect in the upcoming future?
Next clauses will be discussed further into the next section, we’ll dive into the surprising AI trends that could reshape the way we live, work, and interact with technology.
The Future of Gaming: From Sketches to Immersive Virtual Realities
In 2023, we saw the rise of generative images, followed by generative videos in 2024. So, what’s next? Will Douglas Heaven suggests we’re on the verge of something even more exciting: generative virtual worlds, or as we know them, video games!
In February, Google DeepMind gave us a sneak peek with their model, Genie, which could turn a simple still image into an interactive 2D platform game. Fast forward to December, and we got Genie 2, capable of transforming a single image into an entire virtual world. It’s pretty mind-blowing!
But Google isn’t alone in this. Startups like Decart and Etched are also exploring similar concepts. They even managed to hack Minecraft in a way that generates every frame on the fly as you play. And World Labs, co-founded by Fei-Fei Li (the creator of ImageNet, which helped ignite deep learning), is developing something called large world models (LWMs), which aim to create vast virtual spaces for machines to explore.
So, what does this mean? Well, it could revolutionise video games. Imagine being able to create entire game worlds from a simple sketch, opening the door to new types of games. But it’s not just about fun and play. These virtual worlds might also be used to train robots. Heaven explains that by simulating countless environments, robots could learn how to interact with the real world more effectively—especially when there’s limited real-world data available for training.
In simple terms, we’re talking about an explosion of creativity in game design and a big leap forward in how machines learn about the world. Generative virtual worlds could be the next big thing!
The Rise of New Chip Giants: Will Nvidia’s Reign Be Challenged in future?
For years, if you wanted to build an AI model, Jensen Huang, CEO of Nvidia, was the name everyone turned to. Under his leadership, Nvidia became the go-to company for AI chips, powering everything from training AI models to the important job of “inferencing”—the process of AI models making sense of real-world data. But according to James O’Donnell, things could change in 2025, with some serious competition coming Nvidia’s way.
Big names like Amazon, Broadcom, and AMD have been pouring huge amounts of money into creating their own chips, and there are signs that these new chips could rival Nvidia’s, especially when it comes to inferencing, an area where Nvidia’s lead isn’t as secure.
And then there are the startups. Instead of just tweaking Nvidia’s designs, companies like Groq are taking bigger risks, betting on brand-new chip architectures that could, with time, be more efficient or effective at training AI. While these experiments are still in their early days, O’Donnell hints that we might see a challenger rise up in 2025, changing the idea that all top AI models need to rely on Nvidia.
Lastly, there’s the shifting landscape of chip production. Companies are looking to reduce their dependence on a few key manufacturers, which could lead to more local and varied production. This shift has the potential to stir up more competition in the market and challenge Nvidia’s reign. So, 2025 could very well be the year when Nvidia faces its biggest challenge yet.
Smart AI That Thinks Before It Acts: The Future of Reasoning Models
When OpenAI introduced o1 in September, it wasn’t just another AI upgrade—it was a whole new way of doing things. Then, two months later, they followed up with o3, a model that could completely change how AI works. According to Will Douglas Heaven, this shift is all about teaching AI to “reason” through problems instead of just spitting out quick answers.
Most AI models, including the well-known GPT-4, tend to go with the first answer they come up with—sometimes it’s right, sometimes it’s not. But OpenAI’s new models take a different approach. They break down complex problems step by step, trying different methods when one doesn’t work. This “reasoning” technique (yes, we know it sounds like AI is becoming too smart) makes these models much better at handling things like math, physics, and logic-based challenges.
And this isn’t just useful for answering tricky questions—it’s also a game-changer for AI agents.
Take Google DeepMind’s new web-browsing agent, Mariner, as an example. During a demo, Megha Goel, a product manager, asked Mariner to find a Christmas cookie recipe that matched a photo she provided. Mariner found the recipe and started adding ingredients to an online grocery basket—but then it got stuck. It didn’t know what kind of flour to pick. Instead of giving up, it walked through its thought process in a chat window: “I will use the browser’s Back button to return to the recipe.”
That might sound simple, but for AI, it’s a big deal—a tiny step closer to problem-solving like humans do. And guess what? It worked. Mariner went back, checked the recipe, and finished the job.
Google DeepMind is taking things further with an experimental version of Gemini 2.0, its latest AI model, which uses a similar step-by-step approach called Flash Thinking to tackle problems logically.
But it’s not just OpenAI and Google in the game. Many companies are jumping on this trend, working on AI that can reason through challenges, whether it’s finding the perfect recipe or writing clean code. And as Heaven points out, we can expect to hear a lot more about AI reasoning this year.
Wrapped Up: AI Applications You Didn’t See Coming
As we look ahead, it’s clear that AI is evolving at breakneck speed, with innovations that are set to redefine how we live, work, and play. From reasoning AI models that think through problems step by step, to generative virtual worlds that could revolutionise gaming and robot training, the possibilities are expanding faster than ever before.
We’re also witnessing the rise of new chip competitors, potentially ending Nvidia’s reign and bringing fresh innovation to AI hardware. At the same time, the threat of AI-driven misinformation reminds us that with great power comes great responsibility—ensuring AI is used ethically and transparently will be more important than ever.
What does all this mean for the future? Simply put, AI is no longer just about chatbots and automation. It’s about intelligent problem-solving, creativity, and adaptability across every aspect of our lives. Whether it’s transforming industries or reshaping our daily experiences, the next big thing in AI might just be something we never saw coming.
So, buckle up—upcoming year is set to be a wild ride in the world of artificial intelligence!
