The AI Gold Rush is Dead. Long Live the New AI Gold Rush!

Why your ChatGPT obsession is SO last year, and what’s really going to make you rich in the AI revolution.

Forget everything you thought you knew about AI. That shiny ChatGPT toy you’ve been playing with? It’s about to become as outdated as my olden but golden Motorola flip phone. For a deeper dive of this, go to my blog post.

But don’t panic — I’m about to let you in on the REAL future of AI, and trust me, it’s wilder than you could ever imagine.

The Great AI Lie You’ve Been Sold

Remember when everyone and their grandma were talking about ChatGPT? Well, folks, that was so 2023. The AI landscape is shifting faster than a chameleon on a disco floor, and if you blink, you might miss the next big thing.

This also means that if you’re not already pivoting your AI strategy, you’re already behind. But don’t worry, I’m about to give you the cheat codes to get ahead of the game.

5 AI Trends That are Entering the Horizon

I’ve seen the future of AI, and it’s nothing like what the tech giants are telling you. At the core, think of this simple two-step statement:

1. AI models are becoming commoditized — the race is now becoming less about yet another LLM or MMLLM
2. The next step is the “productizing” of AI models — bringing a diversity of AI models together to solve real-life problems

Based on this, here are some recent AI types we see emerging/growing in interest and use:

• First Principles AI: This approach involves breaking down complex problems into their most fundamental elements and building solutions from the ground up. It’s about understanding the core truths or “first principles” of a problem domain and using that knowledge to create more robust and generalizable AI systems.
• Multi-Agent Systems: These are distributed systems composed of multiple AI agents that can perceive, reason, and act autonomously. These agents interact with each other and their environment to solve problems that are difficult or impossible for a single agent to solve alone.
• Causal AI: This type of AI goes beyond traditional correlation-based machine learning to identify and utilize cause-effect relationships. It aims to understand not just that two events are related, but how and why they are related, enabling more accurate predictions and more effective interventions.
• Composite AI: This refers to the integration of multiple AI techniques or technologies to create more powerful and flexible systems. It might combine machine learning, rule-based systems, and other AI approaches to tackle complex, multifaceted problems.
• Neuro-symbolic AI: This approach aims to combine the strengths of neural networks (good at pattern recognition and learning from data) with symbolic AI (good at reasoning and using explicit knowledge). The goal is to create AI systems that can both learn from data and reason about it using symbolic logic.

Meanwhile, poor old computer vision is now sitting in the corner, wondering where all its friends went.

With this in mind, we have to realize that AI is now becoming a cog in the wheel — a powerful one at that, but still that AI is the big leverage to solve problems, and less being the solution itself.

Why Many AI Companies Will Fail in the Next 5 Years

Let’s talk about everyone’s favorite graph: the Gartner Hype Cycle. If you haven’t seen it, imagine a rollercoaster designed by a caffeinated toddler. That’s pretty much what the AI hype cycle looks like right now, as shown below:

According to this graph of destiny, Generative AI already has hit its peak in 2023, and we’re possibly heading into a phase of disillusionment for GenAI models.

But as you can see, there’s a whole bunch of new AI flavors climbing up that hype hill.

Here the S-curve of innovation comes into play. Did you think the S-curve of innovation is just some boring business concept about a one-off innovation cycle? Think again! It’s like a never-ending game of leapfrog, where each new technology jumps over the last one’s shoulders, as shown below:

At Neurons (that’s us, by the way — www.neuronsinc.com), we’re not content with riding the first wave. Oh no, we’re surfing on the second (maybe even third) S-curve!

We’re taking all those fancy AI models and mashing them together into a product that’s solving problems faster than you can say “artificial intelligence.” Instead of only making a single AI that predicts consumer responses (actually, different AI models that predict attention, emotion, cognition, memory) we also have models for object/brand tracking in images and videos, LLMs that operate as marketing copilots to help marketers improve their assets, and beyond.

7 Mind-Blowing AI Technologies You’ve Never Heard Of (Yet)

While you’ve been hearing about ChatGPT and DALL-E, the AI world has been quietly revolutionizing in other ways. Here are seven cutting-edge AI technologies that are reshaping the future:

1. Federated Learning: This technology allows AI models to be trained across multiple decentralized devices or servers holding local data samples, without exchanging them. It’s revolutionizing privacy-preserving AI.
2. Neuromorphic Computing: Inspired by the human brain, these AI systems use electronic circuits to mimic neurobiological architectures, potentially leading to more efficient and adaptable AI.
3. Quantum Machine Learning: This field combines quantum computing with machine learning, promising exponential speedups for certain AI tasks and the ability to process complex quantum data.
4. Explainable AI (XAI): Unlike traditional “black box” AI, XAI systems can provide clear, understandable reasons for their outputs, crucial for building trust in AI decision-making.
5. Edge AI: This technology enables AI processing on local devices rather than in the cloud, reducing latency and enhancing privacy for applications like autonomous vehicles and smart home devices.
6. Generative Adversarial Networks (GANs): While not at all new, recent advancements in GANs are pushing the boundaries of AI creativity, enabling the generation of increasingly realistic images, videos, and even music.
7. Swarm AI: Inspired by collective biological behavior in nature, Swarm AI combines real-time human insights with AI algorithms to make more accurate predictions and decisions. The models work as collective behavior and cooperation of large numbers of homogeneous, self-organized, and decentralized agents to solve problems.

As this and the previous list show, innovation in AI develops like the leapfrog layered S-curve model.

The AI Gold Rush: It Ain’t Over, Folks!

Around 1900, some physicists believed that science was “over”. One claimed that:

“There is nothing new to be discovered in physics now. All that remains is more and more precise measurement.” (often misttirbuted to Lord Kelvin but more likeky stated by Albert A. Michelson)

In the same vein, some people out there might be thinking, “The AI race is over! Pack up your neural networks and go home!” But let me tell you, they couldn’t be more wrong if they tried.

The real race? It’s just getting started. Sure, it’s not about who can build the biggest, baddest AI model anymore.

Now, it’s insteadabout who can take these AI building blocks, combine them, and construct the Taj Mahal of solutions. AI models are the building blocks, the solution that solves people’s problem is the product.

This is exactly what we’re doing at Neurons. We’re taking those MMLLMs (multi modal large language models), fine tune them with our own data, create our own predictive AI models based on our neurobehavioral database, sprinkling in some additional machine learning magic, and creating products that are so cutting-edge, they make Swiss Army knives look like stone tools.

The REAL AI Revolution is Looming!

As we hurtle towards the future on this upward-going AI rollercoaster, one thing’s for sure: it’s going to be one heck of a ride! Will First Principles AI become the next big thing? Will Multi-Agent Systems take over the world (hopefully in a nice way)? Or will some yet-unknown AI technology swoop in and steal the show?

The AI revolution waits for no one. Today, you need to determine whether you areready to be a leader or a follower! The choice is yours, but you need to make it NOW. One simple start: share this article! Another one: comment and contribute :)