Why Canadian News Is Stuck Using Generic AI Models — And How My Thousands of Fine-Tuned Models Are Changing the Game

By Gerard King, www.gerardking.dev

In the world of modern journalism, one would assume that artificial intelligence (AI) would be harnessed to enhance storytelling, add depth to reporting, and produce more thoughtful, nuanced articles. However, the reality, particularly in Canadian mainstream media, is far from that ideal. Over the past few years, I’ve spent countless hours developing and fine-tuning AI models to do exactly that: craft high-quality, tailored content that speaks to specific audiences and addresses complex issues. And yet, despite this, Canadian news outlets are relying on generic, off-the-shelf AI models that produce repetitive, uninspired, and often flat content.

I’m Gerard King, and my website, gerardking.dev, is home to thousands of highly advanced, customized AI models that I’ve painstakingly developed over the years. These models don’t just churn out basic content. They are designed to understand nuance, context, and tone, enabling them to create rich, engaging, and highly specialized pieces of writing. Yet despite these advancements in AI technology, Canadian mainstream media outlets continue to use basic, mass-produced AI models that fail to meet even the most basic standards of originality.

The Problem: Generic AI Models in Canadian Newsrooms

Let’s break down the core issue: Canadian media, for the most part, is still using generic, one-size-fits-all AI tools that anyone can access. These are models like GPT-3, which, while impressive in their ability to generate coherent text, lack the sophistication and nuance needed to produce high-quality journalism. The result? A wave of repetitive headlines and articles that use the same tired phrases over and over again — phrases that seem to be generated with little regard for creativity or originality.

One of the most noticeable trends in Canadian news today is the overuse of the word "unveiling." This term has become so ubiquitous that it seems to appear in over 50% of Canadian news headlines. Why? Because it’s a go-to phrase for AI models that are designed to churn out “catchy” headlines with minimal effort. AI models, including GPT-based systems, are trained to favor certain words and structures that are proven to get clicks, but they don’t have the capacity to understand whether these phrases are overused or out of context.

This reliance on the word "unveiling" is just one symptom of a much larger problem: the laziness and lack of originality that comes with using generic AI models for news generation. The word itself is a buzzword — a filler designed to give a sense of drama and excitement without delivering anything of substance. AI models trained on vast amounts of text data tend to pick up these kinds of shortcuts, producing headlines that are repetitive and shallow, rather than meaningful or thought-provoking.

A Broader Issue: The Rise of “Buzzwords” and AI Simplification

The problem doesn’t stop with "unveiling." Canadian headlines are also dominated by other generic, AI-friendly buzzwords that serve to sensationalize content without adding real value. Here’s a list of other terms that have become almost cliché in AI-generated content:

• "Revolutionary"

• "Breakthrough"

• "Exclusive"

• "Incredible"

• "Shocking"

• "Unprecedented"

• "Transformative"

• "Innovative"

• "Game-changing"

These words have become so overused that they no longer evoke any real emotion or interest. They are the product of AI tools that prioritize simplicity and engagement over genuine creativity or depth. The sad irony is that these words are supposed to grab attention, yet they’ve become so formulaic that they do the exact opposite: they make readers feel like they’re being sold something that isn’t as exciting as it’s made out to be.

For example, when you see a headline like “Exclusive Interview with CEO: A Revolutionary New Product Unveiled Today,” you immediately know it’s probably been generated by an AI model looking to create a headline that ticks all the boxes — attention-grabbing, sensationalist, and, most importantly, using language that AI knows will generate clicks. But is the content actually revolutionary? Probably not. Is it exclusive? Likely not. Yet these terms continue to dominate our media landscape.

My Work: Crafting AI Models That Go Beyond Generic

So, what’s the alternative? Well, I’ve spent years developing and fine-tuning AI models that go far beyond the basic, generic outputs you see in mainstream media today. While the mainstream media is relying on simple, mass-market models that produce uninspired content, I’ve built thousands of AI models that can generate complex, creative, and highly engaging pieces of writing.

At gerardking.dev, you can explore these models and see the difference for yourself. These models are not just designed to spit out random content based on keyword popularity or clickbait tactics. They are tailored to specific needs, each one fine-tuned to deliver original, insightful, and high-quality text. I use an advanced approach that incorporates contextual understanding, audience preferences, and industry-specific needs, making my models capable of creating content that resonates with readers on a much deeper level.

When I develop an AI model, it’s not about using the same tired phrases that everyone else uses. Instead, I ensure that the AI understands the nuances of language, tone, and cultural context. For instance, if I were to develop an AI model for Canadian journalism, I would train it on Canadian news sources, history, and cultural context, ensuring that the AI could produce articles that are relevant, insightful, and unique to the Canadian experience.

In contrast, the generic AI models that dominate newsrooms today don’t have the ability to make such distinctions. They might know that "unveiling" is a popular word in headlines, but they don’t understand why it’s being used or whether it’s even appropriate. And because they lack that critical understanding, they churn out repetitive, formulaic content that doesn’t add value to the reader.

AI: The Future of Journalism — But Only If It’s Used Correctly

There’s no doubt that AI has the potential to revolutionize journalism. But for that to happen, news organizations need to stop relying on cookie-cutter models that produce lazy content. They need to embrace AI that is not only capable of understanding language at a deep level but also capable of creativity, nuance, and originality.

Imagine a future where AI is used to not only generate content but to analyze data, identify emerging trends, and even offer new perspectives on complex issues. That future is already here, but it’s being held back by the widespread use of basic, generic AI models that fail to meet the demands of a modern, discerning audience.

If Canadian newsrooms are serious about improving the quality of their journalism, they need to invest in more advanced, tailored AI systems. Systems that can go beyond buzzwords and clichés and deliver the kind of thoughtful, nuanced content that today’s readers are craving.

Conclusion: Don’t Settle for Generic AI

As someone who’s spent years developing and refining AI models, I can say with confidence that there’s a better way. The technology is here, and it’s far more sophisticated than the generic models currently being used by mainstream media. It’s time for Canadian journalism — and media worldwide — to move beyond the limitations of basic AI tools and embrace the power of fine-tuned, customized AI systems that can generate truly original, engaging content.

If you’re interested in seeing how AI can be used to create high-quality, meaningful journalism, head over to gerardking.dev and explore the thousands of fine-tuned models I’ve developed. It’s time to stop relying on the same old tired phrases like “unveiling” and “revolutionary” and start creating journalism that matters.