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  • Writer's pictureJames Johnson

The AI Awakening - Separating Hype from Reality



We're in the midst of an "AI awakening" where artificial intelligence has taken center stage in our cultural consciousness. However, the reality is that AI has been quietly integrated into our lives for years, with many of us unaware of how prevalent it already was.


The Origins of AI in Software

While the current wave of AI hype and consumer adoption may seem recent, the core technologies like machine learning, neural networks, and natural language processing have been part of software for decades. These mathematical models that can learn from data and make predictions have been employed behind the scenes in industries like:


- Fraud detection for financial services

- Recommendation engines for e-commerce sites

- Spam filtering for email services

- Voice recognition for virtual assistants

- Image recognition for social media auto-tagging


So in many ways, AI has been an invisible helper making our computing experiences smarter and more seamless for years before becoming a mainstream buzzword.


The Marketing Ploy of "AI-Washing"

With AI now a hot topic capturing public interest, many companies have started slapping an "AI-Powered" label on their products and services as a way to position themselves as cutting-edge and innovative. This "AI-washing" is akin to companies jumping on other tech buzzwords like "cloud computing" and "big data."


The truth is many companies are doing little more than applying basic machine learning models or rules-based systems and calling it AI as a means of marketing hype. In other cases, companies have had AI capabilities in their software for some time but are just now making noise about it since AI is newly bankable.


Separating Substance from Marketing Spin

While AI will surely transform many industries in the coming years, it's important for consumers to look beyond the AI branding and understand what companies are actually delivering:


- What specific AI capabilities (e.g. computer vision, NLP, predictive modeling) are being utilized?

- How is the AI model trained and what data powers its intelligence?

- What are the practical use cases and benefits for end-users?


Understanding the reality behind the AI claims will allow us to separate substance from empty marketing spin as we navigate this "AI awakening."


As AI becomes more democratized and applied to new real-world problems, we should maintain a balanced perspective - being excited about its potential while also being discerning about what companies are truly offering versus just cashing in on a hot trend.

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