3 questions to separate AI from marketing hype
One of the myriad challenges of being a modern technology leader is separating the marketing hype from reality when it comes time to procure new hardware or software. Product marketing often tends toward hyperbole and focuses on the positive rather than the negative. With technology products, there’s the added wrinkle of complex technical elements that require specialized understanding.
Mix the historical hyperventilation of most product marketing with a hot technology, and you’re forced to wallow through a dense wall of promises, buzzwords and claims to determine if a product will work for your organization. This is especially true in the era of artificial intelligence, where it seems everything from supply chain software to office furniture claims to have some element of AI embedded. One could almost imagine a late-night infomercial host shouting that the product he’s shilling: “Now includes 30% more machine learning!”
The problem in evaluating products that include AI is that definitions of what constitutes AI can vary widely. If your definition assumes learning algorithms that intelligently categorize new data, and your vendor considers AI to include little more than a bit of fancy computation, you’ll be disappointed. In order to pin down what your vendor means when they tell you there are elements of AI included in their product, here are three simple questions that can help separate the hype from reality.
How does the AI model learn?
A foundational element of most true AI technologies is that they improve based on the data they receive or include technologies that test potential future outcomes and strengthen their calculations based on those outcomes. Game-playing AI’s are a classic example of this technology, where the AI can simulate playing thousands of iterations of a game and improves its performance based on the outcome of each game.
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