Author: Navot Volk / Source: The Next Web
It seems like there are two words on the tongue of every tech entrepreneur, VC, or industry observer: artificial intelligence.
This is without a doubt the hottest topic in tech at the moment and this technological transformation is touching nearly every industry from automotive, to marketing, and even health.
Now, I’m not afraid of technology nor am I skeptical about the potential of AI, far from it. I’ve had the opportunity to work with multiple AI startups in my professional life and I believe this technology is going to change the world.
However, like any other emerging and potentially disruptive technology, there are a lot of startups in the space right now and that means that the potential for real tech development is clouded by claims of over eager startup founders looking to either fund their company or secure their first customers.
This general trend, which can be found with every new technology, is compounded by some truly difficult to understand and complicated concepts, which make AI more opaque as a technology than other fields. What this means, is that there is currently a great deal of hype and marketing fluff coming from AI startups.
For anyone looking to engage with AI companies, the prevalence of marketing fluff can make it difficult to move forward without stepping in someone’s outlandish claims. So, what can you do to avoid the landmines of hype littering the tech ecosystem? Here are a few suggestions:
Is there a simple idea hidden in a sea of complexity?
It may seem counterintuitive, but there is very often a simple idea hidden in complicated AI messaging.
There are of course two reasons to do this. The first is to make a company’s solution sound more capable than it is, while the second is to distract you from something the company would rather avoid talking about.The other way this problem manifests itself is in entrepreneurs trying to “sex up” their product or solution with AI terminology. One area we see this is with solutions using language processing such as chat bots or sentiment analysis.
While technologies such as machine learning are indeed used to understand language, the responses in many chatbot solutions are simple response trees – essentially not much more than a number of if/then statements.
Also, the language processing in some sentiment analysis solutions isn’t sophisticated enough to understand more complex or nuanced statements such as something being “a bomb” vs “da bomb.”
Always think about the data
AI, as it’s currently structured, is dependent on the breadth and quality of the data driving it. So, if you’re meeting an AI startup, it’s imperative that you drill down into the data. Find out how they acquired it, how they are labeling it, and exactly how they plan to use it.
There is also the issue that more and more frequently, companies are simply outsourcing the process of…
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