Waiting for AI? It’s Due to Arrive in 2047

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Waiting for AI? It’s Due to Arrive in 2047

If you are in the software business, you can probably identify with this. Have you noticed that most of your competitors are now saying they offer artificial intelligence (AI) products? Yesterday they didn’t, today they do. I think someone is stretching the truth a bit.

An article in The New Yorker commented about functional AI, “In the nineteen-forties, the first visionaries assumed that we’d reach it in a generation; A.I. experts surveyed last year converged on a new date of 2047.” Imagine, our competitors can do it in 24 hours – ha ha.

Anyway, what does that mean to you and me? It means if we expect the world to be digitally powered by accurate, reliable AI applications, then we have a wait ahead of us. Those who have the wherewithal are eagerly jumping on the bandwagon, although I am not sure they fully understand what they are doing.

Let’s take a look at search and these technologies. Search engines are computer applications, but they need to be able to understand human language in order to find the information users are looking for. Some would call that natural language processing (NLP), a field of AI. What improves search involves learning to rank algorithms. Machines are taught to create an optimal list from a set of possible outcomes, learning from each of the variables over time. For example, if one result on a search engine is ranking third but has a higher click through rate than the options above it, the search engine would learn from this anomaly and bump that result to the top.

The most important thing to understand about AI is that it is not a static formula to solve. It’s a constantly evolving system designed to identify, sort, and present the data that is most likely to meet the needs of users at that specific time, based on a multitude of variables that go far beyond just a simple keyword phrase. Sounds like our software.

What are the drawbacks? According to Google, not only will its AI develop new ranking factors on its own, it will do so inside a proverbial black box. This presents a special problem for search engines, because if the engineers don’t know what their AI is using as ranking signals, they can never fully compute how the machine got to the specific conclusion it did in a specific instance. This means you may or may not find what you are looking for, and they don’t know what to fix.

Another issue, at least to me, is that as AI search evolves, search engines will simply extract the data most likely to meet users’ needs and present it directly to them, rather than giving them a list of potential matches. As a professional who performs a vast amount of research, I don’t want one answer. Even with the recent changes by Google, I am not finding what I am looking for. And I can’t get out of the loop – in other words, Google doesn’t understand that the result has nothing to do with what I am looking for.

Finally, there is the problem of accommodating different types of end user queries, including navigational, informational, commercial, and transactional. Maybe by 2047 someone will have figured this out.

If your goal is to have an AI-powered search, good for you. If you need a search engine now, not in 2047, our insight engine can go toe-to-toe with AI. In fact, it would probably surpass it, and is a lot cheaper, a lot faster, and technically better.

Addressing the issue of metadata, our insight engine generates multi-term metadata. What does that mean? It means it is smart enough to identify phrases that represent topics, subjects, and concepts. Like AI, it will also identify inter-related or intra-related content, even if none of the keywords are present. Content is then classified against one or more taxonomies, and the rich multi-term metadata is provided to the search engine index. Is there a need for data scientists? Nope – it was designed for subject-matter experts. Easily managed and maintained, with highly interactive features unique in the field of content management solutions, it expedites development and testing, in real-time.

Why wait until 2047 for AI-powered search, when you can have the same functionality today?

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