Bing announces AI-powered new ‘intelligent search’ features

At Microsoft’s AI event yesterday in San Francisco, the company showcased its vision for AI-enabled computing, as well as its AI differentiation strategy. The latter essentially boils down to three big ideas: making AI-supported software broadly accessible to people to improve “everyday” experiences, the seamless combining of work and personal functionality in the same tools and the intention to be an ethical AI company.

Microsoft showed how AI and machine learning are now supporting its marquee products, from Windows to Office 365 and Bing. The most impressive demonstration of the day (from a self-interested perspective) featured AI-guided and automated design suggestions in PowerPoint.

There were several Bing-centric AI announcements, all under the heading of “intelligent search“:

• Intelligent Answers
• Intelligent Image Search
• Conversational Search

Intelligent Answers

Think of this as a kind of “next-gen Featured Snippets.” But what is different and interesting is that Bing is often summarizing or comparing multiple sources of information rather than just presenting a single answer.

If there are competing perspectives on an issue, for example, Bing will present them. It will also provide a “carousel of intelligent answers” if there are multiple answers to a question. This is intended to replace “blue links” and provide quick access to relevant information.

Below is a Bing-provided example of a comparison involving two different content sources on the question, “Is kale good for you?”

Intelligent Image Search

Here Bing is essentially doing what Pinterest announced in 2016 with “visual search” and object recognition. Bing is seeking to make virtually any image “shoppable.” Right now, that capability is focused on fashion and home furniture.

Users can “click the magnifying glass icon on the top right of any image to search within an image and find related images or products.” The example below illustrates how it works.

Bing can also detect and identify buildings and landmarks in user photos or in image search — though not yet in the real world.

Google Lens offers visual search for objects and places in the real world (so does Amazon, for products). I would anticipate that soon Bing will introduce a similar Lens-like capability through Cortana or its search app.

Conversational Search

Bing is taking search suggest/autocomplete to a new level with what it’s calling “conversational search.” From a very general or vague query, Bing will help with query refinement suggestions:

Now if you need help figuring out the right question to ask, Bing will help you with clarifying questions based on your query to better refine your search and get you the best answer the first time around. You’ll start to see this experience in health, tech and sports queries, and we will be adding more topic areas over time. And because we’ve built it with large-scale machine learning, the experience will get better over time as more users engage with it.

Finally, the company also announced the integration of Reddit content (answers/opinions) into Bing. Tim Peterson wrote about that in more detail yesterday. In short, however, Bing is going to show snippets of Reddit content or conversations when it believes that’s the best source of information.

Microsoft will also promote AMAs in search results and in knowledge panels: “On Bing you can discover AMA schedules and see snapshots of AMAs that have already been completed. Simply search a person’s name to see their AMA snapshot or search for ‘Reddit AMAs’ to see a carousel of popular AMAs.”

It’s unlikely that any of these changes will move the needle on market share in the short term. However, collectively they show an AI-driven acceleration of changes in search overall. Google will probably be compelled to answer a couple of the new Microsoft features.

If Microsoft truly wants to convert more users, it will need to be even bolder with features, content and UI changes. And the company is in a fairly strong position to be disruptive because it doesn’t rely on search-ad revenue to the extent that Google does.

About The Author

Greg Sterling

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.