When it comes to finding the best pav bhaji, most people would turn to a search engine like Google to help them locate the best options. But what happens when we pit the search engine results to find the best pav bhaji against the result from the latest Bing AI chatbot? Which one will offer the best results and the best user experience? 

Tech Today’s Aayush Ailawadi got early access to the Bing AI chatbot which is currently being tested and is not widely available. Let’s explore the Google vs Bing AI chatbot debate and find out which one is better at finding the best pav bhaji for you.

When we asked Google Search “I want to eat Pav Bhaji” the search engine curated a list of restaurants and street food vendors in the area that served the popular Indian dish. The results included links to the restaurants’ websites, customer reviews, and maps showing their locations. Google also provided other links with more details on the dish.

In contrast, when we asked the Bing AI chatbot for Pav Bhaji, it took a different approach. Instead of simply curating a list of nearby joints, Bing started by explaining the origin and meaning of Pav Bhaji. It provided a brief history of the dish, along with some information about its ingredients and preparation. Bing then asked us if we wanted to order the dish online or find a nearby restaurant that served it. When we chose the option to order online, Bing curated a list of online food delivery services that offered Pav Bhaji, along with some information about each service.

Overall, we found that both Google Search and the Bing AI chatbot were effective at providing us with information about Pav Bhaji. However, the two services took different approaches to answer our query. Google focused on providing us with a list of nearby restaurants, while Bing took a more educational approach by explaining the dish’s history and ingredients.

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Pav Bhaji query 10 times more expensive for Bing than Google

Putting the Pav Bhaji conundrum aside, Bing’s AI-based chatbot is most likely to be considerably more expensive per query than a Google search, which may have implications for businesses looking to implement such technology.

In an interview, Alphabet’s Chairman John Hennessy told Reuters that having an exchange with AI known as a large language model likely cost 10 times more than a standard keyword search, though fine-tuning will help reduce the expense quickly.

The process of handling AI-powered search queries is known as « inference, » in which a « neural network » loosely modelled on the human brain’s biology infers the answer to a question from prior training whereas, in a traditional search, Google’s web crawlers have scanned the internet to compile an index of information. When a user types a query, Google serves up the most relevant answers stored in the index.

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