Like humans, search engines will have an evolutionary brain that understands search behavior to learn from it. Search engines are fast becoming personal assistant by enabling meaningful contextual conversation. Search engines will provide real-time opinion & experience from customers across the globe.
SEARCH TOMORROW WILL BE ‘HUMAN LIKE’
1. Evolutionary Brain:
Like humans, search engines will have an evolutionary brain that understands search behavior to learn from it. While Machine Learning is already being used by search engines, we still have a long way to go to understand & learn from ‘mass-scale’ human search patterns. Deep learning technique is fast evolving. It’s becoming increasingly more important to capture your customer’s imagination and attention with visuals, and search companies are taking notice.
2. Personal Assistant
Search engines are fast becoming personal assistant by enabling meaningful contextual conversation. E.g., When you search for the status of your flight, it tells you that your old friend is travelling in the same flight. Search engines today provides personalized responses for queries like “what’s the status of my flight”. Search engine crawling is transitioning from being web based to IoT based. Search engines are truly moving away from being information providers to becoming personal assistants. In the near future, they may very well book your flight tickets, order a pizza and more.
3. Experiential Intelligence
Search engines will provide real-time opinion & experience from customers across the globe. More & more people search online to understand real-time experience from another person. For example, how does the food taste today in a particular restaurant, traffic congestion on a busy road, etc. Search engines of the future will provide real time information on people’s experiences. It’s almost like asking a customer how does the coffee taste today before you place your order.
CHANGING THE WAY PEOPLE SEARCH CODE:
We learn code with Google:
Today’s smart engineers learn with Google. We search for code syntax, use cases, properties – and learn from it. Many a times we end up reading through irrelevant blogs & articles. As Engineers, we look for solution to solve a problem with examples of how it was done in the past & in what context a particular class was used.
Can we make code search more contextual?
So, we asked ourselves – can we make code search more contextual & relevant for Engineers with real examples of how a particular piece of code was used in the past. This opens up new opportunities to explore all possible use cases of a specific class.
We built KodeBeagle. It makes code search contextual.