Why is Google Focusing more on AI-based Technologies?

With the overwhelming popularity of artificial intelligence (AI), every major tech company is transforming their processes and repackaging their research labs with a focus on AI. From Microsoft to Google to Amazon to Apple and Facebook, all are gearing up to face the new opportunities and challenges of the AI. Among all these major tech companies, Google has taken the most significant step in incorporating AI to its business processes more than any other brand. 

Just ahead of its developer congress event this year, Google named its research division as Google AI. The company further explained the move with the statement saying that the rebranding is part of its unflinching commitment to integrating AI into Google services. 

While Google will continue with its AI focus in branding and rebranding as well as optimizing services, we need to look into the reasons and impetus behind this enhanced focus. Let us inquire about various aspects that made Google focus more on AI-based technologies. 

Google Research Rebranded as Google AI Research 

With the Google Research being rebranded as Google AI Research, it is quite clear that the company is all set to bring in even the non-AI Research within AI Research hub. Though it is not clear as of now how far this will impact Google Research as a whole, this may incorporate the power of AI into traditional non-AI research projects as well.  

According to experts, a few broader perspectives can be spotted with this rebranding of Google Research. If you compare how other global tech companies are restructuring and rebranding their research facilities to create avenues for incorporating cutting-edge technologies, we can easily understand this as an industry trend and competitive phenomenon. Microsoft already rebranded its research facility as Microsoft AI+Research. Such moves are mainly motivated by the need for orienting the latest research with AI technologies. 

AI is becoming more powerful

Apart from the competitive factor that pushed Google to rebrand and orient its research lab with AI, the new and invigorated focus on AI has also resulted from the increasingly sophisticated AI technology. AI technology over the span of a few years went from strength to strength. From intelligent face detection to machine learning to productive modeling to natural language processing capability to more humanely voice interactions, AI-based algorithms and bots have become more powerful. 

If you look at face recognition and biometrics technology used in mobile apps, you should be amazed by the precision of most leading device platforms and apps. Hardly, the cutting-edge devices make any error and fail to do something it is meant for. 

Similarly, smart speaker systems continue to get better and more capable of driving interactions with users. Now even in a noisy room environment, the smart speaker of Google can detect the user’s voice and understand the spoken command. Even Google chief Sundar Pichai is amazed at the pace the voice recognition capability has progressed within a year or so. 

Other Google products also continue to get AI-powered improvements at regular intervals. From the search engine algorithm to the YouTube video suggestions to the Google AdWords catering audience-specific ads, all Google products are leveraging the power of AI for delivering more audience-centric, personalized and context-aware contents for the users. 

Google and Deep Learning AI 

To understand how Google made significant strides in incorporating AI in its services and app offerings for the millions of users, we also need to understand the impetus behind Google’s preference of deep learning. The deep learning earlier was first introduced by Google into its research labs and games. But soon it became a quintessential part of many of the Google services. 

Deep learning was first used for image recognition to help the photo search find the right of the image to the search context and query. As millions of images are indexed by Google for every niche, coming with the right image relevant to the search often becomes a challenging task. This is where deep learning AI plays a great role in making things simple and easy. From a mobile app development company to a business website, for businesses depending on visual content marketing, image recognition proves to be a key feature. When it comes to classifying images and delivering the best results against image searches, the technology proves to be really ideal. 

Google Cloud Video Intelligence

Google Cloud Video Intelligence is another key platform that by analyzing the video contents and their context can generate summaries automatically and deliver them as search results against meaningful and relevant searches. This video intelligence platform is also capable of sending security alerts in case any suspicious activity is detected.

Google Natural Language Processing (NLP)

Natural Language Processing is the sophisticated AI-based capability that gives many of the hi-tech services an edge in terms of better user experience and customer engagement. The natural language processing capability has been implemented by the Google Assistant by using deep neural networks in understanding spoken words and comments better irrespective of individual differences in tone, speech, pronunciation and voice modulation. The technology has also been introduced in the Google translation service, and a new platform called Google Neural Machine Translation has been created.

Conclusion 

With the huge and unprecedented success of AI technology in making Google services better and customer-centric, Google is more likely to implement AI in all future projects. From Google’s own cloud machine learning engine to the autonomous car division to the Deep Mind intelligent healthcare projects, AI will continue to play an elementary role across all futuristic Google projects across the spectrum.