
To get a perspective on Google’s cloud services in India, talking to Debashis Roy, vice president-IT of CESC, the Sanjiv Goenka-owned power distribution company, helps.
A couple of years ago, every company in the $2.7 billion RP-Sanjiv Goenka Group had a different domain name for emails, lacking uniformity. Roy migrated all employee emails — 6,500 of them — to Google Cloud. For a legacy company, which traces its roots to pre-Independence India, having information stored in servers in remote destinations owned by Google, in different parts of the world, was a big culture shift.
After putting emails in the cloud, Roy has taken the next step. He is running two pilots using Google’s machine learning (ML) and artificial intelligence (AI) services to improve customer satisfaction, reduce operating time, and boost revenue.
Take the process of collecting electric meter readings prior to cash collection from customers. It was mostly a manual data-entry job. In one of the pilots, Roy has given meter readers Android devices and installed a proprietary app, which allows them to either key in the reading, or speak into the phone, or just take a picture. In the backend, Roy explains, the software decodes the text, voice or picture, and generates the bill. And, what’s more, the meter reader can speak into the phone in his native language.
In one of the pilots, Roy has given meter readers Android devices and installed a proprietary app, which allows them to either key-in the reading, or speak into the phone, or just take a picture
Google does not only want to make its own services better by using AI and ML, it wants small, medium and large companies to rent its AI and ML platforms to run projects.
Although Google’s entry into the fast-growing (and immensely profitable) domain of cloud storage and computing services has been somewhat late, which has allowed competitors, especially Amazon Web Services (AWS) to take a big lead, Google’s cloud services are being touted by the company as a game-changer because of its built-in AI and Machine Learning capabilities.
While AWS and Microsoft (Azure) offer renting and processing data on the cloud, Google provides a lot more to its enterprise customers, which includes hearing, listening, translation, sifting through tons of data to perform tasks, using ML and AI. It also launched a new AI chipset during its recent Google I/O conference, which it has been using internally to run its own AI and ML services. The new chip not only runs neural networks (a computer that is like the human brain and nervous system, and is ‘self-learning’), it also trains them — capabilities that Amazon and Microsoft do not have at present. Even Intel has been struggling to launch its AI-enabled processor.
Google’s cloud services are being touted by the company as a game-changer because of its built-in AI and Machine Learning capabilities.
Amazon and Microsoft allow graphics processor-maker nVidia chips to power AI and ML projects for their clients, but none of them have bespoke chips like Google does.
So, are AI and ML Google’s biggest weapons to transform the enterprise cloud services business and fend itself from competition?
Both ML and AI are required for three things, explains Pande: when a lot of data is required to be processed; need of algorithms to built a framework for ML; and a lot of processing power. Google internally handles all of those — it has seven businesses, including Gmail, Maps and YouTube, with more than a billion users each.
Google does not only want to make its own services better by using AI and ML, it wants small, medium and large companies to rent its AI and ML platforms to run projects.
In India, an insurance company that can’t be named is using Google cloud with ML capabilities to estimate damages for accident claims through pictures, instead of sending a surveyor. Google’s vision API figures out the damage and generates a quote.
Customer service teams are using Google’s cloud-based services to understand the mood of the caller, if he/she is angry, sad, happy or irritated, using natural language API. These data-sets can be further used for internal training purposes.
In other cases, Pande explains that companies can use video intelligence APIs to search and tag videos automatically. “The software understands if you upload a clipping… if the picture is of a pizza delivery point, or a man in a red shirt, or on a yellow scooter and it will give you the ten thousand tags and it will take you exactly to the position where you want to be,” says Pande, quoting the example of a restaurant using the cloud services to streamline home-delivery of food.
Financial companies are using Google’s cloud services for fraud and theft detection, healthcare companies are using it for genome research, oil and mining companies for geological explorations, and retail and e-commerce companies are using it to figure out the next logical purchase for customers.
Some of this is being used by online real estate company NoBroker to identify rooms, apartments, find the owner’s credentials, and figure out the condition of the property. “No one goes to check these properties. Google scans through the images, names the bedroom as a bedroom. We don’t engage any human being to do this,” says Akhil Gupta, CEO and founder of NoBroker.
Google has helped Gupta reduce 12% of its staff and engage them in other work. He also says that even if the company expands into 50 or 100 cities, he will not have to hire people to do this job.
Most of Google’s services come with a hint of AI and ML. Even the basic Gmail has been upgraded with new features of automated replies, depending your mailing behaviour. Google Maps has AI and ML layers. For example, an insurance company can decide on a customer’s premium based on where she stays in Mumbai. Using Google Maps, and adding AI and ML to it, companies will be able to figure out flood-prone areas and assess damage.
Most of Google’s services come with a hint of AI and ML. Even the basic Gmail has been upgraded with new features of automated replies, depending your mailing behaviour.