AWS AI and Machine Learning is here to solve the big problems

23rd Oct 2019
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Amazon Web Services

Amazon Web Services

Today, there are definite use cases being deployed using Artificial intelligence (AI) and Machine learning (ML) with a much wider impact on the society in the areas of healthcare, education, travel, governance to name a few.


To evangelise and showcase the immense potential of AI and Machine Learning, Amazon Web Services (AWS), the cloud technology and service provider has been continuously interacting with ecosystem through events, demonstration of use cases and most importantly the progress these technologies have made till now.


One of the best ways to create awareness about AI and Machine Learning is to always reach out to the first port of call which is the developer community. The recent event in Bengaluru called the AWS AI & Machine Learning Day brought the ecosystem players together be it the developers, entrepreneurs, startups, technologists and venture capitalists. This ensured that there is a free flow of ideas, suggestions and much needed stimulation for the brain cells.

ML everywhere

Digbijoy Shukla, Head of Startup Ecosystem, India, Amazon Internet Services, said, “Our mission at AWS is to put ML in the hands of every developer.” He further remarked that Amazon has been engaged with AI and Machine Learning for the last 20 years in various forms.


Digbijoy Shukla, Head of Startup Ecosystem, India, Amazon Internet

Here, the critical driving force for AWS has been the Amazon SageMaker. This is a fully managed machine learning service and now data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production ready hosted environment.


The Amazon SageMaker has already found many use cases among startups like PolicyBazaar, Redbus, Shaadi.com to name a few where there have been very tangible and demonstrable results.


During the event, Redbus explained how it has deployed the various technology tools of Amazon especially Amazon SageMaker to solve some critical customer facing challenges. Given the amount of data this bus booking platform receives every minute, they had the challenge of creating credible user generated reviews for the users. “Amazon SageMaker has been revolutionary in solving the various continuous iterations we have in products,” said, Phaneesh Gururaj, Vice President – B2C Engineering, Redbus.


AWS has helped all these new age companies to scale and create a plug and tap architecture to provide that seamless end user experience.


For the startups, the partnership with AWS is very enriching as it much more than mere cloud credits and there are other features like stronger partner network, go-to-market strategy and also the launchpad for startups.


As Arun Gupta, Principal Technologist, AWS, said, “We want AWS to be the best platform to run your ML services.”


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Arun Gupta, Principal Technologist, AWS

Meet of perspectives

Any gathering is not complete unless there is the best of minds coming together to discuss, debate and expound their ideas. The panel discussion was on the topic: Building around recommendation engines, fraud and forecasting use-cases.


Movin Jain, vice president, products, Meesho, a social commerce startup was clear about their goal, “How do we reach the next 500 million users.” To achieve this target, it is quite clear that the technology platform of AWS would be the gateway.


At the same time, it is also equally important that technologies like AI and Machine Learning are more widely accepted within in an organisation. As Vijay Chidambaram, Vice President, Cloud Engineering, Manthan Systems said, “One needs to understand what the end consumer needs and have an internal structure which will facilitate the use of ML and AI.”


Technologies like ML and AI are critical for fintech startup like Razorpay especially while dealing with issues like fraud. Raju Shetty, head of Engineering, Razorpay felt that the need of the hour to have the technology to interpret the huge amount of data within a few minutes so as to understand the pattern.


The panelists were of the opinion that the biggest challenge for all the startups was definitely in the area of talent.


Voice of the customer

Tarkeshwar Thakur, VP Engineering, Freshworks took to the stage to talk on SageMaker, and how they, as a customer, are able to build their business using Amazon AI and ML services.


Tarkeshwar Thakur, VP Engineering, Freshworks

Tarkeshwar Thakur, VP Engineering, Freshworks


Money, talent and culture

There are technologies available on hand and smart techies are willing to harness the use cases but a critical element in this entire process will always be money. At the fireside chat which had the participation of Ashish Anantharaman, Co-founder & CTO, Zestmoney and Manish Singhal, Founding Partner, PI Ventures, very interesting insights came out.


Ashish said, “Raising funding is not easy and one needs to read the stories of successful entrepreneurs to keep oneself motivated as the rejection rate is high.” Though, he felt that this entire process is challenging, difficult but not impossible. In short, it was always the case of never giving up.


On the other hand, when it comes to investing in startups that are engaged with cutting edge technologies, Manish said, “There are no rules of investing in this area and one should take that leap of faith. AI is a means to solve a larger problem.”



Both felt that it is very important to build the culture within the organisation to attract the right kind of talent specially to deal with technologies like AI and ML.


In such events, there is always the eager participants who had multitude of questions around talent building, business development, gaining market share or just how to write a good code.


The march of AI and Machine Learning will continue and there is no force which will stop the advancement of these technologies. As Digbijoy said, “Our vision at AWS is to democratise the tools.”

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