Exclusive Interview with Rahul Prasad, Co-founder, and CTO, Bobble AI

There is no parallel to chatting with friends because we express our truest emotions, how much ever nonsensical or raw be the words that we use. Many times, we fall short of words due to the language barrier, or lack of casual jargon that can depict the emotion exactly, which we accomplish through facial expression or body language during direct conversations. AI chatbots and conversational platforms could solve this problem to a large extent, but when it comes to overcoming the language barrier, there hasn't been much progress. Bobble AI says its AI-powered applications can help make the online conversations par real helping not only individuals but businesses to achieve superior user experiences. Analytics Insight has engaged in an exclusive interview with Rahul Prasad, Co-founder, and CTO, of Bobble AI.

Tell us how your company is contributing to the Big Data Analytics/Cloud Computing industry of the nation and how the company is benefiting the clients.

Bobble AI is an AI-powered company that is revolutionizing smartphone conversations and also the digital marketing space with its innovative solutions where data analytics is playing a crucial role in the above-mentioned ways

• Bobble AI is pioneering big data engineering and Analytics by using hybrid cloud and on-premise servers and ETL technologies like EMR and Glue for data processing
• Bobble AI adopted modern data lake house architecture that enables flexibility, cost efficiency, and scale  by enabling BI, Analytics, and ML on all the data
• Bobble AI delivers many competitive intelligence reports and analytics for its clients using a data lake house at scale in a very cost-efficient manner using serverless and dedicated warehouses.

 Kindly share your point of view on the current scenario of Big Data Analytics and its future.

Four important & crucial factors that explain the current scenario of Big Data Analytics and its future really well that I would like to highlight here in detail.

• Boom In The Data Marketplace
• Use of Data lakes gives rise to the data marketplace by combining more sources both external and internal.
• Buying and selling of data is more cost-effective and scalable

• Future of the data marketplace is to provide insights, competitive intelligence, and reports

• Decentralized data processing
• Blockchain technologies like the Oceans protocol are enabling companies to expose access to data processing without exposing actual data.

• Video and Audio processing
• Combining AI and big data, video and audio processing, and insights generation will be very accessible to organizations

• Emergence Of Cloud-Based Analytics Solutions
• Use of cloud computing adds greater flexibility and scalability for storing and analyzing the data beyond its native boundaries
• Cloud-based analysis provides a competitive edge to businesses by enhancing business information using huge data at scale from all sources
• The future of cloud-based analytics is limitless and continues to grow as more businesses will continue to adopt a cloud-first strategy by 2025

How is Artificial Intelligence is evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe? How is the Artificial Intelligence industry changing? What are some of the key technology transformations in this space?

AI is not a futuristic vision, but rather something that is here today and is being integrated with and deployed into a variety of sectors. This includes fields such as finance, national security, health care, criminal justice, transportation, and smart cities. There are numerous examples where AI already is making an impact on the world and augmenting human capabilities in significant ways. One of the reasons for the growing role of AI is the tremendous opportunities for economic development that it presents. A project undertaken by PriceWaterhouseCoopers estimated that "artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030."  China is making rapid strides because it has set a national goal of investing $150 billion in AI and becoming the global leader in this area by 2030.

How are disruptive technologies like Big Data analytics and Cloud Computing impacting today's innovation?

 Big data and analytics have had a deep impact on organizations' ability to better advance their decision-making, identifying areas to cut costs and allowing for massive economic gains, especially for startups and SMEs

Cloud-native analytics will empower the data analysts to align the right services with the right use cases, which might give birth to governance and integration overheads. The data and analytics leaders will also be required to prioritize workloads to exploit cloud capabilities like Cost Optimisations, change management, or large-scale migration to the clouds.

The efficient data processing capabilities of Business Intelligence software help companies around the world accomplish their corporate and data goals.

BI Software draws strength from Data preparation, distribution of data and KPIs, analytical queries, and information to drive business decisions.

The value of the global BI and analytics software market is expected to be 17.6 Bn USD by 2024.

What are the Predictions/ The Promise of Big Data Analytics?

As per my personal experience as a software engineer with a deep understanding & interest in Big Data Analytics I see a lot of opportunities that are possible and are taking shape very fast.

Big data technologies will become more powerful and useful with the help of proper data analysis. Data scientists help in collecting and analyzing data using tools to turn it into useful business insights. Today's data scientists and analysts draw handsome salaries.

As more and more research is being done on big data, it will become easier for normal users to do analysis on big data and come up with insights.

The more we research AI and BigData working together, the more people will just need to dump the data and AI models will figure out most of the insights without even needing to organize the data and run queries on organized data.

 What are your predictions on the promise of Artificial Intelligence?

AI promises considerable economic benefits, even as it disrupts the world of work. The time may have finally come for artificial intelligence (AI) after periods of hype followed by several "AI winters" over the past 60 years. AI now powers so many real-world applications, ranging from facial recognition to language translators and assistants like Siri and Alexa, that we barely notice it. Along with these consumer applications, companies across sectors are increasingly harnessing AI's power in their operations. Embracing AI promises considerable benefits for businesses and economies through its contributions to productivity growth and innovation. At the same time, AI's impact on work is likely to be profound. Some occupations, as well as demand for some skills, will decline, while others grow and many changes as people work alongside ever-evolving and increasingly capable machines. Several other factors have contributed to the recent progress. Exponentially more computing capacity has become available to train larger and more complex models; this has come through silicon-level innovation including the use of graphics processing units and tensor processing units, with more on the way. This capacity is being aggregated in hyper scale clusters, increasingly being made accessible to users through the cloud.

 Could you highlight your company's recent innovations in the Analytics space?

• We have created a Hybrid data lake that includes Multi-cloud and On-premise servers. Which is scalable, super fast, and also cost-effective.
• Conversation media marketing dashboard – with this dashboard a brand can measure the performance of their conversation media campaign.
• User profiling and data enrichment using machine learning to predict user's profile

Could you highlight your company's recent innovations in Artificial Intelligence?

Bobble being a Conversational AI-driven company, our primary need was to come up with AI models that can help us understand the language of our users. India has a splendid diversity in terms of cultures and languages are spoken. With 22 separate official languages recognized like Bengali, Marathi, Tamil, Telugu, etc., our urgent need was to power all these languages and help our users express themselves in a thoroughly personalized manner. We developed in-house AI models to support typing in each of these languages in a highly contextualized and personalized manner, keeping users' privacy and users' experience at the top. Our biggest challenge was to develop a framework for new age digitally enforced writing lingos called Hinglish, and Bengalish (where users type their own native language words, but use Latin characters). They are called Macaronic languages. To handle such languages, which have no vocab, and no set of grammar rules was the biggest challenge. We innovated this in-house and went on to deploy these models on-device, fulfilling all the edge device restrictions of size, latency, etc. We were immensely successful in this as we saw user adoption rising almost 20-30% after 3 months of deployment! We also went ahead to file patents for these models we architectured.

We also have deployed models which can capture the intent of the user, while he/she is typing, on the fly, and with the intents captured, we can show relevant products that they might want to buy, cabs they might want to book, order food instantly, right there while staying inside the conversation. The models adhere to privacy norms strictly, as they sit inside the mobiles and there's no data theft!

Suggesting the users, complete sentences while he/she has started typing certain characters/words with Smart Sentence Completion, on-device in Macaronic languages is also something we innovated recently and have filed a patent for. The technology we developed for this was completely indigenous and abides by all the edge device restrictions

While the above are clear products, we fuel our day-to-day business needs by developing unsupervised models which can understand the trends in data and render various insights on what the current pattern of conversation is like for example: how are users feeling about a certain mobile brand, or what are they searching the most on e-com sites like Amazon, etc. These are all powered by our in-house models which have the intelligence to understand the languages being spoken/written by our users.