Deloitte has launched an AI Institute to build an ecosystem in the country by integrating AI innovations and research for applications in various organisations. Called the ‘Deloitte AI Institute India,’ it aims to bridge the gap between organisations that embrace AI and those waiting for ‘the future’. Building AI solutions and skilling will be the priority of the institute.
India is currently in a vital phase of its infrastructure, energy, and mobility development, which nicely sets the stage to leapfrog current or existing practices. According to sources, an estimated 40% of its population will be living in urban areas by 2025, and they will account for over 60% of the consumption of resources.
Moreover, transportation in India is highly fragmented, disorganised across modes with poor infrastructure, congestion and low public transport density. Riders and drivers have to undertake multiple challenges daily such as lack of availability, reliability, quality, consistent pricing, safety etc.
“Our goal is to change the Indian mindset and help people replace their car with their phone by offering a range of mobility options — whether cars, bikes, autos or public transport — all in the Uber app. By putting more people in fewer cars, we have the potential to build smarter and more liveable cities,” said Andhare.
Using technology, Uber India has been trying to transform the mobility landscape and change how people move around in the country by playing a transformational role in addressing pain points for riders and adding efficiency into the system.
With its multi-modal vision for mobility in India, Uber wants to make a variety of options available to help commuters get where they want to go at a price point that works for them. To that end, Uber has announced partnerships across airports and Metros in Delhi and Hyderabad to provide last-mile connectivity.
Andhare said that about seven years ago, Uber launched in Bangalore with just three employees. Today, Uber India has tech teams across Bangalore and Hyderabad. It continues its exponential growth journey, focusing on facilitating affordable, reliable and convenient transportation to millions of riders and livelihood opportunities for hundreds of thousands of driver-partners.
The company has doubled its engineering team in India this year. The R&D teams located in Hyderabad and Bangalore continue to grow and currently host over a dozen global charters including rider, maps, customer obsession, infrastructure, money, and eats. These teams are driving global impact for Uber based on several India-first product innovations.
Andhare said, “With over a billion trips in India and South Asia and counting, along with a large driver-partner base, we are focused on winning hearts and minds in the market. We plan to do this by doubling down on products that can solve for low network connectivity, congestion and pollution, as well as enable multiple price points with a varied set of offerings. Uber’s success is deeply tied to our success in India, we are in a strong position in India, and we are committed to serving the market.”
He added, “As we gear up to deliver the next billion rides in the region, we remain focused on providing convenient, affordable rides to millions of riders and stable and sustainable earning opportunities to driver-partners.”
Andhare stated that technology provides an incredible opportunity to improve road safety in new and innovative ways before, during and after every ride. At every step, Uber is maximising the usage of technology to bring transparency and accountability through features such as two-way feedback and ratings, telematics and GPS, among others. These will have a positive impact on furthering trust and empathy between riders and driver-partners.
Uber’s Engineering Centre in Bangalore and Hyderabad are engaged in cutting-edge basic and applied technology solutions in areas that include rider growth, driver growth, digital payments, mapping, telematics, vehicle tracking/safety and fleet management, and the Uber core experience.
Some of the India-first innovations include the in-app emergency feature, arrears handling, driver inbound phone support, cash trips, Uber Rentals for longer trips and UberGO. The company is investing heavily in research and resources.
Some of the technologies used at Uber include computer vision, automation, Machine Learning(ML), Optical character recognition (OCR), and Artificial Intelligence (AI) techniques, NLP etc. These technologies are used in areas such as onboarding restaurant menus onto Uber marketplace, enabling earnings opportunities and more. It is also crucial to perform other tasks such as better routing, matching, fraud detection, document processing, maps editing, machine translations, customer support, and more.
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If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.
AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.
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Amsterdam and Helsinki both launched an Open AI Register at the Next Generation Internet Summit. According to sources, these two cities are the first in the world that are aiming to be open and transparent about the use of algorithms and AI in the cities.
Currently, in the beta version, Algorithm Register is an overview of the artificial intelligence systems and algorithms used by the City of Amsterdam. The register is an effort to show where the cities are currently making use of AI and how the algorithms work.
Jan Vapaavuori, Mayor of Helsinki stated, “Helsinki aims to be the city in the world that best capitalises on digitalisation. Digitalisation is strongly associated with the utilisation of artificial intelligence. With the help of artificial intelligence, we can give people in the city better services available anywhere and at any time. In the front rank with the City of Amsterdam, we are proud to tell everyone openly what we use Artificial Intelligence for.”
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The Government of India has recognised that an AI-driven economy can transform the lives of millions. Leveraging AI for inclusive growth is one of the core principles identified in NITI Aayog’s National Strategy paper. It is the path for much-needed job creation in various sectors, apart from creating new business opportunities and helping increase household incomes. But nationwide AI can only be done by creating datasets that combine these information systems that power e-schemes already established in India.
India’s AI revolution will require new architecture designs and upgraded technologies to make real-time decisions in an efficient manner. To integrate AI with Indian sectors, it will need a nationwide strategy that is centred on uniform AI standards and practices. Apart from that, an AI-centred smart economy will need extensive investment at technical and skills level. Hence, the government, along with private sector players, including manufacturers, service integrators, cloud service providers, etc., need to come together and coordinate in the development of an AI framework.
What are the various steps that are being taken when it comes to establishing a technical framework for the adoption of AI in India?
There are technical challenges in the form of scalable and robust platforms that can ingest zettabytes of large data sets. In a recent discussion paper, India’s AI Standardisation Committee has outlined the issues related to developing a framework of an Indian AI stack.
This paper proposes a stack that seeks to remove the impediments to AI deployment by putting in place a comprehensive framework. A framework that will create an enabling environment to exploit AI productively in various walks of life. This will enable the development of a suitable AI stack with a different mix of layers and interfaces that complements each other and achieves integration.
One of the major advantages of this proposed Indian AI stack is that it will facilitate open API integration and build the AI architecture from the ground up. It also ensures the creation of a common Data controller, including multi-cloud scenarios-private and public, as part of the infrastructure layer.
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India’s AI tech leaves something to be desired. Ironically, a sizable chunk of engineers working for tech companies like Google, Microsoft, Apple, Facebook and Amazon are Indians. According to Seattle Times, close to 70% of Indian H1B visa holders in the US work in the tech industry, from just under 40% in 2003.
The International Monetary Fund (IMF) has ranked India as the seventh-largest economy, down from the sixth position in 2020 and fifth in 2019. The relegation is chalked up to the pandemic crisis. Now, with the rising number of COVID-19 cases and deaths, India’s future looks bleak.
It is high time Indian companies and industry leaders started focusing on enhancing tech capabilities and developing core artificial intelligence (AI) products in India instead of relying on foreign firms.
Today, most tech companies have the money to acquire startups making strides in AI. Unfortunately, India does not have a tech giant, nor a billionaire agent provocateur like Elon Musk.
As companies began developing digital applications for customers during the pandemic, the interest in application programming interface (API) and low-code, no-code technology platforms grew significantly. Today, such solutions are mainly offered by technology companies such as Microsoft, Amazon, Appian, Pega, OpenAI and Service Now.
In India, however, very few companies, including Infosys, HCL Technologies and Tech Mahindra, are working on low-code, no-code technology platforms. Indian companies can add value by developing state-of-the-art APIs and coding platforms that are easy to use and scalable.
For machine learning engineers and data scientists, notebooks have become an integral tool. Notebooks are highly interactive multi-purpose tools to write and execute code and analyse intermediate results to gain insights while working on a project. Notable tools include Jupyter Notebook, Kaggle Notebook, Colab, Gradient, Deepnote, Saturn Cloud, and Polynote. Unfortunately, there aren’t any machine learning notebooks from India.
With supervised learning being the most common form of machine learning technique used by companies today, there is a need for labelled or annotated data across images, audio, video and text formats across sectors, and companies developing data labelling tools and feature stores (open-source as well proprietary) becomes crucial for enterprises’ machine learning strategy.
According to Grandview Research, the global data labelling market is expected to touch $8.2 billion by 2028, from $1.3 billion in 2020. The market is expected to grow at a CAGR of 25.6% from 2021 to 2028.
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