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The AI Behind FaceApp - Analytics India Magazine
When released back in 2017 for iOS and Android devices, this AI-based face changing/photo editing app — FaceApp took the internet by storm. And with its mind-boggling results, it also created a major kerfuffle on social media platforms like Facebook, Twitter and Instagram, where everybody including celebrities was using the app to transform their selfies to see their “older version.” At the inception, the app was renowned for its ethnicity filters, but later it evolved with a lot of features.
Read more: https://analyticsindiamag.com/the-ai-behind-faceapp/
#artificial-intelligence #photoeditingapp #algorithm #gans
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AI & Data Science India Salary Study - 2021
The annual Analytics India Salary report presented by AIM and AnalytixLabs is the only annual study in India that delves into salary trends and provides a comprehensive view of the changing landscape of analytics salaries. The report, now in its seventh year, look at the distribution of average salaries across several categories including years of experience, metropolitan regions, industries, education levels, gender, tools, and skills.
The Data Analytics function is experiencing significant growth and development in terms of skills, capabilities, and funding. Last year, despite the pandemic, the Indian start-up industry witnessed $836.3 million investment, almost a 10% (9.7%) increase than the previous year. Also, more than one in five (21%) analytics teams across firms in India witnessed a growth in the last 12 months and the post-pandemic job market saw an upswing of data science jobs. The development of the data science domain is evidenced by the high salaries drawn by analytics professionals across the organization, with Analytics professionals doing relatively well in spite of the pandemic.
#featured #ai salaries in india #analytics salaries in india #analytics salary key trends #analytics salary trend #average data analytics salary #average salary of analytics professionals #data science salaries in india #data science salary study #latest data science salaries
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Uber’s Success Is Deeply Tied To Its Success In India: Shirish Andhare
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.
To know more about the current space and transportation in India, Analytics India Magazine caught up with Shirish Andhare, Director, Program Management, Uber India and South Asia.
“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.
Transformation of Uber India
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.”
Deep Tech At Uber
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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Making Sales More Efficient: Lead Qualification Using AI
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.
#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution
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What Does India Need In Place To Implement Nationwide AI Systems Across Sectors?
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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The Last Call to Adopt AI - Analytics India Magazine
The coming decade will have no patience for businesses with old ways of working. Companies that continue to deliberate on adopting AI technologies will find themselves brutally snared between digital-born companies with inherent AI drivers and early adopters with highly operational AI, steadily losing customers over a widening gap in quality and intuitiveness of offerings. The time for organizations to be on the fence with AI is over.
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