Airtel Invests in AI Startup

Airtel is strategically investing in new startups to increase its service quality and revenue. In return, new startups get a platform to explore and expand from the wide range of experience Airtel has. The telco even recorded a rise in Average Revenue Per User, which is a critical measure in the telecom sector.

Crux of the Matter

Telcos’ Modern Warfare: AI
Airtel invested in conversational artificial intelligence (AI) technologies based startup Voicezen. Voicezen is working on developing advanced solutions that leverage machine learning, speech to text, AI, and voice technologies to offer real-time analytics to provide better customer services. Even Vodafone launched VIC, AI-powered digital customer service, and support virtual assistant. Reliance Jio is also working on natural language processing and AI-based chatbot developed by startups like Reverie and Haptik.

Airtel’s Strategic Investments
Airtel’s Startup Accelerator Programme aims to support the startup ecosystem contributing to Digital India. Startups get the benefit from Airtel’s online and offline distribution network, deep market understanding, the ecosystem of global strategic partners, and advisory services from Airtel’s executive team.

Today, early-stage startups in India have some very exciting ideas but face multiple challenges in scaling up. With Airtel’s scale and digital capabilities around distribution and payments, we have the potential to drive accelerated growth of emerging startups that are solving hard problems.

Adarsh Nair, Chief Product Officer of Bharti Airtel

So far Airtel has invested in three startups i.e. Voicezen, Vahan Inc., and Spectacom. Vahan focuses on developing the online platform dedicated to finding blue-collar jobs in India. Whereas, Airtel is helping Spectacom to spread awareness about its health and fitness platform and soon-to-be-launched fitness platform ‘X sport’ similar to the ‘Airtel X stream’ platform. Telcos seem to be collaborating with Tech firms to increase revenue and improve customer services. In recent, Reliance Jio has announced a series of deals with Tech giants or Investors backing tech firms.

Airtel Preparing for Big?
Recent Airtel’s deal with Nokia is expected to lay the foundation of 5G for it. 6.4 billion subscribers of Nokia will help Airtel to expand and enhance its capacity and revenue.

Even AI market size is expected to grow from $4.2 billion in 2019 to $15.7 billion by 2024. Increased working efficiency with the accuracy of AI is a major factor in the increase in its demand across the globe.

Airtel’s Jan-Mar quarter revenue grew by 15% YoY to ₹23,723 crores from ₹20,602 crores compared to last year. Currently Airtel’s average revenue per user is ₹154 which is higher than Jio’s ARPU of ₹130.6.

  • Sunil Bharti Mittal is an Indian billionaire entrepreneur, philanthropist, and the founder and chairman of Bharti Enterprises. In 2007, he was awarded the Padma Bhushan, India’s third-highest civilian honor. And as of April 2020, he is listed as the 6th richest person in India by Forbes with a net worth of $8.2 billion.
  • The world’s sixth-largest mobile messaging application Hike Messenger was launched on 12 December 2012 by Kavin Bharti Mittal and is now owned by Hike Private Limited. Kavin Bharti Mittal is the son of Sunil Mittal, founder of Bharti Enterprise.
  • Airtel is one of the largest mobile network operators in the world with over 400 million subscribers. Airtel was named India’s 2nd most valuable brand in the first-ever Brandz ranking by Millward Brown and WPP plc.

Memes by AI

Artificial Intelligence has stepped into the domain of creating humor. A software called “This Meme Does Not Exist” was made using Machine Learning techniques to generate memes.

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What Can AI Not Do?
Imgflip has made an AI meme generator called “This Meme Does Not Exist”. Its founder is Dylan Wenzlau. He trained AI using 48 most famous memes and 20,000 captions for each. This machine generates meme character by character. In the middle of a pandemic, the world is witnessing the creation of humor by AI.

Since we are building a generational model there will be one training example for each character in the caption, totaling ~45,000,000 training examples. Character-level generation rather than word-level was chosen here because memes tend to use spelling and grammar … uh … creatively.

Dylan Wenzlau, Founder, Imgflip

The Marriage of AI and Creativity
Use of AI and Machine Learning in creating content, music, writing songs, etc. is on the rise. OpenAI project developed a language software that could match human capabilities. Many experts believe that AI works more efficiently for creating hyper-personalized content. With the advent of AI in the field of creation, some content marketers are preferring AI over human content.

  • The term ‘meme’ was coined in 1976 by evolutionary biologist Richard Dawkins. It is derived from the Greek word “mimema” that suggests how an organism can mutate and spread itself by communicating essential knowledge of the surrounding.
  • A Google Trend comparison of words meme and Jesus – the world’s largest religion, shows that meme is searched on average 2-3 folds more than Jesus.
  • The study of mathematical logic led directly to Alan Turing’s theory of computation, which suggested that a machine, by shuffling symbols as simple as “0” and “1”, could simulate any conceivable act of mathematical deduction. This insight, that digital computers can simulate any process of formal reasoning, is known as the Church-Turing thesis.

Age of AI : Researchers develop agents that take human-like creative decisions


Researchers at Carnegie Mellon University and Pennsylvania State University, USA have developed trained AI agents that are are able to adopt human design strategies for creative and exploratory decision making, using neural networks. The study was co-authored by Jonathan Cagan, professor of mechanical engineering and Ayush Raina, a PhD candidate along with Chris McComb, an assistant professor of engineering design. The findings were published in the reputed ASME Journal of Mechanical Design.

Crux of the Matter

Is AI an Army of Robots Out to Kill Us?
AI or Artificial Intelligence is giving the abilities to a machine for performing a task that reduces human effort. According to the father of AI, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”. AI is dominant in fields like Gaming, Expert Systems, Vision Systems, Natural Language Processing (NLP) and Speech Recognition.

What was This Study About?
When engineers use AI, they simply apply it to a problem within a defined set of rules rather than having it generally follow human strategies to create something new. The framework in this study was made up of multiple deep neural networks that worked together in a prediction-based situation by looking through a set of five sequential images and estimating the output of the next design.

Then an AI framework learns human design strategies through observation of human data to generate new designs without explicit goal information, bias, or guidance. Visualization was thereby emphasized in the process because vision is an integral part of how humans perceive the world and go about solving problems.

So How Good can this AI be?
According to Cagan, quite good as he says, “The AI is not just mimicking or regurgitating solutions that already exist. It’s learning how people solve a specific type of problem and creating new design solutions from scratch.”

In times ahead, they would have to tackle truss problems and derive new strategies for it. Commonly seen in bridges, a truss is an assembly of rods forming a complete structure and their problems represent complex engineering design challenges.


A neural network – is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. They can also adapt to changing input, in order to make the network generates the best possible result without needing to redesign the output criteria. This network works similarly to the human brain’s neural network contains layers of interconnected nodes. A “neuron” in a neural network is a mathematical function that collects and classifies information according to a specific architecture. The network bears a strong resemblance to statistical methods such as curve fitting and regression analysis. More Info

Researchers from IIT-M lay foundation stone for AI Development

IIT Madras is all set to develop AISoft, an artificial intelligence solution for solving engineering problems and FairKM, a software that can remove caste, race and sex bias from AI. Both developed software can work with sparse data sets and this makes them stand out when compared to other commercially available software.

Crux of the Matter

Dream Team
A team of researchers led by Vishal Nandigana, assistant professor, Department of Mechanical Engineering, IIT-Madras developed the AI and Deep Learning algorithms for AISoft. The formed flow models can develop solutions to engineering problems in fields such as thermal management, semiconductors, aerospace, and electronic cooling applications.

Need for Removing Bias
AI algorithms learn from human behavior and if the human behavior is biased the AI is automatically biased. There were ‘fair clustering’ techniques that were already prevalent but they could only incorporate one parameter. Dr. Deepak Padmanabhan’s FairKM can take into consideration multiple parameters including various kinds of biases.

Future Impact
The AISoft idea being new is looked upon by various research groups around the world, who can further use Convolutional Neural Networks (CNN) or Conditional Generative Adversarial network (C-GAN) for required output generation. The FairKM can be put to immediate use in the third world and developing countries that are often criticized for bias in terms of ‘sensitive attributes’.


Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. ANNs have various differences from biological brains. Specifically, neural networks tend to be static and symbolic, while the biological brain of most living organisms is dynamic (plastic) and analog. More Info

Future of AI: Can Morals and Scientific Advancement Go Hand in Hand?

Deep researches have been going on in Artificial Intelligence (AI), its use in facial recognition and AI chatbots, etc. But this has also posed a threat to societal elements. Thus tech leaders have urged to set global standards on how to use Advanced Technology.

Crux of the Matter
  • Leading Tech giants like Microsoft, Tesla, IMB and Google had made a call on past Monday for change in the regulation policies related to Artificial Intelligence.
  • Taking into account the dark side of AI, Elon Musk CEO of SpaceX said that “If not regulated or controlled soon, AI could become an “immortal dictator” and there will be no escape for humans.”
  • Understanding the responsibility on his shoulder, Sunder Pichai CEO of Google and Alphabet, said, “There is no question that we need regulation and laws regarding AI at global level but how to approach it is bigger deal.”
  • He further added “Companies such as ours cannot just build promising new technology and let market forces decide how it will be used. It is equally incumbent on us to make sure that technology is harnessed for good and available to everyone”.
  • IMB chief Ginni Rometty said, “artificial intelligence regulations must be crafted with precise regulations and technology can’t flourish at the cost of social security.”
  • She further points out that technology is not an issue but the way it can be used is a potential threat for us.

Machine ethics (or machine morality) is the field of research concerned with designing Artificial Moral Agents (AMAs), robots or artificially intelligent computers that behave morally or as though moral. To account for the nature of these agents, it has been suggested to consider certain philosophical ideas, like the standard characterizations of agency, rational agency, moral agency, and artificial agency, which are related to the concept of AMAs. More Info

Ethical Tech – There is one technology in particular that could truly bring the possibility of robots with moral competence to reality. In a paper on the acquisition of moral values by robots, Nayef Al-Rodhan mentions the case of neuromorphic chips, which aim to process information similarly to humans, nonlinearly and with millions of interconnected artificial neurons. Robots embedded with neuromorphic technology could learn and develop knowledge in a uniquely humanlike way. Inevitably, this raises the question of the environment in which such robots would learn about the world and whose morality they would inherit – or if they end up developing human ‘weaknesses’ as well: selfishness, a pro-survival attitude, hesitation, etc. More Info