Vistara is among India's top airlines, with an operating landscape of more than 40 destinations (both domestic and international) using a fleet of 54 aircraft. The airline has flown over 35 million customers since its inception, of which 5 million were flown between March to July 2022. According to Vinod Bhat, CIO, Vistara, the organisation's key priorities have always revolved around a seamless customer experience, and how the company can work towards elevating it to the next level. "To ensure that, we have strived to maintain the right balance of value for our customers and cost efficiency. Another important aspect is making sure that our infrastructure is resilient. We have been rapidly investing in IT infrastructure and new digital technologies that are easily adaptable and scalable to further enhance customer experience," he says.

In our series- Behind The Code, we reach out to the developers from the community to gain insights on how their journey started in the field of emerging technologies, the tools and skills they use and what they think essential for their day-to-day operations. For this week's column, Analytics India Magazine caught up with Sathyajith Bhat, a Site Reliability Engineer (SRE) at Adobe. Bhat has been working at Adobe for a few years now and currently working as an SRE for Adobe I/O with the API Platform team. As one of the AWS Community Heroes, Bhat will also be talking about Fargate at this year's AWS re:Invent. At the start of this journey, Bhat faced some initial challenges while trying to understand and apply some classical algorithms.

Most people know about one of the greatest salespeople of all time, Steve Jobs. When Jobs introduced the first iPhone, in January of 2007, he had to convince a skeptical world to pay a then-outrageous sum of $600 for a phone made by a company that had never produced a handset before, with a slick back and no physical keyboard to peck out emails. It was a creative act on Jobs's part, an ability to craft a vision of how the world would be and to convince people their lives would be better in that world if they bought his shiny new object. That creative act poses a challenge for a raft of software startups trying to use artificial intelligence to reinvent sales. Companies including Vymo, InsideSales, SalesLoft, and Outreach have gotten hundreds of millions in financing in the last few years, in hopes that by mining historical data such as emails and customer call logs, they can figure out what the best salespeople do.

Most people know about one of the greatest salespeople of all time, Steve Jobs. When Jobs introduced the first iPhone, in January of 2007, he had to convince a skeptical world to pay a then-outrageous sum of $600 for a phone made by a company that had never produced a handset before, with a slick back and no physical keyboard to peck out emails. It was a creative act on Jobs's part, an ability to craft a vision of how the world would be and to convince people their lives would be better in that world if they bought his shiny new object. That creative act poses a challenge for a raft of software startups trying to use artificial intelligence to reinvent sales. Companies including Vymo, InsideSales, SalesLoft, and Outreach have gotten hundreds of millions in financing in the last few years, in hopes that by mining historical data such as emails and customer call logs, they can figure out what the best salespeople do.

Vymo, a software-as-a-service start-up, is gearing up for expansion across Asia Pacific, following a round of engagements with key banking and insurance customers. On the back of customer success in Singapore and Hong Kong, the start-up is currently building strong pipeline within the wider region. As part of this expansion, Anurag Srivastava, former head of financial services at Kofax, has been appointed head of APAC for the business, reporting directly to CEO, Yamini Bhat. "We will follow this up with building the regional capability of customer success, delivery and support teams in key strategic markets in Asia Pacific apart from relationships with cloud solution providers and services partners for local deployments," Bhat said. A developer of an AI-personal assistant used by some leading banks and insurers sees the APAC region as a major growth opportunity.

Since the late 1980s particle physicists have used AI even as the concept of a neural network was barely in the public's consciousness. AI and particle physics go hand in hand as the experiments the physicists perform usually revolves around seeking out patterns in the data from particle detectors and AI is excellent at pattern detection. Boaz Klima, a Physicists from the Fermi National Accelerator Laboratory, also called Fermilab, says "It took us several years to convince people that this is not just some magic, hocus-pocus, black box stuff." He was amongst the first to adopt AI tools but today, it's a part of standard particle physics practices. Usually, particle physicists aim to comprehend the way the inner gears of the universe works, typically by colliding subatomic particles at hit speeds to break them down into even smaller and more unusual kinds of matter.

Chennai: Why pay a common motor insurance premium if you're statistically safer than the rest of the demographic? Insurance companies are aggregating customer data to gauge premiums dynamically. If you are a middle aged man with two kids and drive an SUV, your premiums will be lesser than a 25 year old youth who just got his first sedan. AI and data analytics is changing the sales game rapidly, equipping sales personnel with the right tools and data so they improve conversions and save time. The next time you go to a shop and your favourite dress is out of stock, the salesperson at the counter would take in your order and source it from the neighbouring retail store and earn brownie points.

New technologies actually end up creating different, higher-paying jobs than the ones they replace, according to new research. Fears of "technological unemployment," a term coined by renowned economist John Maynard Keynes in 1930, and recently popularized by MIT Sloan professors Erik Brynjolfsson and Andrew McAfee, are rampant. The worry is that computer-driven automation will take over repetitive tasks across a swath of industries, from retail and financial services to manufacturing and, maybe sooner than we realize, taxicabs and trucking. It turns out, however, that new technologies--most notably AI--aren't harbingers of the so-called robot apocalypse. "Throughout history, automation commonly creates more, and better-paying, jobs than it destroys," writes The Wall Street Journal's Greg Ip. "The reason: Companies don't use automation simply to produce the same thing more cheaply. Instead, they find ways to offer entirely new, improved products. As customers flock to these new offerings, companies have to hire more people."

Google is set to let users pay off their debts without lifting a finger. The tech giant has announced a new feature that will allow users to transfer funds to friends or family via Google Assistant. Those living in the US will just say'Ok Google, send $10 to Jane for pizza', and the AI will pull money from a linked debit card and forward it to the recipient. Google announced a new feature that will allow users to transfer funds to friends or family via Google Assistant. Those living in the US will just say'Ok Google, send $25 to Manuel Martinez', and the AI will pull money from a linked debit card and forward it to the recipient Google is rolling out a feature that lets users add a credit or debit card to their Google Account, enabling them to easily purchase goods online without.

This My thesis work combines AI, programming language design, incompleteness of perception and dynamism in the environment and software engineering. I am integrating reinforcement creates a strong need for adaptivity. Programming this learning (RL) into a programming language so adaptivity by hand in a language that does not provide builtin that the language achieves three primary goals: accessibility, support for adaptivity is very cumbersome. As I demonstrated adaptivity, and modularity. If I am successful, my or designer specifies the structure of certain parts work will enable a discipline of modular large-scale agent of a program while leaving other portions unspecified, such software engineering while making advanced agent modeling that a learning system can learn how to perform them.