MyFitnessPal, a popular, free food logging app, is getting into AI, specifically letting AI plan your meals for you. Following an acquisition of a startup called Intent, MyFitnessPal is adding an AI-generated meal planning feature for subscribers. The meal plans the updated MyFitnessPal app will be able to create take into account subscribers' "goals, preferences, dietary habits, and routines," according to MyFitnessPal, via information the app already has on you, and what looks like a survey. The feature will also be part of an end-to-end experience. Any plan the app creates can be automatically translated into a grocery list for the next time you're at the store, or an order to a grocery delivery service if you'd prefer to do as little as possible.

Today, Artifact is taking another jump on the generative-AI rocket ship in an attempt to address an annoying problem--clickbaity headlines. The app already offers a way for users to flag clickbait stories, and if multiple people tag an article, Artifact won't spread it. But, Systrom explains, sometimes the problem isn't with the story but the headline. It might promise too much, or mislead, or lure the reader into clicking just to find some information that's held back from the headline. From the publisher's viewpoint, winning more clicks is a big plus--but it's frustrating to users, who might feel they have been manipulated.

AI is transforming businesses and making them more efficient. The emerging technology is crucial in improving call center operations and helps companies to provide high customer satisfaction. The cloud call center solution is a perfect example of how businesses can use AI to streamline customer support. Let's discuss the critical role of AI in call center operations and how the call center software supports a company in delivering better CX. AI-powered Call Routing: AI has seeped into every aspect of call center operations and significantly improved the quality of call operations.

In this blog, we will discuss the technology trends of 2022. As we see there is a pace of evolution in the field of technology. As a result, humans have made rapid progress in technology in the last two decades. Technology has made a great impact in our lives. It's because of technology that we have access to many things at a single click.

As organizations begin strategizing how to bring employees back to the office, employers need to not only greet employees at the door with kindness and compassion, but build compassion into the heart of their return-to-office plans. Intrinsically, I know a compassionate workplace performs better than others; I've witnessed it over the years, especially this last year where we've needed understanding and support more than ever. Research also backs this up. Recently, I've been taking a closer look at how we can do this with artificial intelligence. With almost six decades of research and work in the field, I've seen AI detect facial expressions, detect fraud, create maintenance schedules for aircrafts and cars, understand emotions of customers and customer representatives from call center conversations, and more recently estimate the spread of Covid-19 and its economic impact.

Artificial intelligence and predictive analytics hold the promise of tackling the data burden and keeping risk predictions agile to external trends -- but they need to be applied strategically to present real value and minimize business risk. Historically, risk analysts have been able to make sense of complex yet structured data. Although nothing in these methodologies are broken per se, the way we use data is transforming irreversibly. For a business discipline that should offer exactly the opposite, it's clear that the standard practice needs to be adjusted to keep predictive analytics accurate. With the majority of all business services and consumer activity now taking place digitally, data is produced in vast, unprecedented volumes that are virtually impossible to neatly organize into structured, linear data sets for interrogation.

Many believe that cybersecurity is an exciting field to work in, and indeed it is. Yet being responsible for an organization's IT Security is no easy feat. Attackers always seem to be a few steps ahead of defenders. It often feels like a game of one against many – from petty criminals to nation-states. It would be highly advantageous if our cybersecurity tools could automatically adapt to these threats.

Artificial Intelligence-based testing can offer several benefits to testers in the form of enabling automation in writing test cases, improving test coverage, making predictive analysis, and identifying bugs early, and saving significant costs thereon. Quality testing has become a critical factor in ensuring that a software application delivers customer satisfaction. It involves assessing and analyzing the software application under certain conditions to know its threshold and attendant risks when implemented. However, with software build life cycles turning more complex and delivery turnarounds reducing, QA testers need to identify any inherent glitches in the application quickly and effectively. Thereupon, the information is passed on to the development team to fix the glitches and turn the application worthy of being delivered or implemented. The complexity of any software application under development has become more challenging due to the focus on quick releases. So, what used to take a month for delivery has become a weekly affair with updates factored in almost on a daily basis. This has made the job of software testers all the more challenging and has created conditions to make testing smarter, efficient, accurate, and predictive. No wonder AI-based testing has become the go-to area for testers to implement a continuous automated and precision-based testing process. In fact, AI testing has begun to play a critical role in quality control for a host of business and industry verticals. It helps to set in motion a slew of measures that is predictive, accurate, and objective. By freeing up human effort, AI-led quality assurance speeds up the SDLC to achieve outcomes as mandated by Agile and DevOps methodologies. Further, given that human testers have subjective biases, especially in a manual testing setup where the quality of testing can change according to the quality of the testers, Artificial Intelligence app testing delivers on parameters like speed, cost, accuracy, performance, safety, and scalability, seamlessly and effectively. AI can not only find glitches in the software application but perform root cause analysis to understand the source of such glitches. Benefits of using AI in QA testing Since orchestrating test automation across CI/CD pipelines has become challenging, AI testing services are used to enable smart testing in applications that have multiple dependencies, resources, and technologies. The benefits of using AI-based testing are as follows: Automation of writing test cases: One of the challenges QA testers face while conducting test automation is writing test cases. They often end up writing large test cases to detect a minor bug thereby impacting test efficiency. AI test automation can ensure the writing of precise test cases quickly and accurately. Besides, when developers/testers write test cases, instead of choosing the most efficient option – the one that generates the least redundant data, they write test cases that they are comfortable with. AI, on the other hand, can choose the most efficient test option where there would not be bottlenecks, manual involvement, or redundant data. Improve overall test coverage: AI-driven testing can expand the scope of testing by looking into the memory and file contents, data tables, or internal program states. This way it can determine if the software application is behaving as expected. AI can execute several test cases in every test run, which is not possible with manual testing. Identify bugs early and deliver cost savings: Bugs or glitches can be very expensive to fix if identified later in the SDLC. However, AI test automation can offer instant feedback to the developers about the presence of bugs and deliver significant cost savings. It is important to remember that the cost of fixing bugs after product release can be four to five times expensive than the ones identified in the SDLC. Predictive analysis: Artificial Intelligence can analyze the existing customer data to predict how customers’ browsing habits and needs would evolve. This helps developers and testers to be a step ahead of users’ choices and offer quality products or services in alignment with their expectations. With AI-ML testing, the test platforms get better at analyzing user behavior and making precise predictions. Conclusion In a day and age where going digital is the ultimate goal for enterprises to reach out to their customers and be competitive, AI-powered platforms have become a tangible reality. AI-based testing helps to optimize test automation and let the tests to self-heal and execute. It helps in automating more areas of testing such as UI testing and visual validation. By analyzing large volumes of data, Artificial Intelligence can create comprehensive and precise test cases to validate the smallest bugs in the system. The post What role does AI play in QA appeared first on NASSCOM Community |The Official Community of Indian IT Industry.

Comarch is a provider of complete IT solutions for telecoms, working with some of the worlds leading SPs: Vodafone, T-Mobile, Telefónica, E-Plus, KPN and MTS. For Total Telecom, Comarch are also a key partner at the annual Total Telecom Congress. With the 2021 now firmly underway, Total Telecom caught up with Rajmund Zielinski, IAA Product Manager at Comarch to get his thoughts one of the industries hottest topics: AI. In the wake of the coronavirus, digitalization has accelerated around the world and telcos are required to handle ever more data. How can operators use AI to gain value from this data?

You have already heard of AI being used widely today but do you know that is personalizing the searches for you? The search done by you and the recommendations that appear on the screen when you open your Google, Instagram, Facebook and other social media are all influenced by the AI. Apart from this, AI is widely used in various sectors be it the industries or in the medical field. Despite its lack of familiarity, AI is transforming the way you think and every walk of life. It is a tool that makes the people rethink about how to analyze data and improve decision making.