Zeta, a global fintech company revolutionising the digital banking and enterprise payments space, is expanding due to the global appetite for a more decentralised banking experience.

On many evenings during spring and fall migration, tens of millions of birds take flight at sunset and pass over our heads, unseen in the night sky. Though these flights have been recorded for decades by the National Weather Services' network of constantly scanning weather radars, until recently these data have been mostly out of reach for bird researchers. That's because the sheer magnitude of information and lack of tools to analyze it made only limited studies possible, says artificial intelligence (AI) researcher Dan Sheldon at the University of Massachusetts Amherst. Ornithologists and ecologists with the time and expertise to analyze individual radar images could clearly see patterns that allowed them to discriminate precipitation from birds and study migration, he adds. But the massive amount of information – over 200 million images and hundreds of terabytes of data – significantly limited their ability to sample enough nights, over enough years and in enough locations to be useful in characterizing, let alone tracking, seasonal, continent-wide migrations, he explains.

WASHINGTON DC: Researchers discovered that modern machine learning, a branch of artificial intelligence may augment the traditional way of diagnosing kidney disease. Pathologists often classify various kidney diseases on the basis of visual assessments of biopsies from patients' kidneys; however, machine learning has the potential to automate and augment the accuracy of classifications. In one study, a team led by Pinaki Sarder, PhD and Brandon Ginley, BS (Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo) developed a computational algorithm to detect the severity of diabetic kidney disease without human intervention. The algorithm examined a digital image of a patient's kidney biopsy at the microscopic level and extracted information on glomeruli, the small blood vessels of the kidney that filter waste from the blood for excretion. These structures are known to become progressively damaged and scarred over the course of diabetes, reported the study published in the journal -- journal of the American Society of Nephrology.

Bengaluru: As India's second mission to the moon, Chandrayaan-2, is poised to make a soft landing on the southern surface of the moon in the early hours of Saturday, the artificial intelligence (AI)-powered rover of the Indian Space Research Organization (ISRO), will play a significant role in this mission's success. Christened'Pragyan' (wisdom in Sanskrit), the homegrown solar-powered robotic vehicle that will manoeuvre the lunar surface on six wheels, comprises a Laser Induced Breakdown Spectroscope (LIBS) from the Laboratory for Electro Optic Systems (LEOS) in Bengaluru to identify elements present near the landing site, and an Alpha Particle Induced X-ray Spectroscope (APIXS) from the Physical Research Laboratory (PRL) in Ahmedabad that will inspect the composition of the elements near the landing site. The AI-powered Pragyan rover, which can communicate only with the Lander, includes a piece of motion technology developed by IIT-Kanpur researchers that will help the rover manoeuvre on the surface of the moon and aid in landing. The algorithm will help the rover trace water and other minerals on the lunar surface, and also send pictures for research and examination. Homegrown Pragyan is simply a case in point that AI has been gathering pace in space exploration over the years.

A maverick is a person of incredible vision, someone who challenges the norm and forces people to think beyond the ordinary. YourStory is going behind the scenes to uncover the inspirations and secrets of the ultimate maverick in the business world: the entrepreneur. For what is innovation but doing things differently? And as a woman in tech who doesn't code, Ashwini Asokan certainly does not all the stereotypes. At Mad Street Den, the AI startup which she launched in 2013 in Chennai along with her husband Anand Chandrasekaran, Ashwini fills in the shoes of the CEO (with her husband as the CTO).

Facebook is spearheading a competition to find new ways to identify computer-altered videos known as "deepfakes." But some artificial-intelligence specialists say the strategy might backfire. Those experts say the contest will probably hasten the already accelerating arms race between the malicious actors using AI to create increasingly realistic faked videos, and the technology companies racing to detect them. "Any algorithm used to identify deepfakes could also be used to make deepfakes better," says Rachel Thomas, a co-founder of machine-learning lab Fast.ai. Already, top artificial-intelligence researchers across the country have been racing to defuse the computer-generated fake videos as fears grow that they could undermine candidates and mislead voters in the lead-up to the 2020 presidential election.

Can artificial intelligence turn out symphonies to match one of the greats of classical music? That was the question posed by one unusual orchestra performance in the Austrian city of Linz on Friday, in which Gustav Mahler's unfinished Symphony No.10 was played -- immediately followed by six minutes of "Mahleresque" music written by software. The project's creator says that the two are clearly distinguishable but not everyone in the audience agreed. "I couldn't really feel the difference... I believe it was really well done," Maria Jose Sanchez Varela, 34, a science and philosophy researcher from Mexico, told AFP.

Homegrown internet startup Hike describes that social products should be joyful. They should be built around people and not the other way around. They should be fun and should celebrate the depth of relationships. They should allow people to be their true selves and go beyond the limits that hold them back in the real world. And following the same, their messenger app is built around the same values and policies.

Biotechnology, pharmaceutical, and life sciences industries are where applied artificial intelligence (AI) can greatly accelerate innovation and shorten the product development life-cycle. Developing a drug typically takes 10 to 15 years on average, with only approximately 12 percent of drugs in clinical trials ultimately gaining U.S. Food and Drug Administration (FDA) approval. In an AI milestone in life sciences, Insilico Medicine announced a new machine learning tool for drug discovery that can generate a novel molecule in days instead of years and published their findings in Nature Biotechnology on September 2, 2019. Insilico Medicine is a venture-backed start-up with multiple investors that include WuXi AppTec, Juvenescence, Peter Diamandis' BOLD Capital Partners, and Pavilion Capital. Led by CEO and Founder Alex Zhavoronkov, the company's mission is to extend longevity by applied AI solutions for drug discovery and aging research.

Nashville, TN Choosing the right evaluation metric for your machine learning project is crucial, as it decides which model you'll ultimately use. Those coming to ML from software development are often self-taught, but practice exercises and competitions generally dictate the evaluation metric. In a real-world scenario, how do you choose an appropriate metric? This talk will explore the important evaluation metrics used in regression and classification tasks, their pros and cons, and how to make a smart decision.