The Institute of Chartered Accountants of India (ICAI) will introduce Artificial Intelligence and forensic science in its curriculum for the Chartered Accountants to detect financial fraud at a much earlier stage. In most cases, the fraud is detected only when they reach a substantial volume. This new curriculum aims to track such irregularity at a much earlier stage so that the big scams either do not happen or are detected at the initial stages. This is the first time when the institute will bring such big technological changes in their international courses. President of ICAI, Debashish Mitra, said: "We are introducing artificial intelligence, data analytics and new forensic standards in the new curriculum. The mission of ICAI is to provide a strong foundation of knowledge, skill, and professional value that enables students to grow as wholesome professionals and adapt to change throughout their professional career."

The Artificial Intelligence (AI) market in India is set to reach $7.8 billion by 2025 -- covering hardware, software and services markets -- and growing at a CAGR (compound annual growth rate) of 20.2 per cent, a new report showed on Tuesday. The businesses in India will accelerate the adoption of both AI-centric and AI non-centric applications for the next five years, according to the International Data Corporation (IDC). AI software segment will dominate the market and would grow from $2.8 billion in 2020 at a CAGR of 18.1 per cent by the end of 2025. "Indian organisations plan to invest in AI to address current business scenarios across functions, such as customer service, human resources (HR), IT automation, security, recommendations, and many more," IDC India Associate Research Director, Cloud and AI, Rishu Sharma said. "Increasing business resilience and enhancing customer retention are among the top business objectives for using AI by Indian enterprises," Sharma added.

Google is all set to collaborate with researchers to develop new artificial intelligence (AI) algorithms to improve brain stimulation devices to treat people with psychiatric illness and direct brain injuries, such as stroke. The tech giant has tied up with researchers at Mayo Clinic to develop a set of paradigms, or viewpoints, that simplify comparisons between effects of electrical stimulation on the brain. They developed a new type of algorithm called "basis profile curve identification". "Our findings show that this new type of algorithm may help us understand which brain regions directly interact with one another, which in turn may help guide placement of electrodes for stimulating devices to treat network brain diseases," said Kai Miller, a Mayo Clinic neurosurgeon. "As new technology emerges, this type of algorithm may help us to better treat patients with epilepsy, movement disorders like Parkinson's disease, and psychiatric illnesses like obsessive compulsive disorder and depression," he added.

Elon Musk-founded startup OpenAI has discovered multimodal neurons in an Artificial Intelligence system that works just like some neurons work in the human brain. The revelation comes 15 years after the discovery that the human brain possesses multimodal neurons that respond to clusters of abstract concepts centered around a common high-level theme, rather than any specific visual feature. The most famous of these was the "Halle Berry" neuron that responds to photographs, sketches, and the text "Halle Berry" -- but not other names. Two months ago, OpenAI announced a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized. It is trained to recognize and people and objects within abstract contexts -- sketches, cartoons, and even statues of the objects.

Researchers have demonstrated that an artificial intelligence (AI) algorithm could be trained to classify Covid-19 pneumonia in computed tomography (CT) scans with up to 90 per cent accuracy. Also, it correctly identifies positive cases 84 per cent of the time and negative cases 93 per cent of the time. The study, recently published in Nature Communications, shows the new technique can also overcome some of the challenges of current testing. "We demonstrated that a deep learning-based AI approach can serve as a standardized and objective tool to assist healthcare systems as well as patients," said study author Ulas Bagci from the University of Central Florida in the US. "It can be used as a complementary test tool in very specific limited populations, and it can be used rapidly and at large scale in the unfortunate event of a recurrent outbreak," Bagci added.

Researchers, including two of Indian-origin, have developed an artificial intelligence (AI) algorithm which can help predict susceptibility to substance use disorder among young homeless individuals. The study, presented at the International Joint Conference on Artificial Intelligence, revealed that this algorithm can suggest personalized rehabilitation programs for highly susceptible homeless youth. "Proactive prevention of substance use disorder among homeless youth is much more desirable than reactive mitigation strategies such as medical treatments for the disorder and other related interventions," said study author Amulya Yadav from the Penn State University in the US. For the results, the research team built the model using a dataset collected from approximately 1,400 homeless youth, ages 18 to 26, in six US states. The dataset was collected by the Research, Education, and Advocacy Co-Lab for Youth Stability and Thriving (REALIST), which includes Anamika Barman-Adhikari, assistant professor at the University of Denver and co-author of the paper.